The gsll Reference Manual

This is the gsll Reference Manual, version 0, generated automatically by Declt version 4.0 beta 2 "William Riker" on Mon Feb 26 16:38:09 2024 GMT+0.

Table of Contents


1 Systems

The main system appears first, followed by any subsystem dependency.


1.1 gsll

GNU Scientific Library for Lisp.

Author

Liam M. Healy

License

GPL v3

Version

0

Defsystem Dependency

cffi-grovel (system).

Dependencies
  • foreign-array (system).
  • cffi-grovel (system).
  • trivial-garbage (system).
  • alexandria (system).
  • metabang-bind (system).
  • lisp-unit (system).
  • trivial-features (system).
Source

gsll.asd.

Child Components

2 Modules

Modules are listed depth-first from the system components tree.


2.1 gsll/init

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.2 gsll/floating-point

Dependency

init (module).

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.3 gsll/mathematical

Dependency

init (module).

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.4 gsll/data

Dependency

init (module).

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.5 gsll/special-functions

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.6 gsll/linear-algebra

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.7 gsll/eigensystems

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.8 gsll/fast-fourier-transforms

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.9 gsll/random

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.10 gsll/statistics

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.11 gsll/histogram

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.12 gsll/calculus

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.13 gsll/ordinary-differential-equations

Dependency

init (module).

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.14 gsll/interpolation

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.15 gsll/solve-minimize-fit

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.16 gsll/physical-constants

Dependency

init (module).

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.17 gsll/test-unit

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

2.18 gsll/tests

Dependency

test-unit (module).

Source

gsll.asd.

Parent Component

gsll (system).

Child Components

3 Files

Files are sorted by type and then listed depth-first from the systems components trees.


3.1 Lisp


3.1.1 gsll/gsll.asd

Source

gsll.asd.

Parent Component

gsll (system).

ASDF Systems

gsll.


3.1.2 gsll/init/init.lisp

Source

gsll.asd.

Parent Component

init (module).

Packages

gsll.

Internals

gsl-config-pathname (function).


3.1.3 gsll/init/libgsl.lisp

Dependency

init.lisp (file).

Source

gsll.asd.

Parent Component

init (module).


3.1.4 gsll/init/gsl-version.lisp

Dependency

init.lisp (file).

Source

gsll.asd.

Parent Component

init (module).

Public Interface

*gsl-version* (symbol macro).

Internals

3.1.5 gsll/init/utility.lisp

Dependency

init.lisp (file).

Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.6 gsll/init/forms.lisp

Dependency

init.lisp (file).

Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.7 gsll/init/conditions.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Public Interface
Internals

3.1.8 gsll/init/callback-compile-defs.lisp

Dependency

init.lisp (file).

Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.9 gsll/init/mobject.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Public Interface
  • evaluate (generic function).
  • name (generic function).
  • order (generic function).
  • size (generic function).
Internals

3.1.10 gsll/init/callback-included.lisp

Dependency

mobject.lisp (file).

Source

gsll.asd.

Parent Component

init (module).

Public Interface
Internals

3.1.11 gsll/init/callback.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.12 gsll/init/types.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.13 gsll/init/callback-struct.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).


3.1.14 gsll/init/funcallable.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.15 gsll/init/interface.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Public Interface

gsl-lookup (function).

Internals

3.1.16 gsll/init/defmfun.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.17 gsll/init/defmfun-array.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.18 gsll/init/defmfun-single.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Public Interface

name (reader method).

Internals

3.1.19 gsll/init/body-expand.lisp

Dependencies
Source

gsll.asd.

Parent Component

init (module).

Internals

3.1.20 gsll/init/generate-examples.lisp

Dependency

init.lisp (file).

Source

gsll.asd.

Parent Component

init (module).

Public Interface

examples (function).

Internals

3.1.21 gsll/init/generic.lisp

Source

gsll.asd.

Parent Component

init (module).

Public Interface

3.1.22 gsll/floating-point/ieee-modes.lisp

Source

gsll.asd.

Parent Component

floating-point (module).

Public Interface

set-floating-point-modes (function).


3.1.23 gsll/floating-point/floating-point.lisp

Source

gsll.asd.

Parent Component

floating-point (module).

Public Interface
Internals

3.1.24 gsll/mathematical/mathematical.lisp

Source

gsll.asd.

Parent Component

mathematical (module).

Public Interface
Internals

3.1.25 gsll/mathematical/complex.lisp

Source

gsll.asd.

Parent Component

mathematical (module).

Public Interface

3.1.26 gsll/data/array-structs.lisp

Source

gsll.asd.

Parent Component

data (module).


3.1.27 gsll/data/foreign-array.lisp

Dependency

array-structs.lisp (file).

Source

gsll.asd.

Parent Component

data (module).

Internals

3.1.28 gsll/data/vector.lisp

Dependencies
Source

gsll.asd.

Parent Component

data (module).

Public Interface

3.1.29 gsll/data/matrix.lisp

Dependencies
Source

gsll.asd.

Parent Component

data (module).

Public Interface

3.1.30 gsll/data/both.lisp

Dependencies
Source

gsll.asd.

Parent Component

data (module).

Public Interface
Internals

3.1.31 gsll/data/array-tests.lisp

Dependency

both.lisp (file).

Source

gsll.asd.

Parent Component

data (module).


3.1.32 gsll/data/permutation.lisp

Dependencies
Source

gsll.asd.

Parent Component

data (module).

Public Interface
Internals

3.1.33 gsll/data/combination.lisp

Dependencies
Source

gsll.asd.

Parent Component

data (module).

Public Interface
Internals

3.1.34 gsll/polynomial.lisp

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

allocate (method).


3.1.35 gsll/special-functions/sf-result.lisp

Source

gsll.asd.

Parent Component

special-functions (module).


3.1.36 gsll/special-functions/return-structures.lisp

Dependency

sf-result.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Internals

3.1.37 gsll/special-functions/airy.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.38 gsll/special-functions/bessel.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.39 gsll/special-functions/clausen.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

clausen (function).


3.1.40 gsll/special-functions/coulomb.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.41 gsll/special-functions/coupling.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.42 gsll/special-functions/dawson.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

dawson (function).


3.1.43 gsll/special-functions/debye.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.44 gsll/special-functions/dilogarithm.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

dilogarithm (generic function).


3.1.45 gsll/special-functions/elementary.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.46 gsll/special-functions/elliptic-integrals.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.47 gsll/special-functions/elliptic-functions.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

jacobian-elliptic-functions (function).

Internals

3.1.48 gsll/special-functions/error-functions.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.49 gsll/special-functions/exponential-functions.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.50 gsll/special-functions/exponential-integrals.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.51 gsll/special-functions/fermi-dirac.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.52 gsll/special-functions/gamma.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface
Internals

+gamma-xmax+ (constant).


3.1.53 gsll/special-functions/gegenbauer.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.54 gsll/special-functions/hypergeometric.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.55 gsll/special-functions/laguerre.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.56 gsll/special-functions/lambert.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.57 gsll/special-functions/legendre.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.58 gsll/special-functions/logarithm.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.59 gsll/special-functions/mathieu.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface
Internals

allocate (method).


3.1.60 gsll/special-functions/power.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

pow (function).


3.1.61 gsll/special-functions/psi.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.62 gsll/special-functions/synchrotron.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.63 gsll/special-functions/transport.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.64 gsll/special-functions/trigonometry.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.65 gsll/special-functions/zeta.lisp

Dependency

return-structures.lisp (file).

Source

gsll.asd.

Parent Component

special-functions (module).

Public Interface

3.1.66 gsll/sorting.lisp

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

defcomparison (macro).


3.1.67 gsll/linear-algebra/blas1.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface

3.1.68 gsll/linear-algebra/blas2.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

matrix-product-dimensions (function).


3.1.70 gsll/linear-algebra/matrix-generation.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Internals

3.1.71 gsll/linear-algebra/exponential.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface

matrix-exponential (function).


3.1.72 gsll/linear-algebra/lu.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

test-lu-solve-dim (function).


3.1.73 gsll/linear-algebra/qr.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

3.1.74 gsll/linear-algebra/qrpt.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

3.1.75 gsll/linear-algebra/svd.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

test-sv-solve-dim (function).


3.1.76 gsll/linear-algebra/cholesky.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

3.1.77 gsll/linear-algebra/diagonal.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

solve-tridiagonal-example (function).


3.1.78 gsll/linear-algebra/householder.lisp

Source

gsll.asd.

Parent Component

linear-algebra (module).

Public Interface
Internals

test-hh-solve-dim (function).


3.1.79 gsll/eigensystems/symmetric-hermitian.lisp

Source

gsll.asd.

Parent Component

eigensystems (module).

Public Interface
Internals

3.1.80 gsll/eigensystems/eigen-struct.lisp

Source

gsll.asd.

Parent Component

eigensystems (module).


3.1.81 gsll/eigensystems/nonsymmetric.lisp

Dependency

eigen-struct.lisp (file).

Source

gsll.asd.

Parent Component

eigensystems (module).

Public Interface
Internals

3.1.82 gsll/eigensystems/generalized.lisp

Source

gsll.asd.

Parent Component

eigensystems (module).

Public Interface
Internals

3.1.83 gsll/eigensystems/nonsymmetric-generalized.lisp

Source

gsll.asd.

Parent Component

eigensystems (module).

Public Interface
Internals

3.1.84 gsll/fast-fourier-transforms/wavetable-workspace.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface
Internals

3.1.85 gsll/fast-fourier-transforms/forward.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface

forward-fourier-transform (function).

Internals

3.1.86 gsll/fast-fourier-transforms/backward.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface

backward-fourier-transform (function).

Internals

3.1.87 gsll/fast-fourier-transforms/inverse.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface

inverse-fourier-transform (function).

Internals

3.1.88 gsll/fast-fourier-transforms/select-direction.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface

fourier-transform (function).

Internals

3.1.89 gsll/fast-fourier-transforms/unpack.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface

unpack (function).

Internals

3.1.90 gsll/fast-fourier-transforms/discrete.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface

3.1.91 gsll/fast-fourier-transforms/extras.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Public Interface
Internals

3.1.92 gsll/fast-fourier-transforms/example.lisp

Source

gsll.asd.

Parent Component

fast-fourier-transforms (module).

Internals

3.1.93 gsll/random/rng-types.lisp

Source

gsll.asd.

Parent Component

random (module).

Public Interface
Internals

3.1.94 gsll/random/generators.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface
Internals

3.1.95 gsll/random/quasi.lisp

Dependencies
Source

gsll.asd.

Parent Component

random (module).

Public Interface
Internals

3.1.96 gsll/random/tests.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Internals

3.1.97 gsll/random/gaussian.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.98 gsll/random/gaussian-tail.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.99 gsll/random/gaussian-bivariate.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.100 gsll/random/exponential.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.101 gsll/random/laplace.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.102 gsll/random/exponential-power.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.103 gsll/random/cauchy.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.104 gsll/random/rayleigh.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.105 gsll/random/rayleigh-tail.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.106 gsll/random/landau.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.107 gsll/random/levy.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.108 gsll/random/gamma.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.109 gsll/random/flat.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.110 gsll/random/lognormal.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.111 gsll/random/chi-squared.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.112 gsll/random/fdist.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.113 gsll/random/tdist.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.114 gsll/random/beta.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.115 gsll/random/logistic.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.116 gsll/random/pareto.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.117 gsll/random/spherical-vector.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.118 gsll/random/weibull.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.119 gsll/random/gumbel1.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.120 gsll/random/gumbel2.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.121 gsll/random/dirichlet.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.122 gsll/random/discrete.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface
Internals

allocate (method).


3.1.123 gsll/random/poisson.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.124 gsll/random/bernoulli.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.125 gsll/random/binomial.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.126 gsll/random/multinomial.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.127 gsll/random/negative-binomial.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.128 gsll/random/geometric.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.129 gsll/random/hypergeometric.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.130 gsll/random/logarithmic.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.131 gsll/random/shuffling-sampling.lisp

Dependency

rng-types.lisp (file).

Source

gsll.asd.

Parent Component

random (module).

Public Interface

3.1.132 gsll/statistics/mean-variance.lisp

Source

gsll.asd.

Parent Component

statistics (module).

Public Interface

3.1.133 gsll/statistics/absolute-deviation.lisp

Source

gsll.asd.

Parent Component

statistics (module).

Public Interface

3.1.134 gsll/statistics/higher-moments.lisp

Source

gsll.asd.

Parent Component

statistics (module).

Public Interface

3.1.135 gsll/statistics/autocorrelation.lisp

Source

gsll.asd.

Parent Component

statistics (module).

Public Interface

autocorrelation (generic function).


3.1.136 gsll/statistics/covariance.lisp

Source

gsll.asd.

Parent Component

statistics (module).

Public Interface

3.1.137 gsll/statistics/median-percentile.lisp

Source

gsll.asd.

Parent Component

statistics (module).

Public Interface

3.1.138 gsll/histogram/histogram.lisp

Source

gsll.asd.

Parent Component

histogram (module).

Public Interface
Internals

3.1.139 gsll/histogram/updating-accessing.lisp

Dependency

histogram.lisp (file).

Source

gsll.asd.

Parent Component

histogram (module).

Public Interface

3.1.140 gsll/histogram/statistics.lisp

Dependency

histogram.lisp (file).

Source

gsll.asd.

Parent Component

histogram (module).

Public Interface
Internals

3.1.141 gsll/histogram/operations.lisp

Dependency

histogram.lisp (file).

Source

gsll.asd.

Parent Component

histogram (module).

Public Interface

3.1.142 gsll/histogram/probability-distribution.lisp

Dependency

histogram.lisp (file).

Source

gsll.asd.

Parent Component

histogram (module).

Public Interface
Internals

3.1.143 gsll/histogram/ntuple.lisp

Source

gsll.asd.

Parent Component

histogram (module).

Public Interface
Internals

3.1.144 gsll/calculus/numerical-integration.lisp

Source

gsll.asd.

Parent Component

calculus (module).

Public Interface
Internals

3.1.145 gsll/calculus/numerical-integration-with-tables.lisp

Dependency

numerical-integration.lisp (file).

Source

gsll.asd.

Parent Component

calculus (module).

Public Interface
Internals

3.1.146 gsll/calculus/monte-carlo-structs.lisp

Source

gsll.asd.

Parent Component

calculus (module).


3.1.147 gsll/calculus/monte-carlo.lisp

Source

gsll.asd.

Parent Component

calculus (module).

Public Interface
Internals

3.1.148 gsll/calculus/numerical-differentiation.lisp

Source

gsll.asd.

Parent Component

calculus (module).

Public Interface
Internals

3.1.149 gsll/ordinary-differential-equations/ode-system.lisp

Source

gsll.asd.

Parent Component

ordinary-differential-equations (module).

Public Interface

with-ode-integration (macro).


3.1.150 gsll/ordinary-differential-equations/ode-struct.lisp

Source

gsll.asd.

Parent Component

ordinary-differential-equations (module).


3.1.151 gsll/ordinary-differential-equations/stepping.lisp

Dependency

ode-struct.lisp (file).

Source

gsll.asd.

Parent Component

ordinary-differential-equations (module).

Public Interface
Internals

3.1.152 gsll/ordinary-differential-equations/control.lisp

Source

gsll.asd.

Parent Component

ordinary-differential-equations (module).

Public Interface
Internals

3.1.153 gsll/ordinary-differential-equations/evolution.lisp

Source

gsll.asd.

Parent Component

ordinary-differential-equations (module).

Public Interface
Internals

allocate (method).


3.1.154 gsll/ordinary-differential-equations/ode-example.lisp

Dependencies
Source

gsll.asd.

Parent Component

ordinary-differential-equations (module).

Internals

3.1.155 gsll/interpolation/interpolation.lisp

Source

gsll.asd.

Parent Component

interpolation (module).

Public Interface
Internals

3.1.157 gsll/interpolation/lookup.lisp

Source

gsll.asd.

Parent Component

interpolation (module).

Public Interface
Internals

allocate (method).


3.1.158 gsll/interpolation/evaluation.lisp

Source

gsll.asd.

Parent Component

interpolation (module).

Public Interface

3.1.159 gsll/interpolation/spline-example.lisp

Dependency

types.lisp (file).

Source

gsll.asd.

Parent Component

interpolation (module).

Internals

3.1.160 gsll/chebyshev.lisp

Dependency

init (module).

Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

3.1.161 gsll/series-struct.lisp

Source

gsll.asd.

Parent Component

gsll (system).


3.1.162 gsll/series-acceleration.lisp

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

3.1.163 gsll/wavelet.lisp

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

3.1.164 gsll/hankel.lisp

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

allocate (method).


3.1.165 gsll/solve-minimize-fit/generic.lisp

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface

3.1.166 gsll/solve-minimize-fit/solver-struct.lisp

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).


3.1.167 gsll/solve-minimize-fit/roots-one.lisp

Dependency

generic.lisp (file).

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface
Internals

3.1.168 gsll/solve-minimize-fit/minimization-one.lisp

Dependency

generic.lisp (file).

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface
Internals

3.1.169 gsll/solve-minimize-fit/roots-multi.lisp

Dependencies
Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface
Internals

3.1.170 gsll/solve-minimize-fit/minimization-multi.lisp

Dependency

generic.lisp (file).

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface
Internals

3.1.171 gsll/solve-minimize-fit/linear-least-squares.lisp

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface
Internals

3.1.172 gsll/solve-minimize-fit/nonlinear-least-squares.lisp

Dependencies
Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface
Internals

3.1.173 gsll/solve-minimize-fit/simulated-annealing.lisp

Source

gsll.asd.

Parent Component

solve-minimize-fit (module).

Public Interface

simulated-annealing (function).

Internals

3.1.174 gsll/basis-splines.lisp

Dependencies
Source

gsll.asd.

Parent Component

gsll (system).

Public Interface
Internals

3.1.175 gsll/physical-constants/mksa.lisp

Source

gsll.asd.

Parent Component

physical-constants (module).


3.1.176 gsll/physical-constants/cgsm.lisp

Source

gsll.asd.

Parent Component

physical-constants (module).


3.1.177 gsll/physical-constants/num.lisp

Source

gsll.asd.

Parent Component

physical-constants (module).


3.1.178 gsll/physical-constants/export.lisp

Source

gsll.asd.

Parent Component

physical-constants (module).


3.1.179 gsll/test-unit/machine.lisp

Source

gsll.asd.

Parent Component

test-unit (module).


3.1.180 gsll/test-unit/augment.lisp

Dependency

machine.lisp (file).

Source

gsll.asd.

Parent Component

test-unit (module).

Internals

3.1.181 gsll/tests/absolute-deviation.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.182 gsll/tests/absolute-sum.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.183 gsll/tests/airy.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.184 gsll/tests/autocorrelation.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.185 gsll/tests/axpy.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.186 gsll/tests/basis-spline.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.187 gsll/tests/bernoulli.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.188 gsll/tests/bessel.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.189 gsll/tests/beta.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.190 gsll/tests/binomial.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.191 gsll/tests/blas-copy.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.192 gsll/tests/blas-swap.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.193 gsll/tests/cauchy.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.194 gsll/tests/cdot.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.195 gsll/tests/chebyshev.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.196 gsll/tests/chi-squared.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.197 gsll/tests/cholesky.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.198 gsll/tests/clausen.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.199 gsll/tests/column.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.200 gsll/tests/combination.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.201 gsll/tests/coulomb.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.202 gsll/tests/coupling.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.203 gsll/tests/correlation.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.204 gsll/tests/covariance.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.205 gsll/tests/dawson.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.206 gsll/tests/debye.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.207 gsll/tests/dilogarithm.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.208 gsll/tests/dirichlet.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.209 gsll/tests/discrete.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.210 gsll/tests/dot.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.211 gsll/tests/eigensystems.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.212 gsll/tests/elementary.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.213 gsll/tests/elliptic-functions.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.214 gsll/tests/elliptic-integrals.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.215 gsll/tests/error-functions.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.216 gsll/tests/euclidean-norm.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.217 gsll/tests/exponential-functions.lisp

Source

gsll.asd.

Parent Component

tests (module).

Internals

3.1.218 gsll/tests/exponential-integrals.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.219 gsll/tests/exponential.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.220 gsll/tests/exponential-power.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.221 gsll/tests/fast-fourier-transform.lisp

Source

gsll.asd.

Parent Component

tests (module).

Internals

3.1.222 gsll/tests/fdist.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.223 gsll/tests/fermi-dirac.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.224 gsll/tests/flat.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.225 gsll/tests/gamma.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.226 gsll/tests/gamma-randist.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.227 gsll/tests/gaussian-bivariate.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.228 gsll/tests/gaussian.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.229 gsll/tests/gaussian-tail.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.230 gsll/tests/gegenbauer.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.231 gsll/tests/geometric.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.232 gsll/tests/givens.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.233 gsll/tests/gumbel1.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.234 gsll/tests/gumbel2.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.235 gsll/tests/hankel.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.236 gsll/tests/higher-moments.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.237 gsll/tests/histogram.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.238 gsll/tests/householder.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.239 gsll/tests/hypergeometric.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.240 gsll/tests/hypergeometric-randist.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.241 gsll/tests/index-max.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.242 gsll/tests/interpolation.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.243 gsll/tests/inverse-matrix-product.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.244 gsll/tests/laguerre.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.245 gsll/tests/lambert.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.246 gsll/tests/landau.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.247 gsll/tests/laplace.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.248 gsll/tests/legendre.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.249 gsll/tests/levy.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.250 gsll/tests/linear-least-squares.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.251 gsll/tests/logarithmic.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.252 gsll/tests/logarithm.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.253 gsll/tests/logistic.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.254 gsll/tests/lognormal.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.255 gsll/tests/lu.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.256 gsll/tests/mathematical.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.257 gsll/tests/mathieu.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.258 gsll/tests/matrix-div.lisp

Source

gsll.asd.

Parent Component

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3.1.259 gsll/tests/matrix-max-index.lisp

Source

gsll.asd.

Parent Component

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3.1.260 gsll/tests/matrix-max.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.261 gsll/tests/matrix-mean.lisp

Source

gsll.asd.

Parent Component

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3.1.262 gsll/tests/matrix-min.lisp

Source

gsll.asd.

Parent Component

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3.1.263 gsll/tests/matrix-min-index.lisp

Source

gsll.asd.

Parent Component

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3.1.264 gsll/tests/matrix-minmax-index.lisp

Source

gsll.asd.

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3.1.265 gsll/tests/matrix-minmax.lisp

Source

gsll.asd.

Parent Component

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3.1.266 gsll/tests/matrix-sub.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.267 gsll/tests/matrix-add.lisp

Source

gsll.asd.

Parent Component

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3.1.268 gsll/tests/matrix-mult.lisp

Source

gsll.asd.

Parent Component

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3.1.269 gsll/tests/matrix-product-hermitian.lisp

Source

gsll.asd.

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3.1.270 gsll/tests/matrix-product.lisp

Source

gsll.asd.

Parent Component

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3.1.271 gsll/tests/matrix-product-nonsquare.lisp

Source

gsll.asd.

Parent Component

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3.1.272 gsll/tests/matrix-product-symmetric.lisp

Source

gsll.asd.

Parent Component

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3.1.273 gsll/tests/matrix-product-triangular.lisp

Source

gsll.asd.

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3.1.274 gsll/tests/matrix-set-all.lisp

Source

gsll.asd.

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3.1.275 gsll/tests/matrix-set-zero.lisp

Source

gsll.asd.

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3.1.276 gsll/tests/matrix-standard-deviation.lisp

Source

gsll.asd.

Parent Component

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3.1.277 gsll/tests/matrix-standard-deviation-with-fixed-mean.lisp

Source

gsll.asd.

Parent Component

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3.1.278 gsll/tests/matrix-standard-deviation-with-mean.lisp

Source

gsll.asd.

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tests (module).


3.1.279 gsll/tests/matrix-swap.lisp

Source

gsll.asd.

Parent Component

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3.1.280 gsll/tests/matrix-transpose-copy.lisp

Source

gsll.asd.

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3.1.281 gsll/tests/matrix-transpose.lisp

Source

gsll.asd.

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3.1.282 gsll/tests/matrix-variance.lisp

Source

gsll.asd.

Parent Component

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3.1.283 gsll/tests/matrix-variance-with-fixed-mean.lisp

Source

gsll.asd.

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3.1.284 gsll/tests/matrix-variance-with-mean.lisp

Source

gsll.asd.

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3.1.285 gsll/tests/median-percentile.lisp

Source

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Parent Component

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3.1.286 gsll/tests/minimization-one.lisp

Source

gsll.asd.

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3.1.287 gsll/tests/minimization-multi.lisp

Source

gsll.asd.

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3.1.288 gsll/tests/monte-carlo.lisp

Source

gsll.asd.

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3.1.289 gsll/tests/multinomial.lisp

Source

gsll.asd.

Parent Component

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3.1.290 gsll/tests/negative-binomial.lisp

Source

gsll.asd.

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3.1.291 gsll/tests/nonlinear-least-squares.lisp

Source

gsll.asd.

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3.1.292 gsll/tests/ntuple.lisp

Source

gsll.asd.

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3.1.293 gsll/tests/numerical-differentiation.lisp

Source

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3.1.294 gsll/tests/numerical-integration.lisp

Source

gsll.asd.

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3.1.295 gsll/tests/ode.lisp

Source

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3.1.296 gsll/tests/pareto.lisp

Source

gsll.asd.

Parent Component

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3.1.297 gsll/tests/permutation.lisp

Source

gsll.asd.

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3.1.298 gsll/tests/poisson.lisp

Source

gsll.asd.

Parent Component

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3.1.299 gsll/tests/polynomial.lisp

Source

gsll.asd.

Parent Component

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3.1.300 gsll/tests/power.lisp

Source

gsll.asd.

Parent Component

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3.1.301 gsll/tests/psi.lisp

Source

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3.1.302 gsll/tests/qr.lisp

Source

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3.1.303 gsll/tests/qrpt.lisp

Source

gsll.asd.

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3.1.304 gsll/tests/quasi-random-number-generators.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.305 gsll/tests/random-number-generators.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.306 gsll/tests/rank-1-update.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.307 gsll/tests/rayleigh.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.308 gsll/tests/rayleigh-tail.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.309 gsll/tests/roots-multi.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.310 gsll/tests/roots-one.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.311 gsll/tests/row.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.312 gsll/tests/scale.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.313 gsll/tests/series-acceleration.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.314 gsll/tests/set-basis.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.315 gsll/tests/setf-column.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.316 gsll/tests/setf-row.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.317 gsll/tests/set-identity.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.318 gsll/tests/shuffling-sampling.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.319 gsll/tests/sort-matrix-largest.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.320 gsll/tests/sort-matrix.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.321 gsll/tests/sort-matrix-smallest.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.322 gsll/tests/sort-vector-index.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.323 gsll/tests/sort-vector-largest-index.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.324 gsll/tests/sort-vector-largest.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.325 gsll/tests/sort-vector.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.326 gsll/tests/sort-vector-smallest-index.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.327 gsll/tests/sort-vector-smallest.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.328 gsll/tests/spherical-vector.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.329 gsll/tests/svd.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.330 gsll/tests/swap-columns.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.331 gsll/tests/swap-elements.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.332 gsll/tests/swap-row-column.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.333 gsll/tests/swap-rows.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.334 gsll/tests/synchrotron.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.335 gsll/tests/tdist.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.336 gsll/tests/transport.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.337 gsll/tests/trigonometry.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.338 gsll/tests/vector-div.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.339 gsll/tests/vector-max-index.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.340 gsll/tests/vector-max.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.341 gsll/tests/vector-mean.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.342 gsll/tests/vector-min.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.343 gsll/tests/vector-min-index.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.344 gsll/tests/vector-minmax-index.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.345 gsll/tests/vector-minmax.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.346 gsll/tests/vector-sub.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.347 gsll/tests/vector-add.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.348 gsll/tests/vector-mult.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.349 gsll/tests/vector-reverse.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.350 gsll/tests/vector-set-all.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.351 gsll/tests/vector-set-zero.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.352 gsll/tests/vector-standard-deviation.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.353 gsll/tests/vector-standard-deviation-with-fixed-mean.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.354 gsll/tests/vector-standard-deviation-with-mean.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.355 gsll/tests/vector-swap.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.356 gsll/tests/vector-variance.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.357 gsll/tests/vector-variance-with-fixed-mean.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.358 gsll/tests/vector-variance-with-mean.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.359 gsll/tests/weibull.lisp

Source

gsll.asd.

Parent Component

tests (module).


3.1.360 gsll/tests/zeta.lisp

Source

gsll.asd.

Parent Component

tests (module).


4 Packages

Packages are listed by definition order.


4.1 gsll

Source

init.lisp.

Nickname

gsl

Use List
  • cffi.
  • common-lisp.
Used By List

antik-user.

Public Interface
Internals

5 Definitions

Definitions are sorted by export status, category, package, and then by lexicographic order.


5.1 Public Interface


5.1.1 Constants

Constant: +nan+
Package

gsll.

Source

mathematical.lisp.

Constant: +negative-infinity+
Package

gsll.

Source

mathematical.lisp.

Constant: +positive-infinity+
Package

gsll.

Source

mathematical.lisp.


5.1.2 Special variables

Special Variable: *default-absolute-error*

The default absolute error used in numerical integration.

Package

gsll.

Source

numerical-integration.lisp.

Special Variable: *default-relative-error*

The default relative error used in numerical integration.

Package

gsll.

Source

numerical-integration.lisp.


5.1.3 Symbol macros

Symbol Macro: *gsl-version*
Package

gsll.

Source

gsl-version.lisp.

Symbol Macro: +akima-interpolation+
Package

gsll.

Source

types.lisp.

Symbol Macro: +bisection-fsolver+
Package

gsll.

Source

roots-one.lisp.

Symbol Macro: +borosh13+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +brent-fminimizer+
Package

gsll.

Source

minimization-one.lisp.

Symbol Macro: +brent-fsolver+
Package

gsll.

Source

roots-one.lisp.

Symbol Macro: +broyden+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +bspline-wavelet+
Package

gsll.

Source

wavelet.lisp.

Symbol Macro: +bspline-wavelet-centered+
Package

gsll.

Source

wavelet.lisp.

Symbol Macro: +cmrg+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +conjugate-fletcher-reeves+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +conjugate-polak-ribiere+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +coveyou+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +cubic-spline-interpolation+
Package

gsll.

Source

types.lisp.

Symbol Macro: +daubechies-wavelet+
Package

gsll.

Source

wavelet.lisp.

Symbol Macro: +daubechies-wavelet-centered+
Package

gsll.

Source

wavelet.lisp.

Symbol Macro: +default-seed+
Package

gsll.

Source

generators.lisp.

Symbol Macro: +default-type+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +discrete-newton+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +false-position-fsolver+
Package

gsll.

Source

roots-one.lisp.

Symbol Macro: +fishman18+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +fishman20+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +fishman2x+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +gfsr4+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +gnewton-mfdfsolver+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +golden-section-fminimizer+
Package

gsll.

Source

minimization-one.lisp.

Symbol Macro: +haar-wavelet+
Package

gsll.

Source

wavelet.lisp.

Symbol Macro: +haar-wavelet-centered+
Package

gsll.

Source

wavelet.lisp.

Symbol Macro: +halton+
Package

gsll.

Source

quasi.lisp.

Symbol Macro: +hybrid-scaled+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +hybrid-unscaled+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +knuthran+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +knuthran2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +knuthran2002+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +lecuyer21+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +levenberg-marquardt+
Package

gsll.

Source

nonlinear-least-squares.lisp.

Symbol Macro: +levenberg-marquardt-unscaled+
Package

gsll.

Source

nonlinear-least-squares.lisp.

Symbol Macro: +linear-interpolation+
Package

gsll.

Source

types.lisp.

Symbol Macro: +minstd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +mrg+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +mt19937+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +mt19937-1998+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +mt19937-1999+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +newton-fdfsolver+
Package

gsll.

Source

roots-one.lisp.

Symbol Macro: +newton-mfdfsolver+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +niederreiter2+
Package

gsll.

Source

quasi.lisp.

Symbol Macro: +periodic-akima-interpolation+
Package

gsll.

Source

types.lisp.

Symbol Macro: +periodic-cubic-spline-interpolation+
Package

gsll.

Source

types.lisp.

Symbol Macro: +polynomial-interpolation+
Package

gsll.

Source

types.lisp.

Symbol Macro: +powells-hybrid+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +powells-hybrid-unscaled+
Package

gsll.

Source

roots-multi.lisp.

Symbol Macro: +quad-golden-fminimizer+
Package

gsll.

Source

minimization-one.lisp.

Symbol Macro: +r250+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ran0+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ran1+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ran2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ran3+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +rand+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +rand48+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random128_bsd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random128_glibc2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random128_libc5+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random256_bsd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random256_glibc2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random256_libc5+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random32_bsd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random32_glibc2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random32_libc5+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random64_bsd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random64_glibc2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random64_libc5+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random8_bsd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random8_glibc2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random8_libc5+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random_bsd+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random_glibc2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +random_libc5+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +randu+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranf+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlux+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlux389+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlxd1+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlxd2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlxs0+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlxs1+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranlxs2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +ranmar+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +reverse-halton+
Package

gsll.

Source

quasi.lisp.

Symbol Macro: +secant-fdfsolver+
Package

gsll.

Source

roots-one.lisp.

Symbol Macro: +simplex-nelder-mead+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +simplex-nelder-mead-on2+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +simplex-nelder-mead-random+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +slatec+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +sobol+
Package

gsll.

Source

quasi.lisp.

Symbol Macro: +steffenson-fdfsolver+
Package

gsll.

Source

roots-one.lisp.

Symbol Macro: +step-bsimp+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-gear1+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-gear2+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rk2+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rk2imp+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rk4+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rk4imp+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rk8pd+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rkck+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +step-rkf45+
Package

gsll.

Source

stepping.lisp.

Symbol Macro: +taus+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +taus113+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +taus2+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +transputer+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +tt800+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +uni+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +uni32+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +vax+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +vector-bfgs+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +vector-bfgs2+
Package

gsll.

Source

minimization-multi.lisp.

Symbol Macro: +waterman14+
Package

gsll.

Source

rng-types.lisp.

Symbol Macro: +zuf+
Package

gsll.

Source

rng-types.lisp.


5.1.4 Macros

Macro: maref (mpointer class-name &rest indices)

Get or set (setf maref) the array element from the GSL mpointer. The class-name is the specific subclass name of grid:foreign-array.

Package

gsll.

Source

both.lisp.

Setf expander for this macro

(setf maref).

Macro: return-value-on-error (values error &body body)

Return the value(s) (a value or list of values) in case the specified GSL error is signalled in the body.

Package

gsll.

Source

conditions.lisp.

Macro: with-fourier-transform-environment ((wavetable workspace element-type dimension &optional half-complex) &body body)

Create an environment where all FFTs will be performed on vectors of the same type and with the same length. This allows to calculculate and reuse the wavetable and workspace only once.

The first and second arguments will be bound to the wavetable and workspace, the third argument is the element type of the vectors to be FFT’d and the fourth argument indicates the length of the vectors to which FFTs will be applied. Optionally, T can be given as a fifth argument if the element type of the vectors is real, but must be considered as half-complex.

Package

gsll.

Source

wavetable-workspace.lisp.

Macro: with-ode-integration ((function time step-size max-time dependent dimensions &key jacobian scalarsp stepper absolute-error relative-error) &body body)

Environment for integration of ordinary differential equations when dependent variables are individually named scalars.

Package

gsll.

Source

ode-system.lisp.


5.1.5 Setf expanders

Setf Expander: (setf maref) (&rest args)
Package

gsll.

Source

both.lisp.

Reader

maref (macro).

Writer

set-maref (macro).


5.1.6 Ordinary functions

Function: 1/gamma (x)

The reciprocal of the gamma function, 1/Gamma(x) using the real Lanczos method.

Package

gsll.

Source

gamma.lisp.

Function: accelerate (array levin)

From the terms of a series in array, compute the extrapolated
limit of the series using a Levin u-transform. Additional working space must be provided in levin. The extrapolated sum is returned with an estimate of the absolute error. The actual term-by-term sum is returned in
w->sum_plain. The algorithm calculates the truncation error
(the difference between two successive extrapolations) and round-off error (propagated from the individual terms) to choose an optimal number of terms for the extrapolation.

Package

gsll.

Source

series-acceleration.lisp.

Function: accelerate-truncated (array levin)

From the terms of a series in array, compute the extrapolated
limit of the series using a Levin u-transform. Additional working space must be provided in levin. The extrapolated sum is returned with an estimate of the absolute error. The actual term-by-term sum is returned in w->sum_plain. The algorithm terminates when the difference between two successive extrapolations reaches a minimum or is sufficiently small. The difference between these two values is used as estimate of the error and is stored in abserr_trunc. To improve the reliability of the algorithm the extrapolated values are replaced by moving averages when calculating the truncation error, smoothing out any fluctuations.

Package

gsll.

Source

series-acceleration.lisp.

Function: accelerated-interpolation-search (x-array x acceleration)

Search the data array x-array of size, using the given acceleration.
This is how lookups are performed during evaluation of an interpolation. The function returns an index i such that x_array[i] <= x < x_array[i+1]}.

Package

gsll.

Source

lookup.lisp.

Function: adjust-stepsize (control stepper current-y y-error dydt step-size)

Adjust the step-size using the control function
and the current values of current-y, y-error and dydt.
The stepping function stepper is also needed to determine the order of the method. If the error in the y-values y-error is found to be too large then the step-size is reduced and the function returns :step-size-decreased. If the error is sufficiently small then step-size may be increased and :step-size-increased is returned. The function returns :step-size-unchanged if the step-size is unchanged. The goal of the function is to estimate the largest step-size which satisfies the user-specified accuracy requirements for the current point.

Package

gsll.

Source

control.lisp.

Function: airy-ai (x &optional mode)

The Airy function Ai(x).

Package

gsll.

Source

airy.lisp.

Function: airy-ai-deriv (x &optional mode)

The Airy function derivative Ai’(x).

Package

gsll.

Source

airy.lisp.

Function: airy-ai-deriv-scaled (x &optional mode)

The scaled Airy function derivative S_A(x) Ai’(x).
For x>0 the scaling factor S_A(x) is exp(+(2/3) x^(3/2)), and is 1 for x<0.

Package

gsll.

Source

airy.lisp.

Function: airy-ai-scaled (x &optional mode)

The scaled Airy function S_A(x) Ai(x).
For x>0 the scaling factor S_A(x) is exp(+(2/3) x^(3/2)), and is 1 for x<0.

Package

gsll.

Source

airy.lisp.

Function: airy-bi (x &optional mode)

The Airy function Bi(x).

Package

gsll.

Source

airy.lisp.

Function: airy-bi-deriv (x &optional mode)

The Airy function derivative Bi’(x).

Package

gsll.

Source

airy.lisp.

Function: airy-bi-deriv-scaled (x &optional mode)

The scaled Airy function derivative S_B(x) Bi’(x). For x>0 the scaling factor S_B(x) is exp(-(2/3) x^(3/2)), and is 1 for x<0.

Package

gsll.

Source

airy.lisp.

Function: airy-bi-scaled (x &optional mode)

The scaled Airy function S_B(x) Bi(x).
For x>0 the scaling factor S_B(x) is exp(-(2/3) x^(3/2)), and is 1 for x<0.

Package

gsll.

Source

airy.lisp.

Function: airy-zero-ai (s)

The location of the s-th zero of the Airy function Ai(x).

Package

gsll.

Source

airy.lisp.

Function: airy-zero-ai-deriv (s)

The location of the s-th zero of the Airy function derivative Ai’(x).

Package

gsll.

Source

airy.lisp.

Function: airy-zero-bi (s)

The location of the s-th zero of the Airy function Bi(x).

Package

gsll.

Source

airy.lisp.

Function: airy-zero-bi-deriv (s)

The location of the s-th zero of the Airy function derivative Bi’(x).

Package

gsll.

Source

airy.lisp.

Function: all-random-number-generators ()

A list of all random number generator types.

Package

gsll.

Source

rng-types.lisp.

Function: apply-evolution (evolution time y step-size control stepper max-time)

Advance the system (e, dydt) from time
and position y using the stepping function step.
The new time and position are stored in time and y on output.
The initial step-size supplied, but this will be modified
using the control function to achieve the appropriate error
bound if necessary. The routine may make several calls to step in order to determine the optimum step-size. If the step-size has been changed the value of step-size will be modified on output. The maximum time max-time is guaranteed not to be exceeded by the time-step. On the final time-step the value of time will be set to t1 exactly.

Package

gsll.

Source

evolution.lisp.

Function: apply-hankel (hankel array-in &optional array-out)

Apply the transform to the array array-in
whose size is equal to the size of the transform. The result is stored in the array array-out which must be of the same length.

Package

gsll.

Source

hankel.lisp.

Function: apply-step (stepper time y step-size yerr dydt-in dydt-out)

Apply the stepping function stepper to the system of equations defined by make-ode-stepper, using the step size step-size to advance the system from time time and state y to time t + step-size. The new state of the system is stored in y on output, with an estimate of the absolute error in each component stored in yerr If the argument dydt-in is not null it should point an array containing the derivatives for the system at time t on input. This is optional as the derivatives will be computed internally if they are not provided, but allows the reuse of existing derivative information. On output the new derivatives of the system at time t + step-size will be stored in dydt-out if it is not null.

User-supplied functions defined in the system dydt
should signal an error or return the correct value.

Package

gsll.

Source

stepping.lisp.

Function: argument (number)

The angle of the complex number.

Package

gsll.

Source

complex.lisp.

Function: atanint (x)

The Arctangent integral, which is defined as AtanInt(x) = int_0^x dt arctan(t)/t.

Package

gsll.

Source

exponential-integrals.lisp.

Function: backward-derivative (function x step)

Compute the numerical derivative of the function at the point x using an adaptive backward difference algorithm with a step-size of step. The function is evaluated only at points less than x, and never at x itself. The derivative is returned in result and an estimate of its absolute error is returned as the second value. This function should be used if f(x) has a discontinuity at x, or is undefined for values greater than x. This function is equivalent to calling #’forward-derivative with a negative step-size.

Package

gsll.

Source

numerical-differentiation.lisp.

Function: backward-fourier-transform (vector &rest args &key decimation-in-frequency stride non-radix-2 &allow-other-keys)

Perform a backward fast Fourier transform on the given vector. If the length of the vector is not a power of 2, and the user has a suitable wavetable and/or workspace, these can be supplied as keyword arguments. If the vector is real, it is assumed to be in half-complex form. If the length of the vector is a power of 2, use of a non-radix-2 transform can be forced.

Package

gsll.

Source

backward.lisp.

Function: bernoulli-pdf (k p)

The probability p(k) of obtaining
k from a Bernoulli distribution with probability parameter p, using the formula given in #’sample :bernoulli.

Package

gsll.

Source

bernoulli.lisp.

Function: bessel-lnknu (nu x)

The logarithm of the irregular modified Bessel function of fractional order nu, ln(K_nu(x)) for x>0, nu>0.

Package

gsll.

Source

bessel.lisp.

Function: bessel-zero-j0 (s)

The location of the s-th positive zero of the Bessel function J_0(x).

Package

gsll.

Source

bessel.lisp.

Function: bessel-zero-j1 (s)

The location of the s-th positive zero of the Bessel function J_1(x).

Package

gsll.

Source

bessel.lisp.

Function: bessel-zero-jnu (nu s)

These routines compute the location of the s-th positive zero of the Bessel function J_nu(x). The current implementation does not support negative values of nu.

Package

gsll.

Source

bessel.lisp.

Function: beta (a b)

The Beta Function, B(a,b) = Gamma(a)Gamma(b)/Gamma(a+b)} for a > 0, b > 0.

Package

gsll.

Source

gamma.lisp.

Function: beta-p (x a b)

The cumulative distribution functions
P(x) for the beta distribution with parameters a and b.

Package

gsll.

Source

beta.lisp.

Function: beta-pdf (x a b)

The probability density p(x) at x
for a beta distribution with parameters a and b, using the formula given in #’sample :beta.

Package

gsll.

Source

beta.lisp.

Function: beta-pinv (p a b)

The inverse cumulative distribution functions
P(x) for the beta distribution with parameters a and b.

Package

gsll.

Source

beta.lisp.

Function: beta-q (x a b)

The cumulative distribution functions
Q(x) for the beta distribution with parameters a and b.

Package

gsll.

Source

beta.lisp.

Function: beta-qinv (q a b)

The inverse cumulative distribution functions
Q(x) for the beta distribution with parameters a and b.

Package

gsll.

Source

beta.lisp.

Function: bidiagonal-decomposition (a tau-u tau-v)

Factorize the M-by-N matrix A into
bidiagonal form U B V^T. The diagonal and superdiagonal of the matrix B are stored in the diagonal and superdiagonal of A, The orthogonal matrices U and V are stored as compressed Householder vectors in the remaining elements of A. The Householder coefficients are stored in the vectors tau-U and tau-V. The length of tau-U must equal the number of elements in the diagonal of A and the length of tau-V should be one element shorter.

Package

gsll.

Source

diagonal.lisp.

Function: bidiagonal-unpack (a tau-u u tau-v v diag superdiag)

Unpack the bidiagonal decomposition of A given by #’bidiagonal-decomposition (A, tau-U, tau-V)
into the separate orthogonal matrices U, V, and the diagonal vector diag and superdiagonal superdiag. Note that U
is stored as a compact M-by-N orthogonal matrix satisfying U^T U = I for efficiency.

Package

gsll.

Source

diagonal.lisp.

Function: bidiagonal-unpack-diagonal-superdiagonal (a diag superdiag)

Unpack the diagonal and superdiagonal of the bidiagonal decomposition of A given by #’bidiagonal-decomposition, into the diagonal vector diag and superdiagonal vector superdiag.

Package

gsll.

Source

diagonal.lisp.

Function: bidiagonal-unpack2 (a tau-u tau-v v)

Unpack the bidiagonal decomposition of A given by #’bidiagonal-decomposition (A, tau-U, tau-V)
into the separate orthogonal matrices U, V and the diagonal vector diag and superdiagonal superdiag. The matrix U is stored in-place in A.

Package

gsll.

Source

diagonal.lisp.

Function: binomial (generator p n)

A random integer from the binomial distribution,
the number of successes in n independent trials with probability p. The probability distribution for binomial variates is, p(k) = {n! over k! (n-k)!} p^k (1-p)^{n-k}
0 <= k <= n.

Package

gsll.

Source

binomial.lisp.

Function: binomial-p (k p n)

The cumulative distribution functions
P(k) for the Binomial distribution with parameters p and n.

Package

gsll.

Source

binomial.lisp.

Function: binomial-pdf (k p n)

The probability p(k) of obtaining k
from a binomial distribution with parameters p and n, using the formula given in #’binomial.

Package

gsll.

Source

binomial.lisp.

Function: binomial-q (k p n)

The cumulative distribution functions Q(k) for the Binomial distribution with parameters p and n.

Package

gsll.

Source

binomial.lisp.

Function: bivariate-gaussian-pdf (x y sigma-x sigma-y rho)

The probability density p(x,y) at
(x,y) for a bivariate Gaussian distribution with standard deviations sigma_x, sigma_y and correlation coefficient rho, using the formula given for #’sample :bivariate-gaussian.

Package

gsll.

Source

gaussian-bivariate.lisp.

Function: bookdata-ntuple (ntuple)

A synonym for #’write-ntuple}.

Package

gsll.

Source

ntuple.lisp.

Function: breakpoint (i bspline)

The ith breakpoint of the basis spline bspline.

Package

gsll.

Source

basis-splines.lisp.

Function: canonical-cycles (p)

Count the number of cycles in the permutation q, given in canonical form.

Package

gsll.

Source

permutation.lisp.

Function: canonical-to-linear (q &optional p)

Convert a permutation q in canonical form back into linear form storing it in the output argument p.

Package

gsll.

Source

permutation.lisp.

Function: cauchy-p (x a)

The cumulative distribution functions
P(x) for the Cauchy distribution with scale parameter a.

Package

gsll.

Source

cauchy.lisp.

Function: cauchy-pdf (x a)

The probability density p(x) at x
for a Cauchy distribution with scale parameter a, using the formula given for #’sample :cauchy.

Package

gsll.

Source

cauchy.lisp.

Function: cauchy-pinv (p a)

The inverse cumulative distribution functions
P(x) for the Cauchy distribution with scale parameter a.

Package

gsll.

Source

cauchy.lisp.

Function: cauchy-q (x a)

The cumulative distribution functions
Q(x) for the Cauchy distribution with scale parameter a.

Package

gsll.

Source

cauchy.lisp.

Function: cauchy-qinv (q a)

The inverse cumulative distribution functions
Q(x) for the Cauchy distribution with scale parameter a.

Package

gsll.

Source

cauchy.lisp.

Function: central-derivative (function x step)

Compute the numerical derivative of the function
at the point x using an adaptive central difference algorithm with
a step-size of step. The derivative and an
estimate of its absolute error is returned.

The initial value of step is used to estimate an optimal step-size, based on the scaling of the truncation error and round-off error in the derivative calculation. The derivative is computed using a 5-point rule for equally spaced abscissae at x-step, x-step/2, x,
x+step/2, x, with an error estimate taken from the difference between the 5-point rule and the corresponding 3-point rule x-step, x, x+step. Note that the value of the function at x
does not contribute to the derivative calculation, so only 4-points are actually used.

Package

gsll.

Source

numerical-differentiation.lisp.

Function: chi (x)

The integral
Chi(x) := Re[ gamma_E + log(x) + int_0^x dt (cosh[t]-1)/t], where gamma_E} is the Euler constant.

Package

gsll.

Source

exponential-integrals.lisp.

Function: chi-squared-p (x nu)

The cumulative distribution functions
P(x) for the chi-squared distribution with nu degrees of freedom.

Package

gsll.

Source

chi-squared.lisp.

Function: chi-squared-pdf (x nu)

The probability density p(x) at x
for a chi-squared distribution with nu degrees of freedom, using the formula given in #’sample :chi-squared.

Package

gsll.

Source

chi-squared.lisp.

Function: chi-squared-pinv (p nu)

The inverse cumulative distribution functions
P(x) for the chi-squared distribution with nu degrees of freedom.

Package

gsll.

Source

chi-squared.lisp.

Function: chi-squared-q (x nu)

The cumulative distribution functions
Q(x) for the chi-squared distribution with nu degrees of freedom.

Package

gsll.

Source

chi-squared.lisp.

Function: chi-squared-qinv (q nu)

The inverse cumulative distribution functions
Q(x) for the chi-squared distribution with nu degrees of freedom.

Package

gsll.

Source

chi-squared.lisp.

Function: cholesky-invert (cholesky)

Compute the inverse of the matrix cholesky which must have been previously computed by #’cholesky-decomposition. The inverse of the original matrix is stored in cholesky on output.

Package

gsll.

Source

cholesky.lisp.

Function: choose (n m)

The combinatorial factor (n choose m) = n!/(m!(n-m)!).

Package

gsll.

Source

gamma.lisp.

Function: ci (x)

The Cosine integral Ci(x) = -int_x^infty dt cos(t)/t for x > 0.

Package

gsll.

Source

exponential-integrals.lisp.

Function: clausen (x)

The Clausen integral Cl_2(x).

Package

gsll.

Source

clausen.lisp.

Function: close-ntuple (ntuple)

Closes the ntuple file and frees its associated allocated memory.

Package

gsll.

Source

ntuple.lisp.

Function: coefficients (chebyshev)

The Chebyshev coefficient array as a CL array (foreign-friendly).

Package

gsll.

Source

chebyshev.lisp.

Function: combination-next (c)

Advance the combination c to the next combination in lexicographic order and return c. If no further combinations are available it returns NIL. Starting with the first combination and repeatedly applying this function will iterate through all possible combinations of a given order.

Package

gsll.

Source

combination.lisp.

Function: combination-previous (c)

Step backwards from the combination c to the previous combination in lexicographic order, returning c. If no previous combination is available it returns NIL with c unmodified.

Package

gsll.

Source

combination.lisp.

Function: combination-range (c)

The range (n), or maximum possible value (n in the (n k) notation) of the combination c.

Package

gsll.

Source

combination.lisp.

Function: complementary-incomplete-gamma (a x)

The complementary normalized incomplete Gamma Function P(a,x) = 1/Gamma(a) int_0^x dt t^{a-1} exp(-t)}
for a > 0, x >= 0. Note that Abramowitz & Stegun call P(a,x) the incomplete gamma function (section 6.5).

Package

gsll.

Source

gamma.lisp.

Function: control-alloc (control-type)

Return a pointer to a newly allocated instance of a
control function of type control-type. This function is only needed for defining new types of control functions. For most purposes the standard control functions described above should be sufficient.

Package

gsll.

Source

control.lisp.

Function: cos-err (x dx)

The cosine of an angle x with an associated absolute error dx, cos(x pm dx).

Package

gsll.

Source

trigonometry.lisp.

Function: coulomb-cl (l eta)

The Coulomb wave function normalization constant C_L(eta) for L > -1.

Package

gsll.

Source

coulomb.lisp.

Function: coulomb-cl-array (l-min eta &optional size-or-array)

The Coulomb wave function normalization constant C_L(eta) for L = Lmin ... Lmin + kmax, Lmin > -1.

Package

gsll.

Source

coulomb.lisp.

Function: coulomb-wave-f-array (l-min eta x &optional size-or-array)

The Coulomb wave function F_L(eta,x) for
L = Lmin ... Lmin + kmax, storing the results in fc-array.
In the case of overflow the exponent is stored in the second value returned.

Package

gsll.

Source

coulomb.lisp.

Function: coulomb-wave-fg (eta x l-f k)

The Coulomb wave functions F_L(eta,x),
G_{L-k}(eta,x) and their derivatives F’_L(eta,x), G’_{L-k}(eta,x) with respect to x. The parameters are restricted to L, L-k > -1/2}, x > 0 and integer k. Note that L itself is not restricted to being an integer. The results are stored in the parameters F, G for the function values and Fp, Gp for the derivative values. If an overflow occurs, the condition ’overflow is signalled and scaling exponents are stored in the modifiable parameters exp-F, exp-G.

Package

gsll.

Source

coulomb.lisp.

Function: coulomb-wave-fg-array (l-min eta x &optional fc-size-or-array gc-size-or-array)

The functions F_L(eta,x),
G_L(eta,x) for L = Lmin ... Lmin + kmax storing the results in fc_array and gc_array. In the case of overflow the exponents are stored in F_exponent and G_exponent.

Package

gsll.

Source

coulomb.lisp.

Function: coulomb-wave-fgp-array (l-min eta x &optional fc-size-or-array fcp-size-or-array gc-size-or-array gcp-size-or-array)

The functions F_L(eta,x),
G_L(eta,x) and their derivatives F’_L(eta,x),
G’_L(eta,x) for L = Lmin ... Lmin + kmax storing the results in fc_array, gc_array, fcp_array and gcp_array.
In the case of overflow the exponents are stored in F_exponent and G_exponent.

Package

gsll.

Source

coulomb.lisp.

Function: coulomb-wave-sphf-array (l-min eta x &optional size-or-array)

The Coulomb wave function divided by the argument
F_L(eta, x)/x for L = Lmin ... Lmin + kmax, storing the results in fc_array. In the case of overflow the exponent is stored in F_exponent. This function reduces to spherical Bessel functions in the limit eta to 0.

Package

gsll.

Source

coulomb.lisp.

Function: coupling-3j (two-ja two-jb two-jc two-ma two-mb two-mc)

The Wigner 3-j coefficient,
pmatrix{ja & jb & jccr
ma & mb & mccr}
where the arguments are given in half-integer units, ja = two_ja/2, ma = two_ma/2, etc.

Package

gsll.

Source

coupling.lisp.

Function: coupling-6j (two-ja two-jb two-jc two-jd two-je two-jf)

The Wigner 6-j coefficient,
ja & jb & jc
jd & je & jf
where the arguments are given in half-integer units, ja = two_ja/2, ma = two_ma/2, etc.

Package

gsll.

Source

coupling.lisp.

Function: coupling-9j (two-ja two-jb two-jc two-jd two-je two-jf two-jg two-jh two-ji)

The Wigner 9-j coefficient,
ja & jb & jc
jd & je & jf
jg & jh & ji
where the arguments are given in half-integer units, ja = two_ja/2, ma = two_ma/2, etc.

Package

gsll.

Source

coupling.lisp.

Function: create-ntuple (filename data foreign-type)

Create a new write-only ntuple file filename for
ntuples of size and return a pointer to the newly created
ntuple struct. Any existing file with the same name is truncated to zero length and overwritten. A pointer to memory for the current ntuple row data must be supplied—this is used to copy ntuples
in and out of the file.

Package

gsll.

Source

ntuple.lisp.

Function: cx-add (c1 c2)
Package

gsll.

Source

complex.lisp.

Function: cx-add-imag (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-add-real (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-arccos (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arccos-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-arccosh (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arccosh-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-arccot (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arccoth (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arccsc (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arccsc-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-arccsch (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arcsec (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arcsec-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-arcsech (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arcsin (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arcsin-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-arcsinh (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arctan (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arctanh (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-arctanh-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-conjugate (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-cos (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-cosh (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-cot (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-coth (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-csc (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-csch (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-div (c1 c2)
Package

gsll.

Source

complex.lisp.

Function: cx-div-imag (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-div-real (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-exp (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-expt (c1 c2)
Package

gsll.

Source

complex.lisp.

Function: cx-expt-real (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-inverse (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-log (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-log10 (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-logb (c1 c2)
Package

gsll.

Source

complex.lisp.

Function: cx-mul (c1 c2)
Package

gsll.

Source

complex.lisp.

Function: cx-mul-imag (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-mul-real (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-negative (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-sec (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-sech (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-sin (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-sinh (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-sqrt (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-sqrt-real (num)
Package

gsll.

Source

complex.lisp.

Function: cx-sub (c1 c2)
Package

gsll.

Source

complex.lisp.

Function: cx-sub-imag (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-sub-real (c1 num)
Package

gsll.

Source

complex.lisp.

Function: cx-tan (c1)
Package

gsll.

Source

complex.lisp.

Function: cx-tanh (c1)
Package

gsll.

Source

complex.lisp.

Function: cylindrical-bessel-i0 (x)

The regular modified cylindrical Bessel function of zeroth order, I_0(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-i0-scaled (x)

The scaled regular modified cylindrical Bessel function of zeroth order, exp(-|x|) I_0(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-i1 (x)

The regular modified cylindrical Bessel function of first order, I_1(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-i1-scaled (x)

The scaled regular modified cylindrical Bessel function of first order, exp(-|x|) I_1(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-in-array (x &optional size-or-array nmin)

The values of the regular modified cylindrical Bessel functions I_n(x) for n from from nmin to nmin+length(array)-1 inclusive.
The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-in-scaled-array (x &optional size-or-array nmin)

The values of the scaled regular modified cylindrical Bessel functions I_n(x) for n from from nmin to nmin+length(array)-1 inclusive. The values are computed using recurrence
relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-j-array-order (x &optional size-or-array nmin)

The values of the regular cylindrical Bessel functions J_n(x)
for n from nmin to nmin+length(array)-1 inclusive.
The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-j-array-x (nu v &optional mode)

The regular cylindrical Bessel function of
fractional order nu, J_nu(x), evaluated at a series of x values. The array v contains the x values.
They are assumed to be strictly ordered and positive. The array is over-written with the values of J_nu(x_i).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-j0 (x)

The regular cylindrical Bessel function of zeroth order, J_0(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-j1 (x)

The regular cylindrical Bessel function of first order, J_1(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-k0 (x)

The irregular modified cylindrical Bessel function of zeroth order, K_0(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-k0-scaled (x)

The scaled irregular modified cylindrical Bessel function of zeroth order, exp(-|x|) K_0(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-k1 (x)

The irregular modified cylindrical Bessel function of first order, K_1(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-k1-scaled (x)

The scaled irregular modified cylindrical Bessel function of first order, exp(-|x|) K_1(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-kn-array (x &optional size-or-array nmin)

The values of the irregular modified cylindrical Bessel functions K_n(x) for n from from nmin to nmin+length(array)-1 inclusive.
The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-kn-scaled-array (x &optional size-or-array nmin)

The values of the scaled irregular cylindrical
Bessel functions exp(x) K_n(x) for n from from nmin to nmin+length(array)-1 inclusive.
The start of the range nmin must be positive
or zero. The domain of the function is x>0. The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-y0 (x)

The irregular cylindrical Bessel function of zeroth order, Y_0(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-y1 (x)

The irregular cylindrical Bessel function of first order, Y_1(x).

Package

gsll.

Source

bessel.lisp.

Function: cylindrical-bessel-yn-array (x &optional size-or-array nmin)

The values of the irregular cylindrical Bessel functions
Y_n(x) for n from from nmin to
nmin+length(array)-1 inclusive. The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: dawson (x)

Dawson’s integral for x.

Package

gsll.

Source

dawson.lisp.

Function: debye-1 (x)

The first-order Debye function D_1(x) = (1/x) int_0^x dt (t/(e^t - 1)).

Package

gsll.

Source

debye.lisp.

Function: debye-2 (x)

The second-order Debye function
D_2(x) = (2/x^2) int_0^x dt (t^2/(e^t - 1)).

Package

gsll.

Source

debye.lisp.

Function: debye-3 (x)

The third-order Debye function
D_3(x) = (3/x^3) int_0^x dt (t^3/(e^t - 1)).

Package

gsll.

Source

debye.lisp.

Function: debye-4 (x)

The fourth-order Debye function
D_4(x) = (4/x^4) int_0^x dt (t^4/(e^t - 1)).

Package

gsll.

Source

debye.lisp.

Function: derivative-chebyshev (derivative chebyshev)

Compute the derivative of the Chebyshev series, storing
the derivative coefficients in the previously allocated series. The two series must have been allocated with the same order.

Package

gsll.

Source

chebyshev.lisp.

Function: dirichlet-log-pdf (alpha theta)

The logarithm of the probability density p(theta_1, ... , theta_K)
for a Dirichlet distribution with parameters alpha[K].

Package

gsll.

Source

dirichlet.lisp.

Function: dirichlet-pdf (alpha theta)

The probability density p(theta_1, ... , theta_K)
at theta[K] for a Dirichlet distribution with parameters alpha[K], using the formula given for #’sample :dirichlet.

Package

gsll.

Source

dirichlet.lisp.

Function: discrete-pdf (k table)

The probability P[k] of observing the variable k.
Since P[k] is not stored as part of the lookup table, it must be recomputed; this computation takes O(K), so if K is large and you care about the original array P[k] used to create the lookup table, then you should just keep this original array P[k] around.

Package

gsll.

Source

discrete.lisp.

Function: divided-difference (xa ya &optional dd)

Compute a divided-difference representation of the interpolating polynomial for the points (xa, ya) stored in the arrays of equal length. On output the divided-differences of (xa,ya) are stored in the array dd, of the same length.

Package

gsll.

Source

polynomial.lisp.

Function: double-factorial (n)

The double factorial n!! = n(n-2)(n-4) dots.

Package

gsll.

Source

gamma.lisp.

Function: double-float-unequal (x y epsilon)

This function determines whether x and y are approximately equal to a relative accuracy epsilon.

The relative accuracy is measured using an interval of size 2 delta, where delta = 2^k epsilon and k is the maximum base-2 exponent of x and y as computed by the function frexp().

If x and y lie within this interval, they are considered approximately equal and the function returns nil. Otherwise if x < y, the function returns -1, or if x > y, the function returns +1.

Package

gsll.

Source

mathematical.lisp.

Function: eigenvalues-eigenvectors-gen (a b &optional alpha beta eigenvectors ws compute-shur-form-s compute-shur-form-t shur-vectors)

Compute eigenvalues and right eigenvectors of the n-by-n real generalized nonsymmetric matrix pair (A, B). The eigenvalues are stored in (alpha, beta) and the eigenvectors are stored in evec. It first calls eigenvalues-gen to compute the eigenvalues, Schur forms, and Schur vectors. Then it finds eigenvectors of the Schur forms and backtransforms them using the Schur vectors. The Schur vectors are destroyed in the process, but can be saved by using setting shur-vectors true. The computed eigenvectors are normalized to have unit magnitude. On output, (A, B) contains the generalized Schur form (S, T).

If compute-shur-form-s is true, the full Schur form S will be computed. If it is NIL, S will not be computed (this is the default setting). S is a quasi upper triangular matrix with 1-by-1 and 2-by-2 blocks on its diagonal. 1-by-1 blocks correspond to real eigenvalues, and 2-by-2 blocks correspond to complex eigenvalues.

If compute-shur-form-t true, the full Schur form T will be computed. If it is NIL, T will not be
computed (this is the default setting). T is an upper triangular matrix with non-negative elements on its diagonal. Any 2-by-2 blocks in S will correspond to a 2-by-2 diagonal block in T.

Package

gsll.

Source

nonsymmetric-generalized.lisp.

Function: eigenvalues-eigenvectors-nonsymm (a &optional eigenvalues eigenvectors ws shur-vectors)

Compute eigenvalues and right eigenvectors of the n-by-n real nonsymmetric matrix A. It first calls #’eigenvalues-nonsymm to compute the eigenvalues, Schur form T, and Schur vectors. Then it finds eigenvectors of T and backtransforms them using the Schur vectors. The Schur vectors are destroyed in the process, but can be saved by specifying binding shur-vectors to a vector of length n, or t to have it automatically made. The computed eigenvectors are normalized to have unit magnitude. On output, the upper portion of A contains the Schur form T. If #’eigenvalues-nonsymm fails, no eigenvectors are computed, and an error code is returned.

Package

gsll.

Source

nonsymmetric.lisp.

Function: eigenvalues-gen (a b &optional alpha beta ws compute-shur-form-s compute-shur-form-t shur-vectors)

Compute the eigenvalues of the real generalized nonsymmetric matrix pair (A, B), and store them as pairs in (alpha, beta), where alpha is complex and beta is real. If beta_i is non-zero, then lambda = alpha_i / beta_i is an eigenvalue. Likewise, if alpha_i is non-zero, then mu = beta_i / alpha_i is an eigenvalue of the alternate problem mu A y = B y. The elements of beta are normalized to be non-negative.

If S is desired, it is stored in A on output. If T is desired, it is stored in B on output. The ordering of eigenvalues in (alpha, beta) follows the ordering of the diagonal blocks in the Schur forms S and T. In rare cases, this function may fail to find all eigenvalues. If this occurs, an error code is returned.

If compute-shur-form-s is true, the full Schur form S will be computed. If it is NIL, S will not be computed (this is the default setting). S is a quasi upper triangular matrix with 1-by-1 and 2-by-2 blocks on its diagonal. 1-by-1 blocks correspond to real eigenvalues, and 2-by-2 blocks correspond to complex eigenvalues.

If compute-shur-form-t true, the full Schur form T will be computed. If it is NIL, T will not be
computed (this is the default setting). T is an upper triangular matrix with non-negative elements on its diagonal. Any 2-by-2 blocks in S will correspond to a 2-by-2 diagonal block in T.

Package

gsll.

Source

nonsymmetric-generalized.lisp.

Function: eigenvalues-nonsymm (a &optional eigenvalues ws compute-shur-form balance shur-vectors)

Compute the eigenvalues of the real nonsymmetric matrix A and stores them in the vector ’eigenvalues. If T is desired, it is stored in the upper portion of A on output. Otherwise, on output, the diagonal of A will contain the 1-by-1 real eigenvalues and 2-by-2 complex conjugate eigenvalue systems, and the rest of A is destroyed. In rare cases, this function may fail to find all eigenvalues. If this happens, a warning is signalled and the number of converged eigenvalues is returned as a second value. The converged eigenvalues are stored in the beginning of eval.

If compute-shur-form is true, the full Schur form T will be computed. If it is set to nil, T will not be computed (this is
the default setting). Computing the full Schur form requires approximately 1.5-2 times the number of flops.

If balance is true, a balancing transformation is applied to the matrix prior to computing eigenvalues. This transformation is designed to make the rows and columns of the matrix have comparable norms, and can result in more accurate eigenvalues for matrices whose entries vary widely in magnitude. See Balancing for more information. Note that the balancing transformation does not preserve the orthogonality of the Schur vectors, so if you wish to compute the Schur vectors with you will obtain the Schur vectors of the balanced matrix instead of the original matrix. The relationship will be

T = Q^t D^(-1) A D Q

where Q is the matrix of Schur vectors for the balanced matrix, and D is the balancing transformation. Then this function will compute a matrix Z which satisfies

T = Z^(-1) A Z

with Z = D Q. Note that Z will not be orthogonal. For this reason, balancing is not performed by default.

Package

gsll.

Source

nonsymmetric.lisp.

Function: elliptic-integral-d (phi k &optional mode)

The incomplete elliptic integral D(phi,k) which is defined through the Carlson form RD(x,y,z) by the relation D(phi,k) = 1/3 (sin phi)^3 RD (1-sin^2(phi), 1-k^2 sin^2(phi), 1).

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-e (phi k &optional mode)

The incomplete elliptic integral of the second kind, E(phi,k). Note that Abramowitz & Stegun define this function in terms of the parameter m = k^2.

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-e-complete (k &optional mode)

The complete elliptic integral of the second kind, E(k).
Note that Abramowitz & Stegun define this function in terms of the parameter m = k^2.

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-f (phi k &optional mode)

The incomplete elliptic integral of the first kind, F(phi,k). Note that Abramowitz & Stegun define this function in terms of the parameter m = k^2.

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-k-complete (k &optional mode)

The complete elliptic integral of the first kind, K(k). Note that Abramowitz & Stegun define this function in terms of the parameter m = k^2.

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-p (phi k n &optional mode)

The incomplete elliptic integral of the third kind, P(phi,k,n). Note that Abramowitz & Stegun define this function in terms of the parameters m = k^2 and sin^2(alpha) = k^2, with the change of sign n to -n.

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-rc (x y &optional mode)

The incomplete elliptic integral RC(x,y).

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-rd (x y z &optional mode)

The incomplete elliptic integral RD(x,y,z).

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-rf (x y z &optional mode)

The incomplete elliptic integral RF(x,y,z).

Package

gsll.

Source

elliptic-integrals.lisp.

Function: elliptic-integral-rj (x y z p &optional mode)

The incomplete elliptic integral RJ(x,y,z,p).

Package

gsll.

Source

elliptic-integrals.lisp.

Function: erf (x)

The error function erf(x), where
erf(x) = (2/sqrt(pi)) int_0^x dt exp(-t^2).

Package

gsll.

Source

error-functions.lisp.

Function: erf-q (x)

The upper tail of the Gaussian probability function Q(x) = (1/sqrt{2pi}) int_x^infty dt exp(-t^2/2)}.

Package

gsll.

Source

error-functions.lisp.

Function: erf-z (x)

The Gaussian probability density function Z(x) = (1/sqrt{2pi}) exp(-x^2/2)}.

Package

gsll.

Source

error-functions.lisp.

Function: erfc (x)

The complementary error function
erfc(x) = 1 - erf(x) = (2/sqrt(pi)) int_x^infty exp(-t^2).

Package

gsll.

Source

error-functions.lisp.

Function: eta (s)

The eta function eta(s) for arbitrary s.

Package

gsll.

Source

zeta.lisp.

Function: evaluate-chebyshev-error (chebyshev x &optional order)

Evaluate the Chebyshev series at a point x, returning result and an estimate of its absolute error. If order is supplied, evaluate to at most the given order.

Package

gsll.

Source

chebyshev.lisp.

Function: evaluate-with-derivatives (coefficients x &optional derivatives)

Evaluates a polynomial and its derivatives and stores the results in the array @var{res} of size @var{lenres}. The output array contains the values of @math{d^k P/d x^k} for the specified value of @var{x} starting with @math{k = 0}. The optional argument ’derivatives may be either a vector-double-float, or a non-negative integer. If the former, the function value and derivatives are put in the vector supplied; if the latter, a new vector-double-float is created with the specified length.

Package

gsll.

Source

polynomial.lisp.

Function: examples (&optional name)

If no argument is supplied, list the names of the example categories. If a category name is given as the argument, give the list of examples in that category.

Package

gsll.

Source

generate-examples.lisp.

Function: exp-1 (x)

exp(x)-1, computed in a way that is accurate for small x.

Package

gsll.

Source

mathematical.lisp.

Function: exp-err (x dx)

Exponentiate x with an associated absolute error dx.

Package

gsll.

Source

exponential-functions.lisp.

Function: exp-err-scaled (x dx)

Exponentiate x with an associated absolute error dx and with extended numeric range.

Package

gsll.

Source

exponential-functions.lisp.

Function: exp-mult (x y)

Exponentiate x and multiply by the factor y to return the product y exp(x).

Package

gsll.

Source

exponential-functions.lisp.

Function: exp-mult-err (x dx y dy)

The product y exp(x) for the quantities x, y with associated absolute errors dx, dy.

Package

gsll.

Source

exponential-functions.lisp.

Function: exp-mult-err-scaled (x dx y dy)

The product y exp(x) for the quantities x, y with associated absolute errors dx, dy and with extended numeric range.

Package

gsll.

Source

exponential-functions.lisp.

Function: exp-mult-scaled (x y)

The product y exp(x) with extended numeric range.

Package

gsll.

Source

exponential-functions.lisp.

Function: exp-scaled (x)

The exponential function scaled. This function may be useful if the value of exp(x) would overflow the numeric range of double.

Package

gsll.

Source

exponential-functions.lisp.

Function: expm1 (x)

exp(x)-1 using an algorithm that is accurate for small x.

Package

gsll.

Source

exponential-functions.lisp.

Function: exponential-integral-3 (x)

The third-order exponential integral Ei_3(x) = int_0^xdt exp(-t^3) for x >= 0.

Package

gsll.

Source

exponential-integrals.lisp.

Function: exponential-integral-e1 (x)

The exponential integral
E_1(x)}, E_1(x) := Re int_1^infty dt exp(-xt)/t..

Package

gsll.

Source

exponential-integrals.lisp.

Function: exponential-integral-e2 (x)

The second-order exponential integral
E_2(x)}, E_2(x) := Re int_1^infty dt exp(-xt)/t^2.

Package

gsll.

Source

exponential-integrals.lisp.

Function: exponential-integral-ei (x)

The exponential integral Ei(x),
Ei(x) := - PVleft(int_{-x}^infty dt exp(-t)/tright).

Package

gsll.

Source

exponential-integrals.lisp.

Function: exponential-integral-en (n x)

The exponential integral E_n(x) of order n, E_n(x) := Re int_1^infty dt exp(-xt)/t^n.

Package

gsll.

Source

exponential-integrals.lisp.

Function: exponential-p (x mu)

The cumulative distribution function
P(x) for the exponential distribution with mean mu.

Package

gsll.

Source

exponential.lisp.

Function: exponential-pdf (x mu)

The probability density p(x) at x
for an exponential distribution with mean mu, using the formula given for #’sample :exponential.

Package

gsll.

Source

exponential.lisp.

Function: exponential-pinv (p mu)

The inverse cumulative distribution function
P(x) for the exponential distribution with mean mu.

Package

gsll.

Source

exponential.lisp.

Function: exponential-power-p (x a b)

The cumulative distribution function
P(x), for the exponential power distribution with parameters a and b.

Package

gsll.

Source

exponential-power.lisp.

Function: exponential-power-pdf (x a b)

The probability density p(x) at x
for an exponential power distribution with scale parameter a
and exponent b, using the formula given for #’sample :exponential-power.

Package

gsll.

Source

exponential-power.lisp.

Function: exponential-power-q (x a b)

The cumulative distribution functions Q(x) for the exponential power distribution with parameters a and b.

Package

gsll.

Source

exponential-power.lisp.

Function: exponential-q (x mu)

The cumulative distribution function
Q(x) for the exponential distribution with mean mu.

Package

gsll.

Source

exponential.lisp.

Function: exponential-qinv (q mu)

The inverse cumulative distribution function
Q(x) for the exponential distribution with mean mu.

Package

gsll.

Source

exponential.lisp.

Function: exprel (x)

(exp(x)-1)/x using an algorithm that is accurate for small x. For small x the algorithm is based on the expansion (exp(x)-1)/x = 1 + x/2 + x^2/(2*3) + x^3/(2*3*4) + ...

Package

gsll.

Source

exponential-functions.lisp.

Function: exprel-2 (x)

2(exp(x)-1-x)/x^2 using an algorithm that is accurate for small x. For small x the algorithm is based on the expansion 2(exp(x)-1-x)/x^2 = 1 + x/3 + x^2/(3*4) + x^3/(3*4*5) + ...

Package

gsll.

Source

exponential-functions.lisp.

Function: exprel-n (n x)

N-relative exponential, which is the n-th generalization of the functions #’exprel and #’exprel-2.

Package

gsll.

Source

exponential-functions.lisp.

Function: factorial (n)

The factorial n!, related to the Gamma function by n! = Gamma(n+1).

Package

gsll.

Source

gamma.lisp.

Function: fdist-p (x nu1 nu2)

The cumulative distribution functions P(x) for the fdist distribution with nu1 and nu2 degrees of freedom.

Package

gsll.

Source

fdist.lisp.

Function: fdist-pdf (x nu1 nu2)

The probability density p(x) at x
for an F-distribution with nu1 and nu2 degrees of freedom, using the formula given #’sample :fdist.

Package

gsll.

Source

fdist.lisp.

Function: fdist-pinv (p nu1 nu2)

The inverse cumulative distribution functions P(x) for the fdist distribution with nu1 and nu2 degrees of freedom.

Package

gsll.

Source

fdist.lisp.

Function: fdist-q (x nu1 nu2)

The cumulative distribution functions Q(x) for the fdist distribution with nu1 and nu2 degrees of freedom.

Package

gsll.

Source

fdist.lisp.

Function: fdist-qinv (q nu1 nu2)

The inverse cumulative distribution functions Q(x) for the fdist distribution with nu1 and nu2 degrees of freedom.

Package

gsll.

Source

fdist.lisp.

Function: fermi-dirac-0 (x)

The complete Fermi-Dirac integral with an index of 0. This integral is given by F_0(x) = ln(1 + e^x).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-1 (x)

The complete Fermi-Dirac integral with an index of 1, F_1(x) = int_0^infty dt (t /(exp(t-x)+1)).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-1/2 (x)

The complete Fermi-Dirac integral F_{1/2}(x).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-2 (x)

The complete Fermi-Dirac integral with an index of 2, F_2(x) = (1/2) int_0^infty dt (t^2 /(exp(t-x)+1)).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-3/2 (x)

The complete Fermi-Dirac integral F_{3/2}(x).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-inc-0 (x b)

The incomplete Fermi-Dirac integral with an index of zero, F_0(x,b) = ln(1 + e^{b-x}) - (b-x).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-integral (j x)

The complete Fermi-Dirac integral with an integer index of j, F_j(x) = (1/Gamma(j+1)) int_0^infty dt (t^j /(exp(t-x)+1)).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-m1 (x)

The complete Fermi-Dirac integral with an index of -1. This integral is given by F_{-1}(x) = e^x / (1 + e^x).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fermi-dirac-m1/2 (x)

The complete Fermi-Dirac integral F_{-1/2}(x).

Package

gsll.

Source

fermi-dirac.lisp.

Function: fft-frequency-vector (element-type size &key sample-spacing shifted)

Make and return a vector that contains the sample frequencies of an FFT that has been applied to a vector with the given size and :sample-spacing.
If :shifted is T, then the vector will contain the sample frequencies after FFT-SHIFT has been applied to the result of an FFT.

Package

gsll.

Source

extras.lisp.

Function: fft-inverse-shift (vector &key stride)

Return a copy of a vector where the zero and positive frequency components are shifted to the beginning, i.e. ordered so that it is suitable for an inverse FFT.

Package

gsll.

Source

extras.lisp.

Function: fft-shift (vector &key stride)

Return a copy of a vector that is the result of an FFT, with the zero and positive frequencies shifted to the center and end, so that the data is suitable for e.g. plotting.

Package

gsll.

Source

extras.lisp.

Function: finitep (x)

Return T if x is finite.

Package

gsll.

Source

mathematical.lisp.

Function: fit-gradient (jacobian function-values gradient)

Compute the gradient of Phi(x) = (1/2) ||F(x)||^2 from the Jacobian matrix and the function values using the formula g = J^T f.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: fit-test-delta (solver absolute-error relative-error)

Test for the convergence of the sequence by comparing the
last step with the absolute error and relative
error to the current position. The test returns T
if |last-step_i| < absolute-error + relative-error |current-position_i| for each component i of current-position and returns NIL otherwise.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: fit-test-gradient (gradient absolute-error)

Test the residual gradient against the absolute
error bound. Mathematically, the gradient should be
exactly zero at the minimum. The test returns T if the
following condition is achieved: sum_i |gradient_i| < absolute-error and returns NIL otherwise. This criterion is suitable
for situations where the precise location of the minimum
is unimportant provided a value can be found where the gradient is small enough.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: flat-p (x a b)

The cumulative distribution functions
P(x) for a uniform distribution from a to b.

Package

gsll.

Source

flat.lisp.

Function: flat-pdf (x a b)

The probability density p(x) at x
for a uniform distribution from a to b, using the formula given for #’sample :flat.

Package

gsll.

Source

flat.lisp.

Function: flat-pinv (p a b)

The inverse cumulative distribution functions P(x) for a uniform distribution from a to b.

Package

gsll.

Source

flat.lisp.

Function: flat-q (x a b)

The cumulative distribution functions
Q(x) for a uniform distribution from a to b.

Package

gsll.

Source

flat.lisp.

Function: flat-qinv (q a b)

The inverse cumulative distribution functions Q(x) for a uniform distribution from a to b.

Package

gsll.

Source

flat.lisp.

Function: float-as-integer (float &optional ieee754)

The sequence integer corresponding to the float
which satisfies three properties:
1) For two floats (< a b), then
(< (float-as-integer a) (float-as-integer b)). 2) If two floats (< a b) are adjacent, then
(= (1+ (float-as-integer a)) (float-as-integer b)). 3) (zerop (float-as-integer 0.0))
The absolute value of the integer is the integer of the IEEE754 representation without the sign bit, and the sign of the integer agrees with the sign of the float. To get the IEEE754 integer, specify ’single-float or ’double-float to ieee754.

Package

gsll.

Source

floating-point.lisp.

Function: fminimizer-f-lower (minimizer)

The value of the function at the current estimate of the lower bound for the minimizer.

Package

gsll.

Source

minimization-one.lisp.

Function: fminimizer-f-upper (minimizer)

The value of the function at the current estimate of the upper bound for the minimizer.

Package

gsll.

Source

minimization-one.lisp.

Function: fminimizer-x-lower (minimizer)

The current lower bound of the interval for the minimizer.

Package

gsll.

Source

minimization-one.lisp.

Function: fminimizer-x-upper (minimizer)

The current upper bound of the interval for the minimizer.

Package

gsll.

Source

minimization-one.lisp.

Function: format-ieee754-bits (float &optional stream)

Format as binary each of the three pieces that make the IEEE 754 floating point representation for a float.

Package

gsll.

Source

floating-point.lisp.

Function: forward-derivative (function x step)

Compute the numerical derivative of the function
at the point x using an adaptive forward difference algorithm with a step-size of step. The function is evaluated only at points greater than x and never at x itself. The derivative is returned in result and an estimate of its absolute error is returned as the second value. This function should be used if f(x) has a discontinuity at x, or is undefined for values less than x.

The initial value of step is used to estimate an optimal step-size, based on the scaling of the truncation error and round-off error in the derivative calculation. The derivative at x is computed
using an “open” 4-point rule for equally spaced abscissae at x+step/4, x+step/2, x+3step/4, x+step,
with an error estimate taken from the difference between the 4-point rule and the corresponding 2-point rule x+step/2,
x+step.

Package

gsll.

Source

numerical-differentiation.lisp.

Function: forward-fourier-transform (vector &rest args &key half-complex decimation-in-frequency stride non-radix-2 &allow-other-keys)

Perform a forward fast Fourier transform on the given vector. If the length of the vector is not a power of 2, and the user has a suitable wavetable and/or workspace, these can be supplied as keyword arguments. If the (real) vector is in half-complex form, then the key argument :half-complex should be non-NIL. If the length of the vector is a power of 2, use of a non-radix-2 transform can be forced.

Package

gsll.

Source

forward.lisp.

Function: fourier-transform (vector direction &rest args &key decimation-in-frequency stride &allow-other-keys)

Perform a fast Fourier transform on the given vector in the selected direction. The direction argument is one of :backward or :forward.

Package

gsll.

Source

select-direction.lisp.

Function: fsolver-lower (solver)

The lower end of the current bracketing interval for the solver.

Package

gsll.

Source

roots-one.lisp.

Function: fsolver-upper (solver)

The upper end of the current bracketing interval for the solver.

Package

gsll.

Source

roots-one.lisp.

Function: gamma (x)

The Gamma function Gamma(x), subject to x
not being a negative integer. The function is computed using the real Lanczos method. The maximum value of x such that
Gamma(x) is not considered an overflow is given by +gamma-xmax+.

Package

gsll.

Source

gamma.lisp.

Function: gamma* (x)

The regulated Gamma Function Gamma^*(x)
for x > 0, given by
Gamma^*(x) = Gamma(x)/(sqrt{2pi} x^{(x-1/2)} exp(-x)) = (1 + {1 over 12x} + ...)
for x to infinity.

Package

gsll.

Source

gamma.lisp.

Function: gamma-p (x a b)

The cumulative distribution functions
P(x) for the Gamma distribution with parameters a and b.

Package

gsll.

Source

gamma.lisp.

Function: gamma-pdf (x a b)

The probability density p(x) at x
for a gamma distribution with parameters a and b, using the formula given in #’sample :gamma.

Package

gsll.

Source

gamma.lisp.

Function: gamma-pinv (p a b)

The inverse cumulative distribution functions
P(x) for the Gamma distribution with parameters a and b.

Package

gsll.

Source

gamma.lisp.

Function: gamma-q (x a b)

The cumulative distribution functions
Q(x) for the Gamma distribution with parameters a and b.

Package

gsll.

Source

gamma.lisp.

Function: gamma-qinv (q a b)

The inverse cumulative distribution functions
Q(x) for the Gamma distribution with parameters a and b.

Package

gsll.

Source

gamma.lisp.

Function: gaussian-p (x sigma)

The cumulative distribution function P(x) for the Gaussian distribution with standard deviation sigma.

Package

gsll.

Source

gaussian.lisp.

Function: gaussian-pdf (x sigma)

Compute the probability density p(x) at x
for a Gaussian distribution with standard deviation sigma.

Package

gsll.

Source

gaussian.lisp.

Function: gaussian-pinv (p sigma)

The inverse cumulative distribution function P(x) for the Gaussian distribution with standard deviation sigma.

Package

gsll.

Source

gaussian.lisp.

Function: gaussian-q (x sigma)

The cumulative distribution function Q(x) for the Gaussian distribution with standard deviation sigma.

Package

gsll.

Source

gaussian.lisp.

Function: gaussian-qinv (q sigma)

The inverse cumulative distribution function Q(x) for the Gaussian distribution with standard deviation sigma.

Package

gsll.

Source

gaussian.lisp.

Function: gaussian-tail-pdf (x a sigma)

The probability density p(x) at x
for a Gaussian tail distribution with standard deviation sigma and lower limit a, using the formula given for gaussian-tail.

Package

gsll.

Source

gaussian-tail.lisp.

Function: gegenbauer (n lambda x)

The Gegenbauer polynomial C^{(lambda)}_n(x)} for a specific value of n, lambda, x subject to lambda > -1/2, n >= 0.

Package

gsll.

Source

gegenbauer.lisp.

Function: gegenbauer-1 (lambda x)

The Gegenbauer polynomial C^{(lambda)}_1(x)}.

Package

gsll.

Source

gegenbauer.lisp.

Function: gegenbauer-2 (lambda x)

The Gegenbauer polynomial C^{(lambda)}_2(x)}.

Package

gsll.

Source

gegenbauer.lisp.

Function: gegenbauer-3 (lambda x)

The Gegenbauer polynomial C^{(lambda)}_3(x)}.

Package

gsll.

Source

gegenbauer.lisp.

Function: gegenbauer-array (lambda x &optional size-or-array)

Compute an array of Gegenbauer polynomials C^{(lambda)}_n(X)} for n = 0, 1, 2, ..., length(array)-1}, subject to lambda > -1/2.

Package

gsll.

Source

gegenbauer.lisp.

Function: geometric-p (k p)

The cumulative distribution functions
P(k) for the geometric distribution with parameter p.

Package

gsll.

Source

geometric.lisp.

Function: geometric-pdf (k p)

The probability p(k) of obtaining k
from a geometric distribution with probability parameter p, using the formula given in #’sample :geometric.

Package

gsll.

Source

geometric.lisp.

Function: geometric-q (k p)

The cumulative distribution functions
Q(k) for the geometric distribution with parameters p.

Package

gsll.

Source

geometric.lisp.

Function: get-random-number (generator)

Generate a random integer. The
minimum and maximum values depend on the algorithm used, but all integers in the range [min, max] are equally likely. The values of min and max can determined using the auxiliary functions #’rng-max and #’rng-min.

Package

gsll.

Source

generators.lisp.

Function: greville-abscissa (i bspline)

Returns the location of the @math{i}-th Greville abscissa for the given B-spline basis. For the ill-defined case when @math{k=1}, the implementation chooses to return breakpoint interval midpoints.

Package

gsll.

Source

basis-splines.lisp.

Function: gsl-asinh (x)

Arc hyperbolic sine.

Package

gsll.

Source

mathematical.lisp.

Function: gsl-atanh (x)

Arc hyperbolic tangent.

Package

gsll.

Source

mathematical.lisp.

Function: gsl-exp (x)

The exponential function.

Package

gsll.

Source

exponential-functions.lisp.

Function: gsl-lookup (string)

Find the GSLL (Lisp) equivalent of the GSL symbol.

Package

gsll.

Source

interface.lisp.

Function: gsl-random-state (rng-instance)

The complete state of a given random number generator, specified as a vector of bytes.

Package

gsll.

Source

generators.lisp.

Function: gumbel1-p (x a b)

The cumulative distribution functions
P(x) for the Type-1 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel1.lisp.

Function: gumbel1-pdf (x a b)

The probability density p(x) at x
for a Type-1 Gumbel distribution with parameters a and b, using the formula given for #’sample :gumbel1.

Package

gsll.

Source

gumbel1.lisp.

Function: gumbel1-pinv (p a b)

The inverse cumulative distribution functions P(x) for the Type-1 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel1.lisp.

Function: gumbel1-q (x a b)

The cumulative distribution functions
Q(x) for the Type-1 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel1.lisp.

Function: gumbel1-qinv (q a b)

The inverse cumulative distribution functions Q(x) for the Type-1 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel1.lisp.

Function: gumbel2-p (x a b)

The cumulative distribution functions
P(x) for the Type-2 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel2.lisp.

Function: gumbel2-pdf (x a b)

The probability density p(x) at x
for a Type-2 Gumbel distribution with parameters a and b, using the formula given in #’sample :gumbel2.

Package

gsll.

Source

gumbel2.lisp.

Function: gumbel2-pinv (p a b)

The inverse cumulative distribution functions P(x) for the Type-2 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel2.lisp.

Function: gumbel2-q (x a b)

The cumulative distribution functions
Q(x) for the Type-2 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel2.lisp.

Function: gumbel2-qinv (q a b)

The inverse cumulative distribution functions Q(x) for the Type-2 Gumbel distribution with parameters a and b.

Package

gsll.

Source

gumbel2.lisp.

Function: hazard (x)

The hazard function for the normal distribution.

Package

gsll.

Source

error-functions.lisp.

Function: heapsort (array count size function)

Sort the count elements of the array of size specified
into ascending order using the comparison
function. The type of the comparison function is defined by,
A comparison function should return a negative integer if the first argument is less than the second argument, zero if the two arguments are equal and a positive integer if the first argument is greater than the second argument.

Package

gsll.

Source

sorting.lisp.

Function: heapsort-index (p array count size function)

Indirectly sort the count elements of the array
array, each of size given, into ascending order using the
comparison function. The resulting permutation is stored
in p, an array of length n. The elements of p give the
index of the array element which would have been stored in that position if the array had been sorted in place. The first element of p
gives the index of the least element in array, and the last
element of p gives the index of the greatest element in
array. The array itself is not changed.

Package

gsll.

Source

sorting.lisp.

Function: histogram-covariance (histogram-2d)

The covariance of the histogrammed x and y variables, where the histogram is regarded as a probability
distribution. Negative bin values are ignored for the purposes of this calculation.

Package

gsll.

Source

statistics.lisp.

Function: histogram-find (histogram x-value &optional y-value)

Finds the bin number which covers the coordinate value in
the histogram. The bin is located using a binary search. The search includes an optimization for histograms with uniform range, and will return the correct bin immediately in this case. If the value is found in the range of the histogram then the function returns the index. If value lies outside the valid range of the histogram then the error input-domain is signalled.

Package

gsll.

Source

updating-accessing.lisp.

Function: householder-hm (tau v a)

Apply the Householder matrix P defined by the
scalar tau and the vector v to the left-hand side of the matrix A. On output the result P A is stored in A.

Package

gsll.

Source

householder.lisp.

Function: householder-hv (tau v w)

Apply the Householder transformation P defined by the scalar tau and the vector v to the vector w. On output the result P w is stored in w.

Package

gsll.

Source

householder.lisp.

Function: householder-mh (tau v a)

Apply the Householder matrix P defined by the
scalar tau and the vector v to the right-hand side of the matrix A. On output the result A P is stored in A.

Package

gsll.

Source

householder.lisp.

Function: householder-solve (a b &optional x-spec)

Solve the system A x = b directly using Householder
transformations. If x-spec is NIL (default), the solution will
replace b. If x-spec is T, then an array will be created and the
solution returned in it. If x-spec is a grid:foreign-array, the solution will be returned in it. If x-spec is non-NIL, on output the solution is
stored in x and b is not modified. The matrix A is destroyed by
the Householder transformations. The solution is returned from the function call.

Package

gsll.

Source

householder.lisp.

Function: householder-transform (v)

Prepare a Householder transformation P = I - tau v v^T
which can be used to zero all the elements of the input vector except the first. Returned values are the transformation, which is stored in the vector v, and the scalar tau.

Package

gsll.

Source

householder.lisp.

Function: hurwitz-zeta (s q)

The Hurwitz zeta function zeta(s,q) for s > 1, q > 0.

Package

gsll.

Source

zeta.lisp.

Function: hydrogenicr (n l x r)

The n-th normalized hydrogenic bound state radial wavefunction,
R_n := {2 Z^{3/2} over n^2} left({2Z over n}right)^l
sqrt{(n-l-1)! over (n+l)!} exp(-Z r/n) L^{2l+1}_{n-l-1}(2Z/n r). The normalization is chosen such that the wavefunction psi is given by psi(n,l,r) = R_n Y_{lm}.

Package

gsll.

Source

coulomb.lisp.

Function: hydrogenicr-1 (x r)

The lowest-order normalized hydrogenic bound state radial wavefunction R_1 := 2Z sqrt{Z} exp(-Z r).

Package

gsll.

Source

coulomb.lisp.

Function: hypergeometric-0f1 (c x)

The hypergeometric function 0F1(c,x).

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-2f0 (a b x)

The hypergeometric function
2F0(a,b,x). The series representation
is a divergent hypergeometric series. However, for x < 0 we have 2F0(a,b,x) = (-1/x)^a U(a,1+a-b,-1/x)

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-2f1 (a b c x)

The Gauss hypergeometric function
2F1(a,b,c,x) for |x| < 1. If the arguments
(a,b,c,x) are too close to a singularity then the function can signal the error ’exceeded-maximum-iterations when the series approximation converges too slowly. This occurs in the region of x=1, c - a - b = m for integer m.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-2f1-conj (a c x)

The Gauss hypergeometric function 2F1(a, a*, c, x) with complex parameters for |x| < 1.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-2f1-conj-renorm (a c x)

The renormalized Gauss hypergeometric function 2F1(a, a*, c, x) / Gamma(c) for |x| < 1.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-2f1-renorm (a b c x)

The renormalized Gauss hypergeometric function 2F1(a,b,c,x) / Gamma(c) for |x| < 1.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-p (k n1 n2 tt)

The cumulative distribution functions P(k) for the hypergeometric distribution with parameters n1, n2 and tt.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-pdf (k n1 n2 tt)

The probability p(k) of obtaining k
from a hypergeometric distribution with parameters n1, n2, tt, using the formula given in #’sample :hypergeometric.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypergeometric-q (k n1 n2 tt)

The cumulative distribution functions Q(k) for the hypergeometric distribution with parameters n1, n2, and tt.

Package

gsll.

Source

hypergeometric.lisp.

Function: hypotenuse (x y)

The hypotenuse function sqrt{x^2 + y^2}.

Package

gsll.

Source

trigonometry.lisp.

Function: hypotenuse* (x y)

The hypotenuse sqrt{x^2 + y^2} computed in a way that avoids overflow.

Package

gsll.

Source

mathematical.lisp.

Function: incomplete-beta (a b x)

The normalized incomplete Beta function B_x(a,b)/B(a,b) where
B_x(a,b) = int_0^x t^{a-1} (1-t)^{b-1} dt for a > 0, b > 0, and 0 <= x <= 1.

Package

gsll.

Source

gamma.lisp.

Function: incomplete-gamma (a x)

The normalized incomplete Gamma Function
Q(a,x) = 1/Gamma(a) int_x^infty dt t^{a-1} exp(-t) for a > 0, x >= 0.

Package

gsll.

Source

gamma.lisp.

Function: infinityp (x)

Return +1 if x is positive infinity, -1 if negative infinity
nil if finite. Some platforms will return only +1 for either sign.

Package

gsll.

Source

mathematical.lisp.

Function: init-first (combination)

Initialize the combination c to the lexicographically first combination, i.e. (0,1,2,...,k-1).

Package

gsll.

Source

combination.lisp.

Function: init-last (combination)

Initialize the combination c to the lexicographically last combination, i.e. (n-k,n-k+1,...,n-1).

Package

gsll.

Source

combination.lisp.

Function: integer-as-float (integer float-type)

Construct the floating point number from its integer representation, either sequence or IEEE754.
Also return the number in rational form.
The integer may be either a signed integer produced by float-as-integer, or an IEEE754 integer. Acceptable float-type is either ’double-float or ’single-float.

Package

gsll.

Source

floating-point.lisp.

Function: integral-chebyshev (integral chebyshev)

Compute the integral of the Chebyshev series, storing
the integral coefficients in the previously allocated series. The two series must have been allocated with the same order. The lower limit of the integration is taken to be the left hand end of the range lower-limit.

Package

gsll.

Source

chebyshev.lisp.

Function: integration-qag (function a b method &optional absolute-error relative-error limit workspace)

Apply an integration rule adaptively until an estimate
of the integral of f over (a,b) is achieved within the
desired absolute and relative error limits, absolute-error and relative-error. The function returns the final approximation,
and an estimate of the absolute error. The integration rule
is determined by the value of method, which should
be chosen from the following symbolic names,
:gauss15 :gauss21 :gauss31 :gauss41 :gauss51 :gauss61
corresponding to the 15, 21, 31, 41, 51 and 61 point Gauss-Kronrod rules. The higher-order rules give better accuracy for smooth functions, while lower-order rules save time when the function contains local difficulties, such as discontinuities.
On each iteration the adaptive integration strategy bisects the interval with the largest error estimate. The subintervals and their results are stored in the memory provided by workspace. The maximum number of subintervals is given by ’limit, which may not exceed the allocated size of the workspace.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qagi (function &optional absolute-error relative-error limit workspace)

Compute the integral of the function f over the
infinite interval (-infty,+infty). The integral is mapped onto the semi-open interval (0,1] using the transformation x = (1-t)/t, int_{-infty}^{+infty} dx , f(x)
= int_0^1 dt , (f((1-t)/t) + f(-(1-t)/t))/t^2.
It is then integrated using the QAGS algorithm. The normal 21-point Gauss-Kronrod rule of QAGS is replaced by a 15-point rule, because the transformation can generate an integrable singularity at the origin. In this case a lower-order rule is more efficient.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qagil (function b &optional absolute-error relative-error limit workspace)

Compute the integral of the function f over the
semi-infinite interval (-infty,b). The integral is mapped onto the semi-open interval (0,1] using the transformation x = b - (1-t)/t, int_{-infty}^{b} dx, f(x) = int_0^1 dt, f(b - (1-t)/t)/t^2
and then integrated using the QAGS algorithm.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qagiu (function a &optional absolute-error relative-error limit workspace)

Compute the integral of the function f over the
semi-infinite interval (a,+infty). The integral is mapped onto the semi-open interval (0,1] using the transformation x = a + (1-t)/t, int_{a}^{+infty} dx, f(x) = int_0^1 dt f(a + (1-t)/t)/t^2
and then integrated using the QAGS algorithm.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qagp (function points &optional absolute-error relative-error limit workspace)

Apply the adaptive integration algorithm QAGS taking
account of the user-supplied locations of singular points. The array points should contain the endpoints of the
integration ranges defined by the integration region and locations of the singularities. For example, to integrate over the region (a,b) with break-points at x_1, x_2, x_3 (where
a < x_1 < x_2 < x_3 < b) then an array with
(setf (data array) #(a x_1 x_2 x_3 b)) should be used.
If you know the locations of the singular points in the integration region then this routine will be faster than #’integration-QAGS.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qags (function a b &optional absolute-error relative-error limit workspace)

Apply the Gauss-Kronrod 21-point integration rule
adaptively until an estimate of the integral of f over
(a,b) is achieved within the desired absolute and relative error limits, absolute-error and relative-error. The results are extrapolated using the epsilon-algorithm, which accelerates the convergence of the integral in the presence of discontinuities and integrable singularities. The function returns the final approximation from the extrapolation, and an estimate of the absolute error. The subintervals and their results are stored in the
memory provided by workspace. The maximum number of subintervals
is given by limit, which may not exceed the allocated size of the workspace.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qawc (function a b c &optional absolute-error relative-error limit workspace)

Compute the Cauchy principal value of the integral of
f over (a,b), with a singularity at c,
I = int_a^b dx, {f(x)/x - c} = lim_{epsilon -> 0}
{int_a^{c-epsilon} dx, {f(x)/x - c} + int_{c+epsilon}^b dx,
{f(x) over x - c}}
The adaptive bisection algorithm of QAG is used, with modifications to ensure that subdivisions do not occur at the singular point x = c.
When a subinterval contains the point x = c or is close to
it then a special 25-point modified Clenshaw-Curtis rule is used to control the singularity. Further away from the singularity the algorithm
uses an ordinary 15-point Gauss-Kronrod integration rule.

Package

gsll.

Source

numerical-integration.lisp.

Function: integration-qawf (function a omega l trig n &optional absolute-error table limit workspace cycle-workspace)

This function attempts to compute a Fourier integral of the function f over the semi-infinite interval [a,+infty).

I = int_a^{+infty} dx f(x) sin(omega x)
I = int_a^{+infty} dx f(x) cos(omega x)

The parameter omega and choice of sin or cos is taken from the table wf (the length L can take any value, since it is overridden by this function to a value appropriate for the fourier integration). The integral is computed using the QAWO algorithm over each of the subintervals,

C_1 = [a, a + c]
C_2 = [a + c, a + 2 c]
... = ...
C_k = [a + (k-1) c, a + k c]

where c = (2 floor(|omega|) + 1) pi/|omega|. The width c is chosen to cover an odd number of periods so that the contributions from the intervals alternate in sign and are monotonically decreasing when f is positive and monotonically decreasing. The sum of this sequence of contributions is accelerated using the epsilon-algorithm.

This function works to an overall absolute tolerance of abserr. The following strategy is used: on each interval C_k the algorithm tries to achieve the tolerance

TOL_k = u_k abserr

where u_k = (1 - p)p^{k-1} and p = 9/10. The sum of the geometric series of contributions from each interval gives an overall tolerance of abserr.

If the integration of a subinterval leads to difficulties then the accuracy requirement for subsequent intervals is relaxed,

TOL_k = u_k max(abserr, max_{i<k}{E_i})

where E_k is the estimated error on the interval C_k.

The subintervals and their results are stored in the memory provided by workspace. The maximum number of subintervals is given by limit, which may not exceed the allocated size of the workspace. The integration over each subinterval uses the memory provided by cycle_workspace as workspace for the QAWO algorithm.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: integration-qawo (function a omega l trig n &optional absolute-error relative-error table limit workspace)

Use an adaptive algorithm to compute the integral of f over (a,b) with the weight function sin(omega x) or cos(omega x) defined by the table wf,
I = int_a^b dx f(x) sin(omega x)
I = int_a^b dx f(x) cos(omega x)

The results are extrapolated using the epsilon-algorithm to accelerate the convergence of the integral. The function returns the final approximation from the extrapolation, result, and an estimate of the absolute error, abserr. The subintervals and their results are stored in the memory provided by workspace. The maximum number of subintervals is given by limit, which may not exceed the allocated size of the workspace.

Those subintervals with large widths d where domega > 4 are computed using a 25-point Clenshaw-Curtis integration rule, which handles the oscillatory behavior. Subintervals with a small widths where domega < 4 are computed using a 15-point Gauss-Kronrod integration.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: integration-qaws (function a b alpha beta mu nu &optional absolute-error relative-error table limit workspace)

Compute the integral of the function f(x) over the interval (a,b) with the singular weight function (x-a)^alpha (b-x)^beta
log^mu (x-a) log^nu (b-x). The parameters of the weight
function (alpha, beta, mu, nu) are used to make the default table. The integral is
I = int_a^b dx f(x) (x-a)^alpha (b-x)^beta log^mu (x-a) log^nu (b-x). The adaptive bisection algorithm of QAG is used. When a
subinterval contains one of the endpoints then a special 25-point modified Clenshaw-Curtis rule is used to control the
singularities. For subintervals which do not include the endpoints an ordinary 15-point Gauss-Kronrod integration rule is used.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: integration-qng (function a b &optional absolute-error relative-error)

Apply the Gauss-Kronrod 10-point, 21-point, 43-point and
87-point integration rules in succession until an estimate of the integral of f over (a,b) is achieved within the desired
absolute and relative error limits, absolute-error and relative-error. The function returns the final approximation, an estimate of
the absolute error, and the number of function evaluations
used. The Gauss-Kronrod rules are designed in such a way
that each rule uses all the results of its predecessors, in order to minimize the total number of function evaluations.

Package

gsll.

Source

numerical-integration.lisp.

Function: interpolation-search (x-array x low-index high-index)

Find the index i of the array x-array such
that x-array[i] <= x < x-array[i+1]. The index is searched for in the range [low-index, high-index].

Package

gsll.

Source

lookup.lisp.

Function: inverse-fourier-transform (vector &rest args &key decimation-in-frequency stride non-radix-2 &allow-other-keys)

Perform a inverse fast Fourier transform on the given vector. If the length of the vector is not a power of 2, and the user has a suitable wavetable and/or workspace, these can be supplied as keyword arguments. If the vector is real, it is assumed to be in half-complex form. If the length of the vector is a power of 2, use of a non-radix-2 transform can be forced.

Package

gsll.

Source

inverse.lisp.

Function: inversions (p)

Count the number of inversions in the permutation
p. An inversion is any pair of elements that are not in order.
For example, the permutation 2031 has three inversions, corresponding to the pairs (2,0) (2,1) and (3,1). The identity permutation has no inversions.

Package

gsll.

Source

permutation.lisp.

Function: jacobian (solver &optional matrix)

The Jacobian matrix for the current iteration of the solver.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: jacobian-elliptic-functions (u m)

The Jacobian elliptic functions sn(u|m),
cn(u|m), dn(u|m) computed by descending Landen transformations.

Package

gsll.

Source

elliptic-functions.lisp.

Function: knots (breakpoints workspace)

Compute the knots associated with the given breakpoints and store them in the workspace.

Package

gsll.

Source

basis-splines.lisp.

Function: laguerre (n a x)

The generalized Laguerre polynomials L^a_n(x) for a > -1, n >= 0.

Package

gsll.

Source

laguerre.lisp.

Function: laguerre-1 (a x)

The generalized Laguerre polynomial L^a_1(x) using explicit representations.

Package

gsll.

Source

laguerre.lisp.

Function: laguerre-2 (a x)

The generalized Laguerre polynomial L^a_2(x) using explicit representations.

Package

gsll.

Source

laguerre.lisp.

Function: laguerre-3 (a x)

The generalized Laguerre polynomial L^a_3(x) using explicit representations.

Package

gsll.

Source

laguerre.lisp.

Function: lambert-w0 (x)

The principal branch of the Lambert W function, W_0(x).

Package

gsll.

Source

lambert.lisp.

Function: lambert-wm1 (x)

The secondary real-valued branch of the Lambert W function, W_{-1}(x).

Package

gsll.

Source

lambert.lisp.

Function: landau-pdf (x)

The probability density p(x) at x
for the Landau distribution using an approximation to the formula given in #’sample :landau.

Package

gsll.

Source

landau.lisp.

Function: laplace-p (x a)

The cumulative distribution function
P(x) for the laplace distribution with width a.

Package

gsll.

Source

laplace.lisp.

Function: laplace-pdf (x a)

The probability density p(x) at x
for a Laplace distribution with width a, using the formula given for #’sample :laplace.

Package

gsll.

Source

laplace.lisp.

Function: laplace-pinv (p a)

The inverse cumulative distribution function P(x) for the laplace distribution with width a.

Package

gsll.

Source

laplace.lisp.

Function: laplace-q (x a)

The cumulative distribution function
Q(x) for the laplace distribution with width a.

Package

gsll.

Source

laplace.lisp.

Function: laplace-qinv (q a)

The inverse cumulative distribution function Q(x) for the laplace distribution with width a.

Package

gsll.

Source

laplace.lisp.

Function: legendre-conicalp-0 (lambda x)

The conical function P^0_{-1/2 + i lambda(x)} for x > -1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-conicalp-1 (lambda x)

The conical function
P^1_{-1/2 + i lambda}(x)} for x > -1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-conicalp-half (lambda x)

The irregular Spherical Conical Function P^{1/2}_{-1/2 + i lambda}(x) for x > -1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-conicalp-mhalf (lambda x)

The regular Spherical Conical Function P^{-1/2}_{-1/2 + i lambda}(x) for x > -1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-h3d (l lambda eta)

The l-th radial eigenfunction of the
Laplacian on the 3-dimensional hyperbolic space
eta >= 0, l >= 0. In the flat limit this takes the form L^{H3d}_l(lambda,eta) = j_l(lambdaeta).

Package

gsll.

Source

legendre.lisp.

Function: legendre-h3d-0 (lambda eta)

The zeroth radial eigenfunction of the Laplacian on the 3-dimensional hyperbolic space,
L^{H3d}_0(lambda,eta) := sin(lambdaeta)/(lambdasinh(eta)) for eta >= 0. In the flat limit this takes the form L^{H3d}_0(lambda,eta) = j_0(lambdaeta).

Package

gsll.

Source

legendre.lisp.

Function: legendre-h3d-1 (lambda eta)

The first radial eigenfunction of the Laplacian on
the 3-dimensional hyperbolic space,
L^{H3d}_1(lambda,eta) := 1/sqrt{lambda^2 + 1}
sin(lambda eta)/(lambda sinh(eta)) (coth(eta) - lambda cot(lambdaeta))} for eta >= 0. In the flat limit this takes the form L^{H3d}_1(lambda,eta) = j_1(lambdaeta)}.

Package

gsll.

Source

legendre.lisp.

Function: legendre-h3d-array (lambda eta &optional size-or-array)

An array of radial eigenfunctions L^{H3d}_l(lambda, eta) for 0 <= l <= length(array).

Package

gsll.

Source

legendre.lisp.

Function: legendre-p1 (x)

The Legendre polynomials P_1(x) using an explicit representation.

Package

gsll.

Source

legendre.lisp.

Function: legendre-p2 (x)

The Legendre polynomials P_2(x) using an explicit representation.

Package

gsll.

Source

legendre.lisp.

Function: legendre-p3 (x)

The Legendre polynomials P_3(x) using an explicit representation.

Package

gsll.

Source

legendre.lisp.

Function: legendre-pl (l x)

The Legendre polynomial P_l(x) for a specific value of l, x subject to l >= 0, |x| <= 1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-pl-array (x &optional size-or-array)

Compute an array of Legendre polynomials P_l(x) for l = 0, ..., length(array), |x| <= 1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-pl-deriv-array (x &optional size-or-array)

Compute an array of Legendre polynomials derivatives dP_l(x)/dx, for l = 0, ..., length(array), |x| <= 1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-plm (l m x)

The associated Legendre polynomial P_l^m(x) for m >= 0, l >= m, |x| <= 1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-q0 (x)

The Legendre function Q_0(x) for x > -1, x /= 1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-q1 (x)

The Legendre function Q_1(x) for x > -1, x /= 1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-ql (l x)

The Legendre function Q_l(x) for x > -1, x /= 1, l >= 0.

Package

gsll.

Source

legendre.lisp.

Function: legendre-regular-cylindrical-conical (l lambda x)

The Regular Cylindrical Conical Function P^{-m}_{-1/2 + i lambda}(x) for x > -1, m >= -1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-regular-spherical-conical (l lambda x)

The Regular Spherical Conical Function P^{-1/2-l}_{-1/2 + i lambda}(x) for x > -1, l >= -1.

Package

gsll.

Source

legendre.lisp.

Function: legendre-sphplm (l m x)

The normalized associated Legendre polynomial sqrt{(2l+1)/(4pi) sqrt{(l-m)!/(l+m)!} P_l^m(x) suitable for use in spherical harmonics. The parameters must satisfy m >= 0, l >= m, |x| <= 1. These routines avoid the overflows that occur for the standard normalization of P_l^m(x).

Package

gsll.

Source

legendre.lisp.

Function: linear-cycles (p)

Count the number of cycles in the permutation p, given in linear form.

Package

gsll.

Source

permutation.lisp.

Function: linear-estimate (x c0 c1 cov00 cov01 cov11)

Use the best-fit linear regression coefficients c0, c1 and their covariance
cov00, cov01, cov11 to compute the fitted function y and its standard deviation y-error for the model Y = c_0 + c_1 X at the point x.

Package

gsll.

Source

linear-least-squares.lisp.

Function: linear-fit (x y &optional weight x-stride y-stride weight-stride)

Compute the best-fit linear regression coefficients
c0, c1 of the model Y = c_0 + c_1 X for the weighted or unweighted
dataset (x, y), two vectors of equal length with strides
x-stride and y-stride, and return as the first two values.
The vector weight if given, of the same length
and stride w-stride, specifies the weight of each datapoint. The
weight is the reciprocal of the variance for each datapoint in y.

The covariance matrix for the parameters (c0, c1) is
computed using the weights and returned via the parameters
(cov00, cov01, c0v01) as the next three values. The weighted or
unweighted sum of squares of the residuals from the best-fit line,
chi^2, is returned as the last value.

Returns: c0, c1, cov00, cov01, cov11, sumsq.
Returns: intercept, slope, intercept variance, covariance, slope variance, sum square of residuals.

Package

gsll.

Source

linear-least-squares.lisp.

Function: linear-mfit (model observations parameters-or-size &optional weight tolerance covariance workspace)

Compute the best-fit parameters c of the weighted or unweighted model y = X c for the observations y and optional weights
and the model matrix X. The covariance matrix of
the model parameters is computed with the given weights. The weighted sum of squares of the residuals from the best-fit, chi^2, is returned as the last value.

The best-fit is found by singular value decomposition of the matrix model using the preallocated workspace provided. The modified Golub-Reinsch SVD algorithm is used for the unweighted solution, with column scaling to improve the accuracy of the singular values. Any components which have zero singular value (to machine precision) are discarded from the fit.

If tolerance is a double-float, the SVD algorithm is used.
If it is nil the non-svd algorithm is used.

Package

gsll.

Source

linear-least-squares.lisp.

Function: linear-to-canonical (p &optional q)

Compute the canonical form of the permutation p and stores it in the output argument q.

Package

gsll.

Source

permutation.lisp.

Function: log+1 (x)

log(1+x), computed in a way that is accurate for small x.

Package

gsll.

Source

mathematical.lisp.

Function: log-1+x (x)

log(1 + x) for x > -1 using an algorithm that is accurate for small x.

Package

gsll.

Source

logarithm.lisp.

Function: log-1+x-m1 (x)

log(1 + x) - x for x > -1 using an algorithm that is accurate for small x.

Package

gsll.

Source

logarithm.lisp.

Function: log-abs (x)

The natural logarithm of the magnitude of x, log(|x|), for x ne 0.

Package

gsll.

Source

logarithm.lisp.

Function: log-beta (a b)

The logarithm of the Beta Function, log(B(a,b)) for a > 0, b > 0.

Package

gsll.

Source

gamma.lisp.

Function: log-choose (n m)

The logarithm of (n choose m). This is
equivalent to the sum log(n!) - log(m!) - log((n-m)!).

Package

gsll.

Source

gamma.lisp.

Function: log-cosh (x)

Logarithm of cosh function, special functions These routines compute log(cosh(x)) for any x.

Package

gsll.

Source

trigonometry.lisp.

Function: log-double-factorial (n)

Compute the logarithm of the double factorial of n, log(n!!).

Package

gsll.

Source

gamma.lisp.

Function: log-erfc (x)

The logarithm of the complementary error function log(erfc(x)).

Package

gsll.

Source

error-functions.lisp.

Function: log-factorial (n)

The logarithm of the factorial of n, log(n!).
The algorithm is faster than computing
ln(Gamma(n+1)) via #’log-gamma for n < 170, but defers for larger n.

Package

gsll.

Source

gamma.lisp.

Function: log-gamma (x)

The logarithm of the Gamma function,
log(Gamma(x)), subject to x not a being negative
integer. For x<0 the real part of log(Gamma(x)) is returned, which is equivalent to log(|Gamma(x)|). The function is computed using the real Lanczos method.

Package

gsll.

Source

gamma.lisp.

Function: log-gamma-complex (z)

Compute log(Gamma(z)) for complex z=z_r+i z_i
and z not a negative integer, using the complex Lanczos method. The returned parameters are lnr = log|Gamma(z)| and arg = arg(Gamma(z)) in (-pi,pi]. Note that the phase
part (arg) is not well-determined when |z| is very large, due to inevitable roundoff in restricting to (-pi,pi]. This will result in a :ELOSS error when it occurs. The absolute value part (lnr), however, never suffers from loss of precision.

Package

gsll.

Source

gamma.lisp.

Function: log-gamma-sign (x)

Compute the sign of the gamma function and the logarithm of
its magnitude, subject to x not being a negative integer. The function is computed using the real Lanczos method. The value of the gamma function can be reconstructed using the relation Gamma(x) = sgn * exp(resultlg)}.

Package

gsll.

Source

gamma.lisp.

Function: log-modulus (number)

The logarithm of the magnitude of the complex number.

Package

gsll.

Source

complex.lisp.

Function: log-pochammer (a x)

The logarithm of the Pochhammer symbol,
log((a)_x) = log(Gamma(a + x)/Gamma(a)) for a > 0, a+x > 0.

Package

gsll.

Source

gamma.lisp.

Function: log-pochammer-sign (a x)

The logarithm of the Pochhammer symbol and its sign.
The computed parameters are result =
log(|(a)_x|) and sgn = sgn((a)_x) where (a)_x :=
Gamma(a + x)/Gamma(a), subject to a, a+x not being negative integers.

Package

gsll.

Source

gamma.lisp.

Function: log-sin (x)

This function computes the logarithm of the complex sine, log(sin(z_r + i z_i)) storing the real and imaginary parts in szr, szi.

Package

gsll.

Source

trigonometry.lisp.

Function: log-sinh (x)

Logarithm of sinh function, special functions These routines compute log(sinh(x)) for x > 0.

Package

gsll.

Source

trigonometry.lisp.

Function: logarithmic-pdf (k p)

The probability p(k) of obtaining k
from a logarithmic distribution with probability parameter p, using the formula given in #’sample :logarithmic.

Package

gsll.

Source

logarithmic.lisp.

Function: logistic-p (x a)

The cumulative distribution functions
P(x) for the logistic distribution with scale parameter a.

Package

gsll.

Source

logistic.lisp.

Function: logistic-pdf (x a)

The probability density p(x) at x
for a logistic distribution with scale parameter a, using the formula given in #’sample :logistic.

Package

gsll.

Source

logistic.lisp.

Function: logistic-pinv (p a)

The inverse cumulative distribution functions
P(x) for the logistic distribution with scale parameter a.

Package

gsll.

Source

logistic.lisp.

Function: logistic-q (x a)

The cumulative distribution functions
Q(x) for the logistic distribution with scale parameter a.

Package

gsll.

Source

logistic.lisp.

Function: logistic-qinv (q a)

The inverse cumulative distribution functions
Q(x) for the logistic distribution with scale parameter a.

Package

gsll.

Source

logistic.lisp.

Function: lognormal-p (x zeta sigma)

The cumulative distribution functions
P(x) for the lognormal distribution with parameters zeta and sigma.

Package

gsll.

Source

lognormal.lisp.

Function: lognormal-pdf (x zeta sigma)

The probability density p(x) at X
for a lognormal distribution with parameters zeta and sigma, using the formula given in #’sample :lognormal.

Package

gsll.

Source

lognormal.lisp.

Function: lognormal-pinv (p zeta sigma)

The inverse cumulative distribution functions P(x) for the lognormal distribution with parameters zeta and sigma.

Package

gsll.

Source

lognormal.lisp.

Function: lognormal-q (x zeta sigma)

The cumulative distribution functions
Q(x) for the lognormal distribution with parameters zeta and sigma.

Package

gsll.

Source

lognormal.lisp.

Function: lognormal-qinv (q zeta sigma)

The inverse cumulative distribution functions
Q(x) for the lognormal distribution with parameters zeta and sigma.

Package

gsll.

Source

lognormal.lisp.

Function: ls-covariance (solver relative-error &optional covariance jacobian)

Compute the covariance matrix of the best-fit parameters
using the Jacobian matrix J. The relative error
is used to remove linear-dependent columns when J is
rank deficient. The covariance matrix is given by
C = (J^T J)^{-1}
and is computed by QR decomposition of J with column-pivoting. Any columns of R which satisfy |R_{kk}| <= relative-error |R_{11}|
are considered linearly-dependent and are excluded from the covariance matrix (the corresponding rows and columns of the covariance matrix are set to zero).

If the minimisation uses the weighted least-squares function
f_i = (Y(x, t_i) - y_i) / sigma_i then the covariance
matrix above gives the statistical error on the best-fit parameters resulting from the gaussian errors sigma_i on
the underlying data y_i. This can be verified from the relation
delta f = J delta c and the fact that the fluctuations in f
from the data y_i are normalised by sigma_i and
so satisfy <delta f delta f^T> = I.

For an unweighted least-squares function f_i = (Y(x, t_i) -
y_i) the covariance matrix above should be multiplied by the variance
of the residuals about the best-fit sigma^2 = sum (y_i - Y(x,t_i))^2 / (n-p) to give the variance-covariance matrix sigma^2 C.
This estimates the statistical error on the
best-fit parameters from the scatter of the underlying data.

For more information about covariance matrices see the GSL documentation Fitting Overview.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: make-acceleration ()

Create the GSL object representing a acceleration for interpolation (class ACCELERATION). Make an accelerator object, which is a
kind of iterator for interpolation lookups. It tracks the state of
lookups, thus allowing for application of various acceleration
strategies.

Package

gsll.

Source

lookup.lisp.

Function: make-basis-spline (order number-of-breakpoints)

Create the GSL object representing a basis spline (class BASIS-SPLINE). Allocate a workspace for computing B-splines. The number of breakpoints is given by number-of-breakpoints. This leads to n = nbreak + k - 2 basis functions where k = order. Cubic B-splines are specified by k = 4. The size of the workspace is O(5k + nbreak).

Package

gsll.

Source

basis-splines.lisp.

Function: make-chebyshev (order &optional function lower-limit upper-limit scalarsp)

Create the GSL object representing a Chebyshev series (class CHEBYSHEV). Make a Chebyshev series of specified order.

Package

gsll.

Source

chebyshev.lisp.

Function: make-combination (n &optional k initialize)

Make the object representing a combination of k things from a set of n. If initialize is T, initialize as the first k values (init-first). If n is a combination, make a new combination with the same specification. If initialize is also T, copy it.

Package

gsll.

Source

combination.lisp.

Function: make-discrete-random (probabilities)

Create the GSL object representing a lookup table for the discrete random number generator (class DISCRETE-RANDOM). Make a structure that contains the lookup
table for the discrete random number generator. The array probabilities contains
the probabilities of the discrete events; these array elements must all be
positive, but they needn’t add up to one (so you can think of them more
generally as “weights”)—the preprocessor will normalize appropriately.
This return value is used as an argument to #’discrete.

Package

gsll.

Source

discrete.lisp.

Function: make-eigen-gen (n)

Create the GSL object representing a generalized nonsymmetric eigenvalue workspace (class EIGEN-GEN). Make a workspace for computing eigenvalues of n-by-n real
generalized nonsymmetric eigensystems. The size of the workspace
is O(n).

Package

gsll.

Source

nonsymmetric-generalized.lisp.

Function: make-eigen-genherm (n)

Create the GSL object representing a hermitian generalized eigenvalue workspace (class EIGEN-GENHERM). Make a workspace for computing eigenvalues of n-by-n complex
generalized hermitian-definite eigensystems. The size of the
workspace is O(3n).

Package

gsll.

Source

generalized.lisp.

Function: make-eigen-genhermv (n)

Create the GSL object representing a hermitian generalized eigensystem workspace (class EIGEN-GENHERMV). Make a workspace for computing eigenvalues and eigenvectors of
n-by-n complex generalized hermitian-definite eigensystems. The
size of the workspace is O(5n).

Package

gsll.

Source

generalized.lisp.

Function: make-eigen-gensymm (n)

Create the GSL object representing a symmetric generalized eigenvalue workspace (class EIGEN-GENSYMM). Make a workspace for computing eigenvalues of n-by-n real
generalized symmetric-definite eigensystems. The size of the workspace
is O(2n).

Package

gsll.

Source

generalized.lisp.

Function: make-eigen-gensymmv (n)

Create the GSL object representing a symmetric generalized eigensystem workspace (class EIGEN-GENSYMMV). Make a workspace for computing eigenvalues and eigenvectors of
n-by-n real generalized symmetric-definite eigensystems. The size
of the workspace is O(4n).

Package

gsll.

Source

generalized.lisp.

Function: make-eigen-genv (n)

Create the GSL object representing a generalized nonsymmetric eigenvector and eigenvalue workspace (class EIGEN-GENV). Make a workspace for computin geigenvalues and eigenvectors of
n-by-n real generalized nonsymmetric eigensystems. The size of the
workspace is O(7n).

Package

gsll.

Source

nonsymmetric-generalized.lisp.

Function: make-eigen-herm (n)

Create the GSL object representing a Hermitian eigenvalue workspace (class EIGEN-HERM). Make a workspace for computing eigenvalues of
n-by-n complex Hermitian matrices. The size of the workspace
is O(3n).

Package

gsll.

Source

symmetric-hermitian.lisp.

Function: make-eigen-hermv (n)

Create the GSL object representing a Hermitian eigensystem workspace (class EIGEN-HERMV). Make a workspace for computing eigenvalues and
eigenvectors of n-by-n complex hermitian matrices. The size of
the workspace is O(5n).

Package

gsll.

Source

symmetric-hermitian.lisp.

Function: make-eigen-nonsymm (n)

Create the GSL object representing a non-symmetric eigenvalue workspace (class EIGEN-NONSYMM). Make a workspace for computing eigenvalues of
n-by-n real non-symmetric matrices. The size of the workspace
is O(2n).

Package

gsll.

Source

nonsymmetric.lisp.

Function: make-eigen-nonsymmv (n)

Create the GSL object representing a non-symmetric eigenvector and eigenvalue workspace (class EIGEN-NONSYMMV). Make a workspace for computing for computing eigenvalues and
eigenvectors of n-by-n real nonsymmetric matrices. The size of the
workspace is O(5n).

Package

gsll.

Source

nonsymmetric.lisp.

Function: make-eigen-symm (n)

Create the GSL object representing a symmetric eigenvalue workspace (class EIGEN-SYMM). Make a workspace for computing eigenvalues of
n-by-n real symmetric matrices. The size of the workspace
is O(2n).

Package

gsll.

Source

symmetric-hermitian.lisp.

Function: make-eigen-symmv (n)

Create the GSL object representing a symmetric eigensystem workspace (class EIGEN-SYMMV). Make a workspace for computing eigenvalues and
eigenvectors of n-by-n real symmetric matrices. The size of
the workspace is O(4n).

Package

gsll.

Source

symmetric-hermitian.lisp.

Function: make-fft-wavetable (element-type dimension &optional half-complex)

Make a wavetable for an FFT of the given element type and length. T can be given as an optional third argument if the wavetable is meant for a Fourier transform on a half-complex vector.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-workspace (element-type dimension)

Make a wavetable for an FFT of the given element type and length.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fit-workspace (number-of-observations number-of-parameters)

Create the GSL object representing a multi-dimensional root solver with function only (class FIT-WORKSPACE). Make a workspace for a multidimensional linear least-squares fit.

Package

gsll.

Source

linear-least-squares.lisp.

Function: make-hankel (size &optional nu xmax)

Create the GSL object representing a discrete Hankel Transform (class HANKEL). Allocate a Discrete Hankel transform object of the given size and optionally initialize the transform for the given values of nu and x.

Package

gsll.

Source

hankel.lisp.

Function: make-histogram (number-of-bins &optional ranges)

Create the GSL object representing a one-dimensional histogram, including bin boundaries and bin contents (class HISTOGRAM).

Package

gsll.

Source

histogram.lisp.

Function: make-histogram-pdf (number-of-bins &optional histogram)

Create the GSL object representing a one-dimensional histogram PDF (class HISTOGRAM-PDF). Optionally initialize the probability distribution pdf with the contents
of the histogram. If any of the bins are negative then an
input-domain error is signalled because a probability distribution
cannot contain negative values.

Package

gsll.

Source

probability-distribution.lisp.

Function: make-histogram2d (number-of-bins-x number-of-bins-y &optional x-ranges y-ranges)

Create the GSL object representing a two-dimensional histogram, including bin boundaries and bin contents. (class HISTOGRAM2D).

Package

gsll.

Source

histogram.lisp.

Function: make-histogram2d-pdf (number-of-bins-x number-of-bins-y &optional histogram)

Create the GSL object representing a two-dimensional histogram PDF (class HISTOGRAM2D-PDF). Optionally initialize the probability distribution pdf with the contents
of the histogram. If any of the bins are negative then an
input-domain error is signalled because a probability distribution
cannot contain negative values.

Package

gsll.

Source

probability-distribution.lisp.

Function: make-integration-workspace (size)

Create the GSL object representing a integration workspace (class INTEGRATION-WORKSPACE). Make a workspace sufficient to hold n double
precision intervals, their integration results and error estimates.

Package

gsll.

Source

numerical-integration.lisp.

Function: make-interpolation (type &optional xa-or-size ya)

Create the GSL object representing a interpolation (class INTERPOLATION).
Make an interpolation object of type for size data-points,
and optionally initialize the interpolation object interp for the
data (xa,ya) where xa and ya are vectors. The interpolation object does not save the data arrays xa and ya and only stores the static state
computed from the data. The xa data array is always assumed to be
strictly ordered; the behavior for other arrangements is not defined.

Package

gsll.

Source

interpolation.lisp.

Function: make-jacobian-matrix (solver)

Make an empty Jacobian matrix for nonlinear least squares.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: make-levin (order)

Create the GSL object representing a Levin u-transform (class LEVIN). Make a workspace for a Levin u-transform of n
terms. The size of the workspace is O(2n^2 + 3n).

Package

gsll.

Source

series-acceleration.lisp.

Function: make-levin-truncated (order)

Create the GSL object representing a truncated Levin u-transform (class LEVIN-TRUNCATED). Make a workspace for a Levin u-transform of n
terms, without error estimation. The size of the workspace is
O(3n).

Package

gsll.

Source

series-acceleration.lisp.

Function: make-mathieu (n qmax)

Create the GSL object representing a workspace for Mathieu functions (class MATHIEU). Make a workspace needed for some Mathieu functions.

Package

gsll.

Source

mathieu.lisp.

Function: make-monte-carlo-miser (dim)

Create the GSL object representing a miser Monte Carlo integration (class MONTE-CARLO-MISER). Make and initialize a workspace for Monte Carlo integration in
dimension dim. The workspace is used to maintain
the state of the integration.

Package

gsll.

Source

monte-carlo.lisp.

Function: make-monte-carlo-plain (dim)

Create the GSL object representing a plain Monte Carlo integration (class MONTE-CARLO-PLAIN). Make and initialize a workspace for Monte Carlo integration in dimension dim.

Package

gsll.

Source

monte-carlo.lisp.

Function: make-monte-carlo-vegas (dim)

Create the GSL object representing a vegas Monte Carlo integration (class MONTE-CARLO-VEGAS). Make and initialize a workspace for Monte Carlo integration in
dimension dim. The workspace is used to maintain
the state of the integration. Returns a pointer to vegas-state.

Package

gsll.

Source

monte-carlo.lisp.

Function: make-multi-dimensional-minimizer-f (type dimension &optional function initial step-size scalarsp)

Create the GSL object representing a multi-dimensional minimizer with function only (class MULTI-DIMENSIONAL-MINIMIZER-F). Make an instance of a minimizer for a function of the given
dimensions without derivative. Optionally initialize the minimizer
to minimize the function starting from the initial point. The size
of the initial trial steps is given in vector step-size. The
precise meaning of this parameter depends on the method used.

Package

gsll.

Source

minimization-multi.lisp.

Function: make-multi-dimensional-minimizer-fdf (type dimension &optional functions initial step-size tolerance scalarsp)

Create the GSL object representing a multi-dimensional minimizer with function and derivative (class MULTI-DIMENSIONAL-MINIMIZER-FDF). Make an instance of a minimizer for a function of the given
dimensions with a derivative. Optionally initialize the minimizer
to minimize the function starting from the initial point. The size
of the first trial step is given by step-size. The accuracy of the
line minimization is specified by tolernace. The precise meaning
of this parameter depends on the method used. Typically the line
minimization is considered successful if the gradient of the
function g is orthogonal to the current search direction p to a
relative accuracy of tolerance, where dot(p,g) < tol |p| |g|.

Package

gsll.

Source

minimization-multi.lisp.

Function: make-multi-dimensional-root-solver-f (type &optional function-or-dimension initial scalarsp)

Create the GSL object representing a multi-dimensional root solver with function only (class MULTI-DIMENSIONAL-ROOT-SOLVER-F). Make an instance of a solver of the type specified for a system of
the specified number of dimensions. Optionally
set or reset an existing solver to use the function and the
initial guess gsl-vector. If scalarsp is T, the functions will
be supplied scalars, and should return scalars.

Package

gsll.

Source

roots-multi.lisp.

Function: make-multi-dimensional-root-solver-fdf (type &optional function-or-dimension initial scalarsp)

Create the GSL object representing a multi-dimensional root solver with function and derivative (class MULTI-DIMENSIONAL-ROOT-SOLVER-FDF). Make an instance of a derivative solver of the type specified for
a system of the specified number of dimensions. Optionally
set or reset an existing solver to use the function and derivative
(fdf) and the initial guess. If scalarsp is T, the functions will
be supplied, and should return scalars.

Package

gsll.

Source

roots-multi.lisp.

Function: make-nonlinear-fdffit (solver-type dimensions &optional functions initial-guess scalarsp)

Create the GSL object representing a nonlinear least squares fit with function and derivative (class NONLINEAR-FDFFIT). The number of observations must be greater than or
equal to parameters.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: make-nonlinear-ffit (solver-type dimensions &optional function initial-guess scalarsp)

Create the GSL object representing a nonlinear least squares fit with function only (class NONLINEAR-FFIT). The number of observations must be greater than or equal to parameters.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: make-ode-evolution (dimensions)

Create the GSL object representing a evolution for ordinary differential equations (class ODE-EVOLUTION). Make an object to advance the ODE solution.

Package

gsll.

Source

evolution.lisp.

Function: make-ode-stepper (type dimension &optional function jacobian scalarsp)

Create the GSL object representing a stepper for ordinary differential equations (class ODE-STEPPER). Make a stepper for ordinary differential equations. The type is
one of the GSL-supplied types defined in stepping.lisp, and
dimensions is the number of dependent variables. This instance
should be reinitialized whenever the next use of it will not be a
continuation of a previous step.

Package

gsll.

Source

stepping.lisp.

Function: make-one-dimensional-minimizer (type &optional function x-minimum x-lower x-upper f-minimum f-lower f-upper)

Create the GSL object representing a one-dimensional minimizer (class ONE-DIMENSIONAL-MINIMIZER). Make an instance of a minimizer of the given type. Specify
a guess of the minimum point, the search interval
(x-minimum x-lower x-upper) and optionally
function values at those points (f-minimum f-lower f-upper).

Package

gsll.

Source

minimization-one.lisp.

Function: make-one-dimensional-root-solver-f (type &optional function lower upper scalarsp)

Create the GSL object representing a one-dimensional root solver with function only (class ONE-DIMENSIONAL-ROOT-SOLVER-F).

Package

gsll.

Source

roots-one.lisp.

Function: make-one-dimensional-root-solver-fdf (type &optional function df fdf root-guess)

Create the GSL object representing a one-dimensional root solver with function and derivative (class ONE-DIMENSIONAL-ROOT-SOLVER-FDF).

Package

gsll.

Source

roots-one.lisp.

Function: make-permutation (size &optional initialize)

Create the GSL object representing a permutation (class PERMUTATION).

Package

gsll.

Source

permutation.lisp.

Function: make-polynomial-complex-workspace (n)

Create the GSL object representing a complex workspace for polynomials (class POLYNOMIAL-COMPLEX-WORKSPACE).

Package

gsll.

Source

polynomial.lisp.

Function: make-qawo-table (omega l trig n)

Create the GSL object representing a table for QAWO numerical integration method (class QAWO-TABLE). Make a table describing a sine or cosine weight function W(x) with
the parameters (omega, L),
W(x) = sin(omega x)
W(x) = cos(omega x)
The parameter L must be the length of the interval over which the
function will be integrated L = b - a. The choice of sine or cosine
is made with the parameter trig which should be one of :cosine or :sine.
This makes a table of the trigonometric coefficients required in the
integration process. The parameter n determines the number of levels
of coefficients that are computed. Each level corresponds to one
bisection of the interval L, so that n levels are sufficient for
subintervals down to the length L/2^n. An error of class
’table-limit-exceeded is signalled if the number of levels is
insufficient for the requested accuracy.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: make-qaws-table (alpha beta mu nu)

Create the GSL object representing a table for QAWS numerical integration method (class QAWS-TABLE). Make and initialize a table for the QAWS
adaptive integration method for singular functions.
It a singular weight function W(x) with the parameters (alpha, beta, mu, nu),
W(x) = (x-a)^alpha (b-x)^beta log^mu (x-a) log^nu (b-x)
where alpha > -1, beta > -1, and mu = 0, 1, nu = 0, 1. The
weight function can take four different forms depending on the
values of mu and nu,
W(x) = (x-a)^alpha (b-x)^beta (mu = 0, nu = 0)
W(x) = (x-a)^alpha (b-x)^beta log(x-a) (mu = 1, nu = 0)
W(x) = (x-a)^alpha (b-x)^beta log(b-x) (mu = 0, nu = 1)
W(x) = (x-a)^alpha (b-x)^beta log(x-a) log(b-x) (mu = 1, nu = 1)
The singular points (a,b) do not have to be specified until the
integral is computed, where they are the endpoints of the integration
range.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: make-quasi-random-number-generator (rng-type dimension)

Create the GSL object representing a quasi random number generator (class QUASI-RANDOM-NUMBER-GENERATOR). Make and optionally initialize the generator q to its starting point.
Note that quasi-random sequences do not use a seed and always produce
the same set of values.

Package

gsll.

Source

quasi.lisp.

Function: make-random-number-generator (rng-type &optional value)

Create the GSL object representing a random number generator (class RANDOM-NUMBER-GENERATOR). Make and optionally initialize (or ‘seed’) the random number
generator of the specified type. If the generator is seeded with
the same value of s on two different runs, the same stream of
random numbers will be generated by successive calls. If different
values of s are supplied, then the generated streams of random
numbers should be completely different. If the seed s is zero then
the standard seed from the original implementation is used instead.
For example, the original Fortran source code for the *ranlux*
generator used a seed of 314159265, and so choosing s equal to zero
reproduces this when using *ranlux*.

Package

gsll.

Source

generators.lisp.

Function: make-scaled-control (absolute-error relative-error y-scaling dydt-scaling absolute-scale dimension)

Create the GSL object representing a scaled control for ordinary differential equations (class SCALED-CONTROL). Create a new control object which uses the same algorithm
as #’new-standard-control but with an absolute error
which is scaled for each component by the array absolute-error.
The formula for D_i for this control object is
D_i = epsilon_{abs} s_i + epsilon_{rel} * (a_{y} |y_i| + a_{dydt} h |y’_i|)
where s_i is the i-th component of the array absolute-scale.
The same error control heuristic is used by the Matlab ode suite.

Package

gsll.

Source

control.lisp.

Function: make-spline (type &optional xa-or-size ya)

Create the GSL object representing a spline (class SPLINE). Make an interpolation object of type for size data-points.

Package

gsll.

Source

interpolation.lisp.

Function: make-standard-control (absolute-error relative-error y-scaling dydt-scaling)

Create the GSL object representing a standard control for ordinary differential equations (class STANDARD-CONTROL). The standard control object is a four parameter heuristic based on
absolute and relative errors absolute-error and relative-error, and
scaling factors y-scaling and dydt-scaling for the system state y(t) and derivatives
y’(t) respectively.

The step-size adjustment procedure for this method begins by computing
the desired error level D_i for each component,
D_i = epsilon_{absolute} + epsilon_{relative} * (a_{y} |y_i| + a_{dydt} h |y’_i|)
and comparing it with the observed error E_i = |yerr_i|. If the
observed error E exceeds the desired error level D by more
than 10% for any component then the method reduces the step-size by an
appropriate factor,
h_{new} = h_{old} * S * (E/D)^{-1/q}
where g is the consistency order of the method (e.g. q=4 for
4(5) embedded RK), and S is a safety factor of 0.9. The ratio
E/D is taken to be the maximum of the ratios E_i/D_i.

If the observed error E is less than 50% of the desired error
level D for the maximum ratio E_i/D_i then the algorithm
takes the opportunity to increase the step-size to bring the error in
line with the desired level,
h_{new} = h_{old} * S * (E/D)^{-1/(q+1)}
This encompasses all the standard error scaling methods. To avoid
uncontrolled changes in the stepsize, the overall scaling factor is
limited to the range 1/5 to 5.

Package

gsll.

Source

control.lisp.

Function: make-wavelet (type member)

Create the GSL object representing a wavelet (class WAVELET). Make and initialize a wavelet object of type ’type. The parameter ’member selects the specific member of the wavelet family. A memory-allocation-failure error indicates either lack of memory or an unsupported member requested.

Package

gsll.

Source

wavelet.lisp.

Function: make-wavelet-workspace (size)

Create the GSL object representing a wavelet workspace (class WAVELET-WORKSPACE). Make a workspace for the discrete wavelet transform.
To perform a one-dimensional transform on size elements, a workspace
of size size must be provided. For two-dimensional transforms of size-by-size matrices it is sufficient to allocate a workspace of
size, since the transform operates on individual rows and
columns.

Package

gsll.

Source

wavelet.lisp.

Function: make-y-control (absolute-error relative-error &optional y-scaling dydt-scaling)

Create the GSL object representing a y control for ordinary differential equations (class Y-CONTROL). Create a new control object which will keep the local
error on each step within an absolute error of absolute-error and
relative error of relative-error with respect to the solution y_i(t).
This is equivalent to the standard control object with y-scaling=1 and
dydt-scaling=0.

Package

gsll.

Source

control.lisp.

Function: make-yp-control (absolute-error relative-error &optional y-scaling dydt-scaling)

Create the GSL object representing a yp control for ordinary differential equations (class YP-CONTROL). Create a new control object which will keep the local
error on each step within an absolute error of absolute-error and
relative error of relative-error with respect to the derivatives of the
solution y’_i(t). This is equivalent to the standard control
object with y-scaling=0 and dydt-scaling=1.

Package

gsll.

Source

control.lisp.

Function: mathieu-a (n q)

Compute the characteristic value a_n(q) of the Mathieu function ce_n(q,x) respectively.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-a-array (q &optional size-or-array minimum-order workspace)

Compute a series of Mathieu characteristic values a_n(q) for n from minimum-order to minimum-order + size - 1 inclusive, where size is either the numerical value supplied in size-or-array, or the the length of the vector supplied there.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-b (n q)

Compute the characteristic values b_n(q) of the Mathieu function se_n(q,x), respectively.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-b-array (q &optional size-or-array minimum-order workspace)

Compute a series of Mathieu characteristic values b_n(q) for n from minimum-order to minimum-order + size - 1 inclusive, where size is either the numerical value supplied in size-or-array, or the the length of the vector supplied there.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-ce (n q x)

Compute the angular Mathieu functions ce_n(q,x).

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-ce-array (q x &optional size-or-array minimum-order workspace)

Compute a series of the angular Mathieu function ce_n(q) for n from minimum-order to minimum-order + size - 1 inclusive, where size is either the numerical value supplied in size-or-array, or the the length of the vector supplied there.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-mc (j n q x)

Compute the radial j-th kind Mathieu functions Mc_n^{(j)}(q,x) of order n. The allowed values of j are 1 and 2. The functions for j = 3,4 can be computed as M_n^{(3)} = M_n^{(1)} + iM_n^{(2)} and M_n^{(4)} = M_n^{(1)} - iM_n^{(2)}, where M_n^{(j)} = Mc_n^{(j)} or Ms_n^{(j)}.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-mc-array (j q x &optional size-or-array minimum-order workspace)

Compute a series of the radial Mathieu function of kind j for n from minimum-order to minimum-order + size inclusive, where size is either the numerical value supplied in size-or-array, or the the length of the vector supplied there.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-ms (j n q x)

Compute the radial j-th kind Mathieu functions Ms_n^{(j)}(q,x) of order n. The allowed values of j are 1 and 2. The functions for j = 3,4 can be computed as M_n^{(3)} = M_n^{(1)} + iM_n^{(2)} and M_n^{(4)} = M_n^{(1)} - iM_n^{(2)}, where M_n^{(j)} = Mc_n^{(j)} or Ms_n^{(j)}.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-ms-array (j q x &optional size-or-array minimum-order workspace)

Compute a series of the radial Mathieu function of kind j for n from minimum-order to minimum-order + size inclusive, where size is either the numerical value supplied in size-or-array, or the the length of the vector supplied there.

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-se (n q x)

Compute the angular Mathieu functions se_n(q,x).

Package

gsll.

Source

mathieu.lisp.

Function: mathieu-se-array (q x &optional size-or-array minimum-order workspace)

Compute a series of the angular Mathieu function se_n(q) for n from minimum-order to minimum-order + size - 1 inclusive, where size is either the numerical value supplied in size-or-array, or the the length of the vector supplied there.

Package

gsll.

Source

mathieu.lisp.

Function: matrix-exponential (matrix exponential &optional mode)

Calculate the matrix exponential by the scaling and squaring method described in Moler + Van Loan,
SIAM Rev 20, 801 (1978). The matrix to be exponentiated is matrix, the returned exponential is exponential. The mode argument allows
choosing an optimal strategy, from the table
given in the paper, for a given precision.

Package

gsll.

Source

exponential.lisp.

Function: mfdfminimizer-gradient (minimizer)

The current best estimate of the gradient for the minimizer.

Package

gsll.

Source

minimization-multi.lisp.

Function: mfdfminimizer-restart (minimizer)

Reset the minimizer to use the current point as a new starting point.

Package

gsll.

Source

minimization-multi.lisp.

Function: min-test-gradient (gradient absolute-error)

Test the norm of the gradient against the
absolute tolerance absolute-error. The gradient of a multidimensional function goes to zero at a minimum. The test returns T
if |g| < epsabs is achieved, and NIL otherwise. A suitable choice of absolute-error can be made from the desired accuracy in the function for small variations in x. The relationship between these quantities delta f = g delta x.

Package

gsll.

Source

minimization-multi.lisp.

Function: min-test-interval (lower upper absolute-error relative-error)

Test for the convergence of the interval [lower,upper]
with absolute error and relative error specified.
The test returns T if the following condition is achieved:
|a - b| < epsabs + epsrel min(|a|,|b|)
when the interval x = [a,b] does not include the origin. If the interval includes the origin then min(|a|,|b|) is replaced by
zero (which is the minimum value of |x| over the interval). This ensures that the relative error is accurately estimated for minima close to the origin.

This condition on the interval also implies that any estimate of the minimum x_m in the interval satisfies the same condition with respect to the true minimum x_m^*,
|x_m - x_m^*| < epsabs + epsrel x_m^*
assuming that the true minimum x_m^* is contained within the interval.

Package

gsll.

Source

minimization-one.lisp.

Function: min-test-size (size absolute-error)

Test the minimizer specific characteristic size (if applicable to
the used minimizer) against absolute tolerance absolute-error. The test returns T if the size is smaller than tolerance, and NIL otherwise.

Package

gsll.

Source

minimization-multi.lisp.

Function: modulus (number)

The magnitude, or modulus of the complex number.

Package

gsll.

Source

complex.lisp.

Function: modulus2 (number)

The magnitude squared of the complex number.

Package

gsll.

Source

complex.lisp.

Function: monte-carlo-integrate-miser (function lower-limits upper-limits &optional number-of-samples generator state scalars)

Uses the miser Monte Carlo algorithm to integrate the
function f over the hypercubic region defined by the
lower and upper limits in the arrays ’lower-limits and
’upper-limits, each a gsl-vector of the samelength
The integration uses a fixed number
of function calls number-of-samples, and obtains random sampling points using the random number generator ’generator. A previously allocated workspace ’state must be supplied. The result of the integration is returned
with an estimated absolute error.

Package

gsll.

Source

monte-carlo.lisp.

Function: monte-carlo-integrate-plain (function lower-limits upper-limits &optional number-of-samples generator state scalars)

Uses the plain Monte Carlo algorithm to integrate the
function f over the hypercubic region defined by the
lower and upper limits in the arrays ’lower-limits and
’upper-limits, each a gsl-vector of length dim.
The integration uses a fixed number
of function calls number-of-samples, and obtains random sampling points using the random number generator ’generator. A previously allocated workspace ’state must be supplied. The result of the integration is returned
with an estimated absolute error.

Package

gsll.

Source

monte-carlo.lisp.

Function: monte-carlo-integrate-vegas (function lower-limits upper-limits &optional number-of-samples generator state scalars)

Uses the vegas Monte Carlo algorithm to integrate the function f over the dim-dimensional hypercubic region defined by the lower and upper limits in the arrays x1 and xu, each of the same length. The integration uses a fixed number of function calls number-of-samples, and obtains random sampling points using the random number generator r. A previously allocated workspace s must be supplied. The result of the integration is returned with an estimated absolute error. The result and its error estimate are based on a weighted average of independent samples. The chi-squared per degree of freedom for the weighted average is returned via the state struct component, s->chisq, and must be consistent with 1 for the weighted average to be reliable.

Package

gsll.

Source

monte-carlo.lisp.

Function: multi-linear-estimate (x coefficients covariance)

Use the best-fit multilinear regression coefficients
and their covariance matrix to compute the fitted function value y and its standard deviation for the model y = x.c
at the point x.

Package

gsll.

Source

linear-least-squares.lisp.

Function: multi-linear-residuals (x observations coefficients &optional residuals)

Compute the vector of residuals r = y - X c for the observations y, coefficients c and matrix of predictor variables X.

Package

gsll.

Source

linear-least-squares.lisp.

Function: multinomial-log-pdf (p n)

Compute the natural logarithm of the probability P(n_1, n_2, ..., n_K) of sampling n[K] from a multinomial distribution
with parameters p[K], using the formula given for #’sample :multinomial.

Package

gsll.

Source

multinomial.lisp.

Function: multinomial-pdf (p n)

Compute the probability P(n_1, n_2, ..., n_K)
of sampling n[K] from a multinomial distribution
with parameters p[K], using the formula given for #’sample :multinomial.

Package

gsll.

Source

multinomial.lisp.

Function: multiplier-estimate (x c1 cov11)

Use the best-fit linear regression coefficient
c1 and its covariance cov11 to compute the fitted function y and its standard deviation y-error for the model
Y = c_0 + c_1 X at the point x.

Package

gsll.

Source

linear-least-squares.lisp.

Function: multiplier-fit (x y &optional weight x-stride y-stride weight-stride)

Compute the best-fit linear regression coefficient
c1 of the model Y = c_1 X for the weighted or unweighted datasets (x, y), two vectors of equal length with strides
x-stride and y-stride. The vector weight of the same length and of stride w-stide specifies the weight of each datapoint. The weight is the reciprocal of the variance for each datapoint in y.
The variance of the parameter c1 is computed using the weights and returned as the second value. The weighted sum of squares of the residuals from the best-fit line, chi^2, is returned as the last value.

Package

gsll.

Source

linear-least-squares.lisp.

Function: multiply (x y)

Multiplies two double-floats returning the product and associated error.

Package

gsll.

Source

elementary.lisp.

Function: multiply-err (x dx y dy)

Multiplies two double floats x and y with associated absolute errors dx and dy. The product xy +/- xy sqrt((dx/x)^2 +(dy/y)^2) is returned.

Package

gsll.

Source

elementary.lisp.

Function: multiroot-test-delta (solver absolute-error relative-error)

Test for the convergence of the sequence by comparing the last step dx with the absolute error and relative errors given to the current position x. The test returns T if the following condition is achieved:
|dx_i| < epsabs + epsrel |x_i|
for each component of x and returns NIL otherwise.

Package

gsll.

Source

roots-multi.lisp.

Function: multiroot-test-residual (solver absolute-error)

Test the residual value f against the absolute error, returning T if the following condition is achieved: sum_i |f_i| < absolute_error
and returns NIL otherwise. This criterion is suitable for situations where the precise location of the root x is unimportant provided a value can be found where the residual is small enough.

Package

gsll.

Source

roots-multi.lisp.

Function: nanp (x)

Return T if x is a double-float NaN.

Package

gsll.

Source

mathematical.lisp.

Function: negative-binomial-p (k p n)

The cumulative distribution functions P(k) for the negative binomial distribution with parameters p and n.

Package

gsll.

Source

negative-binomial.lisp.

Function: negative-binomial-pdf (k p n)

The probability p(k) of obtaining k
from a negative binomial distribution with parameters p and n, using the formula given in #’sample :negative-binomial.

Package

gsll.

Source

negative-binomial.lisp.

Function: negative-binomial-q (k p n)

The cumulative distribution functions Q(k) for the negative binomial distribution with parameters p and n.

Package

gsll.

Source

negative-binomial.lisp.

Function: nonnormalized-incomplete-gamma (a x)

The incomplete Gamma Function
Gamma(a,x), without the normalization factor included in the previously defined functions: Gamma(a,x) = int_x^infty dt t^{a-1} exp(-t) for a real and x >= 0.

Package

gsll.

Source

gamma.lisp.

Function: number-of-breakpoints (bspline)

The number of breakpoints of the basis spline bspline.

Package

gsll.

Source

basis-splines.lisp.

Function: number-of-coefficients (bspline)
Package

gsll.

Source

basis-splines.lisp.

Function: open-ntuple (filename data foreign-type)

Open an existing ntuple file filename for reading
and return a pointer to a corresponding ntuple struct. The ntuples in the file must have size size. A pointer to memory for the current ntuple row data must be supplied—this is used to copy
ntuples in and out of the file.

Package

gsll.

Source

ntuple.lisp.

Function: pareto-p (x a b)

The cumulative distribution functions
P(x) for the Pareto distribution with exponent a and scale b.

Package

gsll.

Source

pareto.lisp.

Function: pareto-pdf (x a b)

The probability density p(x) at x
for a Pareto distribution with exponent a and scale b, using the formula given in #’sample :pareto.

Package

gsll.

Source

pareto.lisp.

Function: pareto-pinv (p a b)

The inverse cumulative distribution functions
P(x) for the Pareto distribution with exponent a and scale b.

Package

gsll.

Source

pareto.lisp.

Function: pareto-q (x a b)

The cumulative distribution functions
Q(x) for the Pareto distribution with exponent a and scale b.

Package

gsll.

Source

pareto.lisp.

Function: pareto-qinv (q a b)

The inverse cumulative distribution functions
Q(x) for the Pareto distribution with exponent a and scale b.

Package

gsll.

Source

pareto.lisp.

Function: pascal-p (k p n)

The cumulative distribution functions P(k) for the Pascal distribution with parameters p and n.

Package

gsll.

Source

negative-binomial.lisp.

Function: pascal-pdf (k p n)

The probability p(k) of obtaining k
from a Pascal distribution with parameters p and n, using the formula given in #’sample :pascal.

Package

gsll.

Source

negative-binomial.lisp.

Function: pascal-q (k p n)

The cumulative distribution functions Q(k) for the Pascal distribution with parameters p and n.

Package

gsll.

Source

negative-binomial.lisp.

Function: permutation* (p pa pb)

Combine the two permutations pa and pb into a single permutation p where p = pa . pb. The permutation p is equivalent to applying pb first and then pa.

Package

gsll.

Source

permutation.lisp.

Function: permutation-data (p)

A pointer to the array of elements in the permutation p.

Package

gsll.

Source

permutation.lisp.

Function: permutation-inverse (p &optional inv)

Find the inverse of the permutation p.

Package

gsll.

Source

permutation.lisp.

Function: permutation-next (p)

Advance the permutation p to the next permutation
in lexicographic order and return p and T. If no further permutations are available, return p and NIL with
p unmodified. Starting with the identity permutation and repeatedly applying this function will iterate through all possible permutations of a given order.

Package

gsll.

Source

permutation.lisp.

Function: permutation-previous (p)

Step backwards from the permutation p to the
previous permutation in lexicographic order, returning p and T. If no previous permutation is available, return
p and NIL with p unmodified.

Package

gsll.

Source

permutation.lisp.

Function: permutation-reverse (p)

Reverse the order of the elements of the permutation p.

Package

gsll.

Source

permutation.lisp.

Function: pochammer (a x)

The Pochhammer symbol (a)_x := Gamma(a +
x)/Gamma(a), subject to a and a+x not being negative
integers. The Pochhammer symbol is also known as the Apell symbol and sometimes written as (a,x).

Package

gsll.

Source

gamma.lisp.

Function: poisson-p (k mu)

The cumulative distribution functions
P(k) for the Poisson distribution with parameter mu.

Package

gsll.

Source

poisson.lisp.

Function: poisson-pdf (k mu)

The probability p(k) of obtaining k
from a Poisson distribution with mean mu using the formula given in #’sample :poisson.

Package

gsll.

Source

poisson.lisp.

Function: poisson-q (k mu)

The cumulative distribution functions
Q(k) for the Poisson distribution with parameter mu.

Package

gsll.

Source

poisson.lisp.

Function: polar-to-rectangular (r theta)

Convert the polar coordinates (r, theta) to
rectilinear coordinates (x, y), x = rcos(theta), y = rsin(theta).

Package

gsll.

Source

trigonometry.lisp.

Function: polynomial-solve (coefficients &optional answer workspace)

Arguments are: a vector-double-float of coefficients, a complex vector of length one less than coefficients that will hold the answer, and a workspace made by make-polynomial-complex-workspace. The roots of the general polynomial
P(x) = a_0 + a_1 x + a_2 x^2 + ... + a_{n-1} x^{n-1} using balanced-QR reduction of the companion matrix. The coefficient of the highest order term must be non-zero.

Package

gsll.

Source

polynomial.lisp.

Function: pow (x n)

The power x^n for integer n. The
power is computed using the minimum number of multiplications. For example, x^8 is computed as ((x^2)^2)^2, requiring only 3 multiplications. For reasons of efficiency, these functions do not check for overflow or underflow conditions.

Package

gsll.

Source

power.lisp.

Function: project-ntuple (histogram ntuple value-function select-function)

Update the histogram from the ntuple
using the functions value-function and select-function. For each ntuple row where the selection function select-function is non-zero the corresponding value of that row is computed using the function value-function and added to the histogram. Those ntuple rows where select-function returns zero are ignored. New entries are added to the histogram, so subsequent calls can be used to accumulate further data in the same histogram.

Package

gsll.

Source

ntuple.lisp.

Function: psi-1+iy (x)

The real part of the digamma function on the line 1+i y, Re[psi(1 + i y)].

Package

gsll.

Source

psi.lisp.

Function: psi-n (m x)

The polygamma function psi^{(m)}(x)} for m >= 0, x > 0.

Package

gsll.

Source

psi.lisp.

Function: qr-decomposition (a &optional tau)

Factorize the M-by-N matrix A into the QR decomposition A = Q R.
On output the diagonal and
upper triangular part of the input matrix contain the matrix
R. The vector tau and the columns of the lower triangular
part of the matrix A contain the Householder coefficients and Householder vectors which encode the orthogonal matrix Q. The vector tau must be of length k=min(M,N). The matrix
Q is related to these components by, Q = Q_k ... Q_2 Q_1
where Q_i = I - tau_i v_i v_i^T and v_i is the
Householder vector v_i = (0,...,1,A(i+1,i),A(i+2,i),...,A(m,i)). This is the same storage scheme as used by lapack.

The algorithm used to perform the decomposition is Householder QR (Golub & Van Loan, Matrix Computations, Algorithm 5.2.1).

Package

gsll.

Source

qr.lisp.

Function: qr-qrsolve (q r b &optional x)

Solves the system R x = Q^T b for x. It can
be used when the QR decomposition of a matrix is available in unpacked form as Q, R).

Package

gsll.

Source

qr.lisp.

Function: qr-qtvector (qr tau v)

Apply the matrix Q^T encoded in the decomposition
(QR, tau) to the vector v, storing the result Q^T v in v.
The matrix multiplication is carried out directly using
the encoding of the Householder vectors without needing to form the full matrix Q^T.

Package

gsll.

Source

qr.lisp.

Function: qr-qvector (qr tau v)

Apply the matrix Q encoded in the decomposition
(QR, tau) to the vector v, storing the result Q v in v.
The matrix multiplication is carried out directly using
the encoding of the Householder vectors without needing to form the full matrix Q.

Package

gsll.

Source

qr.lisp.

Function: qr-rsolve (qr b &optional x-spec)

Solve the triangular system R x = b for x. It may be useful if the product b’ = Q^T b has already been computed using QR-QTvec. If
x-spec is NIL (default), the solution will replace b. If x-spec is
T, then an array will be created and the solution returned in it.
If x-spec is a grid:foreign-array, the solution will be returned in it. If x-spec is non-NIL, on output the solution is stored in x and b is
not modified. The solution is returned from the function call.

Package

gsll.

Source

qr.lisp.

Function: qr-solve (qr tau b &optional x-spec)

Solve the square system A x = b using the QR decomposition of A
into (QR, tau) given by QR-decomp. The least-squares solution for rectangular systems can be found using QR-lssolve. If x-spec is
NIL (default), the solution will replace b. If x-spec is T, then
an array will be created and the solution returned in it. If
x-spec is a grid:foreign-array, the solution will be returned in it. If x-spec is non-NIL, on output the solution is stored in x and b is not
modified. The solution is returned from the function call.

Package

gsll.

Source

qr.lisp.

Function: qr-solve-least-squares (qr tau b &optional x residual)

The least squares solution to the overdetermined system A x = b where the matrix A has more rows than columns. The least squares solution minimizes the Euclidean norm of the residual, ||Ax - b||.The routine uses the QR decomposition of A into (QR, tau) given by #’QR-decomposition. The solution is returned in x. The residual is computed as a by-product and stored in residual.

Package

gsll.

Source

qr.lisp.

Function: qr-unpack (qr tau &optional q r)

Unpack the encoded QR decomposition (QR, tau) into the matrices Q and R where Q is M-by-M and R is M-by-N.

Package

gsll.

Source

qr.lisp.

Function: qr-update (q r w v)

Perform a rank-1 update w v^T of the QR
decomposition (Q, R). The update is given by Q’R’ = Q R + w v^T where the output matrices Q’ and R’ are also
orthogonal and right triangular. Note that w is destroyed by the update.

Package

gsll.

Source

qr.lisp.

Function: qrng-get (generator return-vector)

Store the next point from the sequence generator q
in the array. The space available for it must match the dimension of the generator. The point will lie in the range 0 < x_i < 1 for each x_i.

Package

gsll.

Source

quasi.lisp.

Function: qrpt-decomposition (a &optional tau permutation norm)

Factorizes the M-by-N matrix A into
the QRP^T decomposition A = Q R P^T. On output the
diagonal and upper triangular part of the input matrix contain the
matrix R. The permutation matrix P is stored in the
permutation. The sign of the permutation is given by
signum. It has the value (-1)^n, where n is the
number of interchanges in the permutation. The vector tau and the
columns of the lower triangular part of the matrix A contain the Householder coefficients and vectors which encode the orthogonal matrix Q. The vector tau must be of length k=min(M,N). The
matrix Q is related to these components by, Q = Q_k ... Q_2 Q_1
where Q_i = I - tau_i v_i v_i^T and v_i is the Householder vector
v_i = (0,...,1,A(i+1,i),A(i+2,i),...,A(m,i)). This is the same storage scheme as used by lapack. The vector norm is a workspace of length
N used for column pivoting.

The algorithm used to perform the decomposition is Householder QR with column pivoting (Golub & Van Loan, Matrix Computations, Algorithm 5.4.1).

Package

gsll.

Source

qrpt.lisp.

Function: qrpt-decomposition* (a &optional q r tau permutation norm)

Factorize the matrix A into the decomposition
A = Q R P^T without modifying A itself and storing the output in the separate matrices q and r.

Package

gsll.

Source

qrpt.lisp.

Function: qrpt-qrsolve (q r permutation b &optional x)

Solve the square system R P^T x = Q^T b for
x. It can be used when the QR decomposition of a matrix is available in unpacked form as (Q, R).

Package

gsll.

Source

qrpt.lisp.

Function: qrpt-rsolve (qr permutation b &optional x-spec)

Solve the triangular system R P^T x = b in-place for the N-by-N
matrix R contained in QR. On input x should contain the right-hand side b, which is replaced by the solution on output. If x-spec is NIL (default), the solution will replace b. If x-spec is T, then an array will be created and the solution returned in it. If x-spec is a grid:foreign-array, the solution will be returned in it. If x-spec is non-NIL, on output the solution is stored in x and b is not modified. The solution is returned from the function call.

Package

gsll.

Source

qrpt.lisp.

Function: qrpt-solve (qr tau permutation b &optional x-spec)

Solve the square system A x = b using the QRP^T decomposition of A
into (QR, tau, permutation) given by #’QRPT-decomposition. If x-spec is NIL (default), the solution will replace b. If x-spec is T, then
an array will be created and the solution returned in it. If
x-spec is a grid:foreign-array, the solution will be returned in it. If x-spec is non-NIL, on output the solution is stored in x and b is not
modified. The solution is returned from the function call.

Package

gsll.

Source

qrpt.lisp.

Function: qrpt-update (q r permutation w v)

Perform a rank-1 update w v^T of the QRP^T
decomposition (Q, R, p). The update is given by
Q’R’ = Q R + w v^T where the output matrices Q’ and
R’ are also orthogonal and right triangular. Note that w is destroyed by the update. The permutation is not changed.

Package

gsll.

Source

qrpt.lisp.

Function: r-solve (r b &optional x-spec)

Solve the triangular system R x = b in-place. On input x should contain the right-hand side b, which is replaced by the solution on output. If x-spec is NIL (default), the solution will replace b.
If x-spec is T, then an array will be created and the solution returned in it. If x-spec is a grid:foreign-array, the solution will be returned in it. If x-spec is non-NIL, on output the solution is stored in x and b is not modified. The solution is returned from the function call.

Package

gsll.

Source

qr.lisp.

Function: rayleigh-p (x sigma)

The cumulative distribution function
P(x) for the Rayleigh distribution with scale parameter sigma.

Package

gsll.

Source

rayleigh.lisp.

Function: rayleigh-pdf (x sigma)

The probability density p(x) at x
for a Rayleigh distribution with scale parameter sigma, using the formula given for #’sample :rayleigh.

Package

gsll.

Source

rayleigh.lisp.

Function: rayleigh-pinv (p sigma)

The inverse cumulative distribution function P(x)} for the Rayleigh distribution with scale parameter sigma.

Package

gsll.

Source

rayleigh.lisp.

Function: rayleigh-q (x sigma)

The cumulative distribution function
Q(x) for the Rayleigh distribution with scale parameter sigma.

Package

gsll.

Source

rayleigh.lisp.

Function: rayleigh-qinv (q sigma)

The inverse cumulative distribution function Q(x) for the Rayleigh distribution with scale parameter sigma.

Package

gsll.

Source

rayleigh.lisp.

Function: rayleigh-tail-pdf (x a sigma)

The probability density p(x) at x
for a Rayleigh tail distribution with scale parameter sigma and lower limit a, using the formula given in #’sample :rayleigh-tail.

Package

gsll.

Source

rayleigh-tail.lisp.

Function: read-ntuple (ntuple)

Read the current row of the ntuple file and stores the value.

Package

gsll.

Source

ntuple.lisp.

Function: rectangular-to-polar (x y)

Convert the rectilinear coordinates (x, y) to polar coordinates (r, theta), such that x =
r cos(theta)}, y = r sin(theta). The argument theta lies in the range [-pi, pi].

Package

gsll.

Source

trigonometry.lisp.

Function: relative-pochammer (a x)

The relative Pochhammer symbol ((a)_x - 1)/x where (a)_x := Gamma(a + x)/Gamma(a)}.

Package

gsll.

Source

gamma.lisp.

Function: restrict-positive (theta)

Force the angle theta to lie in the range [0,2pi).

Package

gsll.

Source

trigonometry.lisp.

Function: restrict-symmetric (theta)

Force the angle theta to lie in the range (-pi,pi].

Package

gsll.

Source

trigonometry.lisp.

Function: rng-environment-setup ()

Read the environment variables GSL_RNG_TYPE and GSL_RNG_SEED and use their values to set the corresponding library variables *default-type* and *default-seed*

Package

gsll.

Source

rng-types.lisp.

Function: rng-max (rng-instance)

The largest value that #’get-random-number can return.

Package

gsll.

Source

generators.lisp.

Function: rng-min (rng-instance)

The smallest value that #’get-random-number
can return. Usually this value is zero. There are some generators with algorithms that cannot return zero, and for these generators the minimum value is 1.

Package

gsll.

Source

generators.lisp.

Function: root-test-delta (x1 x0 absolute-error relative-error)

Test for the convergence of the sequence ... x0, x1 with absolute error absolute-error and relative error relative-error. The test returns T if the following condition is achieved,
|x_1 - x_0| < epsabs + epsrel |x_1|
and returns NIL otherwise.

Package

gsll.

Source

roots-one.lisp.

Function: root-test-interval (lower upper absolute-error relative-error)

Test for the convergence of the interval [lower,upper]
with absolute error absolute-error and relative error relative-error. This returns T
if the following condition is achieved,
|a - b| < epsabs + epsrel min(|a|,|b|)
when the interval x = [a,b] does not include the origin. If the interval includes the origin then min(|a|,|b|) is replaced by
zero (which is the minimum value of |x| over the interval). This ensures that the relative error is accurately estimated for roots close to the origin.

This condition on the interval also implies that any estimate of the root r in the interval satisfies the same condition with respect
to the true root r^*, |r - r^*| < epsabs + epsrel r^*
assuming that the true root r^* is contained within the interval.

Package

gsll.

Source

roots-one.lisp.

Function: root-test-residual (f absolute-error)

Tests the residual value f against the absolute
error bound absolute-error. The test returns T if the following condition is achieved,
|f| < epsabs
and returns NIL otherwise. This criterion is suitable for situations where the precise location of the root, x, is unimportant provided a value can be found where the residual, |f(x)|, is small enough.

Package

gsll.

Source

roots-one.lisp.

Function: sample-k-hankel (hankel n)

The value of the n-th sample point in k-space, j_{nu,n+1}/X}.

Package

gsll.

Source

hankel.lisp.

Function: sample-x-hankel (hankel n)

The value of the n-th sample point in the unit interval, (j_{nu,n+1}/j_{nu,M}) X, which are the points where the function f(t) is assumed to be sampled.

Package

gsll.

Source

hankel.lisp.

Function: sdot (result alpha vec1 vec2)

Sum of a scalar and a dot product for single-floats.

Package

gsll.

Source

blas1.lisp.

Function: set-floating-point-modes (precision rounding exception-mask)

Set the IEEE 754 precision, rounding mode, and exception mask.

Package

gsll.

Source

ieee-modes.lisp.

Function: shi (x)

The integral Shi(x) = int_0^x dt sinh(t)/t.

Package

gsll.

Source

exponential-integrals.lisp.

Function: si (x)

The Sine integral Si(x) = int_0^x dt sin(t)/t.

Package

gsll.

Source

exponential-integrals.lisp.

Function: simulated-annealing (state-values n-tries iterations-fixed-t step-size k t-initial mu-t t-min generator state-maker-function energy-function step-function metric-function copy-function)

Perform a simulated annealing search through a given space. The space is specified by providing the functions energy-function and metric-function. The simulated annealing steps are generated using the random number generator and the function step-function. The starting configuration of the system should be given by state-values. The parameters n-tries, iterations-fixed-T, step-size, k, t-initial, mu-t, t-min control the run by providing the temperature schedule and other tunable parameters to the algorithm. On exit the best result achieved during the search is returned. If the annealing process has been successful this should be a good approximation to the optimal point in the space. The simulated annealing routines require several user-specified functions to define the configuration space and energy function.

Package

gsll.

Source

simulated-annealing.lisp.

Function: sin-err (x dx)

Compute the sine of an angle x with
an associated absolute error dx, sin(x pm dx).

Package

gsll.

Source

trigonometry.lisp.

Function: sinc (x)

sinc(x) = sin(pi x) / (pi x)}

Package

gsll.

Source

trigonometry.lisp.

Function: solve-cubic (a b c)

Find the real roots of the cubic equation, x^3 + a x^2 + b x + c = 0 with a leading coefficient of unity. The roots are given
in ascending order. Three values are always returned;
if a root is not real, the value returned for it will be NIL.

Package

gsll.

Source

polynomial.lisp.

Function: solve-cubic-complex (a b c)

Find the complex roots of the cubic equation, x^3 + a x^2 + b x + c = 0 with a leading coefficient of unity. Three values are always returned; if a root does not exist, the value returned for it will be NIL.

Package

gsll.

Source

polynomial.lisp.

Function: solve-cyclic-tridiagonal (diag super-diag sub-diag b x)

Solve the general N-by-N system A x = b where A is cyclic tridiagonal (N >= 3). The cyclic super-diagonal and sub-diagonal vectors must have the same number of elements as the diagonal vector diag. The form of A for the 4-by-4 case is
A = ( d_0 e_0 0 f_3 )
( f_0 d_1 e_1 0 )
( 0 f_1 d_2 e_2 )
( e_3 0 f_2 d_3 ).

Package

gsll.

Source

diagonal.lisp.

Function: solve-quadratic (a b c)

The real roots of the quadratic equation a x^2 + b x + c = 0. Two values are always returned; if the roots are not real, these values are NIL.

Package

gsll.

Source

polynomial.lisp.

Function: solve-quadratic-complex (a b c)

The complex roots of the quadratic equation a x^2 + b x + c = 0. Two values are always returned; if a root does not exist, the value returned will be NIL.

Package

gsll.

Source

polynomial.lisp.

Function: solve-symmetric-cyclic-tridiagonal (diag off-diagonal b x)

Solve the general N-by-N system A x = b where A is symmetric cyclic tridiagonal (N >= 3). The cyclic
off-diagonal vector must have the same number of elements as the diagonal vector diag. The form of A for the 4-by-4 case is shown below,
A = ( d_0 e_0 0 e_3 )
( e_0 d_1 e_1 0 )
( 0 e_1 d_2 e_2 )
( e_3 0 e_2 d_3 )

Package

gsll.

Source

diagonal.lisp.

Function: solve-symmetric-tridiagonal (diag off-diagonal b x)

Solve the general N-by-N system A x = b where A is symmetric tridiagonal (N >= 2). The off-diagonal vector must be one element shorter than the diagonal vector diag. The form of A for the 4-by-4 case is
A = ( d_0 e_0 0 0 )
( e_0 d_1 e_1 0 )
( 0 e_1 d_2 e_2 )
( 0 0 e_2 d_3 ).

Package

gsll.

Source

diagonal.lisp.

Function: solve-tridiagonal (diag superdiag subdiag b x)

Solve the general N-by-N system A x = b where A is tridiagonal (N >= 2). The super-diagonal and
sub-diagonal vectors must be one element shorter
than the diagonal vector diag. The form of A for the 4-by-4 case is
A = ( d_0 e_0 0 0 )
( f_0 d_1 e_1 0 )
( 0 f_1 d_2 e_2 )
( 0 0 f_2 d_3 ).

Package

gsll.

Source

diagonal.lisp.

Function: spherical-bessel-i0-scaled (x)

The scaled regular modified spherical Bessel function of zeroth order, exp(-|x|) i_0(x).

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-i1-scaled (x)

The scaled regular modified spherical Bessel function of first order, exp(-|x|) i_1(x).

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-i2-scaled (x)

The scaled regular modified spherical Bessel function of second order, exp(-|x|) i_2(x).

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-il-scaled (n x)

The scaled regular modified spherical Bessel function of order l, exp(-|x|) i_l(x).

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-il-scaled-array (x &optional size-or-array)

The values of the scaled regular modified cylindrical Bessel
functions exp(-|x|) i_l(x) for l from 0 to length(array)-1 inclusive. The values are computed using recurrence relations
for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-j0 (x)

The regular spherical Bessel function of zeroth order, j_0(x) = sin(x)/x.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-j1 (x)

The regular spherical Bessel function of first order, j_1(x) = (sin(x)/x - cos(x))/x.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-j2 (x)

The regular spherical Bessel function of second order, j_2(x) = ((3/x^2 - 1)sin(x) - 3cos(x)/x)/x.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-jl (l x)

The regular spherical Bessel function of order l, j_l(x), for l >= 0 and x >= 0.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-jl-array (x &optional size-or-array)

The values of the regular spherical Bessel
functions j_l(x) for l from 0 to length(array)-1 and x >= 0.
The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-jl-steed-array (x &optional size-or-array)

Uses Steed’s method to compute the values of the regular spherical Bessel functions j_l(x) for l from 0 to length(array)-1 inclusive for x >= 0. The Steed/Barnett algorithm is described in Comp. Phys. Comm. 21, 297 (1981). Steed’s method is more stable than the recurrence used in the other functions but is also slower.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-k0-scaled (x)

The scaled irregular modified spherical Bessel function of zeroth order, exp(x) k_0(x), for x>0.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-k1-scaled (x)

The scaled irregular modified spherical Bessel function of first order, exp(x) k_1(x), for x>0.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-k2-scaled (x)

The scaled irregular modified spherical Bessel function of second order, exp(x) k_2(x), for x>0.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-kl-scaled (n x)

The scaled irregular modified spherical Bessel function of order l, exp(x) k_l(x), for x>0.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-kl-scaled-array (x &optional size-or-array)

The values of the scaled irregular modified spherical Bessel functions exp(x) k_l(x) for l from 0 to length(array)-1 inclusive x>0. The values are computed using recurrence relations for efficiency, and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-y0 (x)

The irregular spherical Bessel function of zeroth order, y_0(x) = -cos(x)/x.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-y1 (x)

The irregular spherical Bessel function of first order, y_1(x) = -(cos(x)/x + sin(x))/x.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-y2 (x)

The irregular spherical Bessel function of second order, y_2(x) = (-3/x^3 + 1/x)cos(x) - (3/x^2)sin(x).

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-yl (l x)

The irregular spherical Bessel function of order l, y_l(x), for l >= 0.

Package

gsll.

Source

bessel.lisp.

Function: spherical-bessel-yl-array (x &optional size-or-array)

The irregular spherical Bessel functions y_l(x) for l from 0 to length(array)-1. The values are computed using recurrence relations for efficiency,
and therefore may differ slightly from the exact values.

Package

gsll.

Source

bessel.lisp.

Function: step-order (stepper)

The order of the stepping function on the previous
step, which can vary if the stepping function itself is adaptive.

Package

gsll.

Source

stepping.lisp.

Function: sv-decomposition (a &optional s v work)

Factorize the M-by-N matrix A into
the singular value decomposition A = U S V^T for M >= N.
On output the matrix A is replaced by U. The diagonal elements of the singular value matrix S
are stored in the vector S. The singular values are non-negative and form a non-increasing sequence from S_1 to S_N. The matrix V contains the elements of V in untransposed
form. To form the product U S V^T it is necessary to take the transpose of V. A workspace of length N is required in work. This routine uses the Golub-Reinsch SVD algorithm.

Package

gsll.

Source

svd.lisp.

Function: sv-jacobi-decomposition (a &optional s v)

The SVD of the M-by-N matrix A using one-sided Jacobi orthogonalization for M >= N. The Jacobi method can compute singular values to higher relative accuracy than Golub-Reinsch algorithms (see references for details).

Package

gsll.

Source

svd.lisp.

Function: sv-modified-decomposition (a &optional s v x work)

The SVD using the modified Golub-Reinsch algorithm, which is faster for M >> N. It requires the vector work of length N and the N-by-N matrix X as additional working space.

Package

gsll.

Source

svd.lisp.

Function: sv-solve (u s v b &optional x)

Solve the system A x = b using the singular value
decomposition (U, S, V) of A given by #’SV-decomposition.

Only non-zero singular values are used in computing the solution. The parts of the solution corresponding to singular values of zero are ignored. Other singular values can be edited out by setting them to zero before calling this function.

In the over-determined case where A has more rows than columns the system is solved in the least squares sense, returning the solution x which minimizes ||A x - b||_2.

Package

gsll.

Source

svd.lisp.

Function: synchrotron-1 (x)

The first synchrotron function x int_x^infty dt K_{5/3}(t)} for x >= 0.

Package

gsll.

Source

synchrotron.lisp.

Function: synchrotron-2 (x)

The second synchrotron function x K_{2/3}(x)} for x >= 0.

Package

gsll.

Source

synchrotron.lisp.

Function: taylor-coefficient (n x)

Compute the Taylor coefficient x^n / n! for x >= 0, n >= 0.

Package

gsll.

Source

gamma.lisp.

Function: taylor-divided-difference (xp dd xa &optional coefficients workspace)

Convert the divided-difference representation of a
polynomial to a Taylor expansion. The divided-difference representation is supplied in the arrays dd and xa of the same length.
On output the Taylor coefficients of the polynomial expanded about the point xp are stored in the array coefficients which has the same length as xa and dd.

Package

gsll.

Source

polynomial.lisp.

Function: tdist-p (x nu)

The cumulative distribution functions
P(x) for the tdist distribution with nu degrees of freedom.

Package

gsll.

Source

tdist.lisp.

Function: tdist-pdf (x nu)

The probability density p(x) at x
for a t-distribution with nu degrees of freedom, using the formula given in #’sample :tdist.

Package

gsll.

Source

tdist.lisp.

Function: tdist-pinv (p nu)

The inverse cumulative distribution functions
P(x) for the tdist distribution with nu degrees of freedom.

Package

gsll.

Source

tdist.lisp.

Function: tdist-q (x nu)

The cumulative distribution functions
Q(x) for the tdist distribution with nu degrees of freedom.

Package

gsll.

Source

tdist.lisp.

Function: tdist-qinv (q nu)

The inverse cumulative distribution functions
Q(x) for the tdist distribution with nu degrees of freedom.

Package

gsll.

Source

tdist.lisp.

Function: transport-2 (x)

The transport function J(2,x).

Package

gsll.

Source

transport.lisp.

Function: transport-3 (x)

The transport function J(3,x).

Package

gsll.

Source

transport.lisp.

Function: transport-4 (x)

The transport function J(4,x).

Package

gsll.

Source

transport.lisp.

Function: transport-5 (x)

The transport function J(5,x).

Package

gsll.

Source

transport.lisp.

Function: ugaussian-p (x)

The cumulative distribution function P(x) for the Gaussian distribution with unit standard deviation.

Package

gsll.

Source

gaussian.lisp.

Function: ugaussian-pdf (x)

Compute results for the unit Gaussian distribution,
equivalent to the #’gaussian-pdf with a standard deviation of one, sigma = 1.

Package

gsll.

Source

gaussian.lisp.

Function: ugaussian-pinv (p)

The inverse cumulative distribution function P(x) for the Gaussian distribution with unit standard deviation.

Package

gsll.

Source

gaussian.lisp.

Function: ugaussian-q (x)

The cumulative distribution function Q(x) for the Gaussian distribution with unit standard deviation.

Package

gsll.

Source

gaussian.lisp.

Function: ugaussian-qinv (q)

The inverse cumulative distribution function Q(x) for the Gaussian distribution with unit standard deviation.

Package

gsll.

Source

gaussian.lisp.

Function: ugaussian-tail-pdf (x a)

Equivalent to gaussian-tail-pdf with sigma=1.

Package

gsll.

Source

gaussian-tail.lisp.

Function: uniform-knots (a b workspace)

Compute knots uniformly on the interval [a, b] and store them in the workspace.

Package

gsll.

Source

basis-splines.lisp.

Function: unpack (vector &rest args &key stride unpack-type &allow-other-keys)
Package

gsll.

Source

unpack.lisp.

Function: wavelet-2d-nonstandard-transform (wavelet data tda direction workspace)

Compute the two-dimensional wavelet transform in non-standard form.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-nonstandard-transform-forward (wavelet data tda workspace)

Compute the two-dimensional wavelet transform in non-standard form.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-nonstandard-transform-inverse (wavelet data tda workspace)

Compute the two-dimensional wavelet transform in non-standard form.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-nonstandard-transform-matrix (wavelet data direction workspace)

Compute the non-standard form of the two-dimensional in-place wavelet transform on a matrix.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-nonstandard-transform-matrix-forward (wavelet data workspace)

Compute the non-standard form of the two-dimensional in-place wavelet transform on a matrix.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-nonstandard-transform-matrix-inverse (wavelet data workspace)

Compute the non-standard form of the two-dimensional in-place wavelet transform on a matrix.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-transform (wavelet data tda direction workspace)

Compute in-place forward and inverse discrete wavelet transforms
in standard and non-standard forms on the
array data stored in row-major form with dimensions
and physical row length tda. The dimensions must
be equal (square matrix) and are restricted to powers of two. For the transform version of the function the argument direction can be either :forward or :backward. A
workspace of the appropriate size must be provided. On exit,
the appropriate elements of the array data are replaced by their two-dimensional wavelet transform.
An error invalid-argument is signalled if the matrix is not square with dimension a power of 2, or if insufficient
workspace is provided.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-transform-forward (wavelet data tda workspace)

Compute two-dimensional in-place forward and inverse
discrete wavelet transforms in standard and non-standard forms on the array data stored in row-major form with dimensions size1
and size2 and physical row length tda. The dimensions must
be equal (square matrix) and are restricted to powers of two. A workspace of the appropriate size must be provided. On exit,
the appropriate elements of the array data are replaced by their two-dimensional wavelet transform.
An error invalid-argument is signalled if the matrix is not square with dimension a power of 2, or if insufficient
workspace is provided.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-transform-inverse (wavelet data tda workspace)

Compute two-dimensional in-place forward and inverse discrete
wavelet transforms in standard and non-standard forms on the array
data stored in row-major form with dimensions size1 and size2 and
physical row length tda. The dimensions must be equal (square matrix)
and are restricted to powers of two. A workspace of the appropriate
size must be provided. On exit, the appropriate elements of the array data are replaced by their two-dimensional wavelet transform. An
error invalid-argument is signalled if the matrix is not square with dimension a power of 2, or if insufficient workspace is provided.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-transform-matrix (wavelet data direction workspace)

Compute the two-dimensional in-place wavelet transform on a matrix.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-transform-matrix-forward (wavelet data workspace)

Compute the two-dimensional in-place wavelet transform on a matrix.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-2d-transform-matrix-inverse (wavelet data workspace)

Compute the two-dimensional in-place wavelet transform on a matrix.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-transform (wavelet data stride direction workspace)

Compute in-place forward and inverse discrete wavelet
transforms on the array data. The length of the
transform n is restricted to powers
of two. For the transform version of the function the argument
dir can be either :forward or :backward. A workspace
of the same length as data must be provided.
For the forward transform, the elements of the original array are
replaced by the discrete wavelet
transform f_i -> w_{j,k}
in a packed triangular storage layout,
where j is the index of the level j = 0 ... J-1
and k is the index of the coefficient within each level,
k = 0 ... (2^j)-1. The total number of levels is J = log_2(n).
The output data has the following form,
(s_{-1,0}, d_{0,0}, d_{1,0}, d_{1,1}, d_{2,0},cdots, d_{j,k},cdots, d_{J-1,2^{J-1} - 1}) where the first element is the smoothing coefficient
s_{-1,0}, followed by the detail coefficients d_{j,k} for each level j.
The backward transform inverts these coefficients to obtain
the original data.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-transform-forward (wavelet data stride workspace)

Compute in-place forward and inverse discrete wavelet
transforms on the array data. The length of the transform
is restricted to powers of two.
A workspace of the same length as data must be provided.
For the forward transform, the elements of the original array are
replaced by the discrete wavelet transform
f_i -> w_{j,k} in a packed triangular storage layout,
where j is the index of the level j = 0 ... J-1
and k is the index of the coefficient within each level,
k = 0 ... (2^j)-1. The total number of levels is J = log_2(n).
The output data has the following form,
(s_{-1,0}, d_{0,0}, d_{1,0}, d_{1,1}, d_{2,0},cdots, d_{j,k},cdots, d_{J-1,2^{J-1} - 1}) where the first element is the smoothing coefficient s_{-1,0},
followed by the detail coefficients d_{j,k} for each level j.
The backward transform inverts these coefficients to obtain
the original data.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-transform-inverse (wavelet data stride workspace)

Compute in-place inverse discrete wavelet
transforms on the array data. The length of the transform
is restricted to powers of two.
A workspace of the same length as data must be provided.
For the forward transform, the elements of the original array are
replaced by the discrete wavelet transform
f_i -> w_{j,k} in a packed triangular storage layout,
where j is the index of the level j = 0 ... J-1
and k is the index of the coefficient within each level,
k = 0 ... (2^j)-1. The total number of levels is J = log_2(n).
The output data has the following form,
(s_{-1,0}, d_{0,0}, d_{1,0}, d_{1,1}, d_{2,0},cdots, d_{j,k},cdots, d_{J-1,2^{J-1} - 1}) where the first element is the smoothing coefficient s_{-1,0},
followed by the detail coefficients d_{j,k} for each level j.
The backward transform inverts these coefficients to obtain
the original data.

Package

gsll.

Source

wavelet.lisp.

Function: weibull-p (x a b)

The cumulative distribution functions
P(x) for the Weibull distribution with scale a and exponent b.

Package

gsll.

Source

weibull.lisp.

Function: weibull-pdf (x a b)

The probability density p(x) at x
for a Weibull distribution with scale a and exponent b, using the formula given in #’sample :weibull.

Package

gsll.

Source

weibull.lisp.

Function: weibull-pinv (p a b)

The inverse cumulative distribution functions
P(x) for the Weibull distribution scale a and exponent b.

Package

gsll.

Source

weibull.lisp.

Function: weibull-q (x a b)

The cumulative distribution functions
Q(x) for the Weibull distribution with scale a and exponent b.

Package

gsll.

Source

weibull.lisp.

Function: weibull-qinv (q a b)

The inverse cumulative distribution functions
Q(x) for the Weibull distribution exponent a and scale b.

Package

gsll.

Source

weibull.lisp.

Function: write-ntuple (ntuple)

Write the current ntuple ntuple->ntuple_data of size ntuple->size to the corresponding file.

Package

gsll.

Source

ntuple.lisp.


5.1.7 Generic functions

Generic Function: absolute-deviation (data &optional mean)

The absolute deviation from the mean of data. The absolute deviation from the mean is defined as absdev = (1/N) sum |x_i - Hatmu| where x_i are the elements of the dataset data. The absolute deviation from the mean provides a more robust measure of the width of a distribution than the variance. If ’mean is not supplied, this function computes the mean of data via a call to #’mean. With mean supplied, this function is useful if you have already computed the mean of data (and want to avoid recomputing it), or wish to calculate the absolute deviation relative to another value (such as zero, or the median).

Package

gsll.

Source

absolute-deviation.lisp.

Methods
Method: absolute-deviation ((data vector-single-float) &optional mean)
Method: absolute-deviation ((data vector-double-float) &optional mean)
Method: absolute-deviation ((data vector-signed-byte-8) &optional mean)
Method: absolute-deviation ((data vector-unsigned-byte-8) &optional mean)
Method: absolute-deviation ((data vector-signed-byte-16) &optional mean)
Method: absolute-deviation ((data vector-unsigned-byte-16) &optional mean)
Method: absolute-deviation ((data vector-signed-byte-32) &optional mean)
Method: absolute-deviation ((data vector-unsigned-byte-32) &optional mean)
Method: absolute-deviation ((data vector-signed-byte-64) &optional mean)
Method: absolute-deviation ((data vector-unsigned-byte-64) &optional mean)
Generic Function: absolute-sum (x)

The absolute sum sum |x_i| of the elements of the vector x.

Package

gsll.

Source

blas1.lisp.

Methods
Method: absolute-sum ((x vector-single-float))
Method: absolute-sum ((x vector-double-float))
Method: absolute-sum ((x vector-complex-single-float))
Method: absolute-sum ((x vector-complex-double-float))
Generic Function: autocorrelation (data &optional mean)

The lag-1 autocorrelation of the dataset data.
a_1 = {sum_{i = 1}^{n} (x_{i} - Hatmu) (x_{i-1} - Hatmu) over
sum_{i = 1}^{n} (x_{i} - Hatmu) (x_{i} - Hatmu)}.

Package

gsll.

Source

autocorrelation.lisp.

Methods
Method: autocorrelation ((data vector-single-float) &optional mean)
Method: autocorrelation ((data vector-double-float) &optional mean)
Method: autocorrelation ((data vector-signed-byte-8) &optional mean)
Method: autocorrelation ((data vector-unsigned-byte-8) &optional mean)
Method: autocorrelation ((data vector-signed-byte-16) &optional mean)
Method: autocorrelation ((data vector-unsigned-byte-16) &optional mean)
Method: autocorrelation ((data vector-signed-byte-32) &optional mean)
Method: autocorrelation ((data vector-unsigned-byte-32) &optional mean)
Method: autocorrelation ((data vector-signed-byte-64) &optional mean)
Method: autocorrelation ((data vector-unsigned-byte-64) &optional mean)
Generic Function: axpy (alpha x &optional y)

Compute the sum y = alpha x + y for the vectors x and y.

Package

gsll.

Source

blas1.lisp.

Methods
Method: axpy (alpha (x vector-single-float) &optional y)
Method: axpy (alpha (x vector-double-float) &optional y)
Method: axpy (alpha (x vector-complex-single-float) &optional y)
Method: axpy (alpha (x vector-complex-double-float) &optional y)
Generic Function: backward-discrete-fourier-transform (vector &key stride result)

Backward discrete Fourier transform provided to check the FFT routines.

Package

gsll.

Source

discrete.lisp.

Methods
Method: backward-discrete-fourier-transform ((vector vector-complex-single-float) &key stride result)
Method: backward-discrete-fourier-transform ((vector vector-complex-double-float) &key stride result)
Generic Function: blas-copy (x y)

Copy the elements of the vector x into the vector y.

Package

gsll.

Source

blas1.lisp.

Methods
Method: blas-copy ((x vector-single-float) (y vector-single-float))
Method: blas-copy ((x vector-double-float) (y vector-double-float))
Method: blas-copy ((x vector-complex-single-float) (y vector-complex-single-float))
Method: blas-copy ((x vector-complex-double-float) (y vector-complex-double-float))
Generic Function: blas-swap (vec1 vec2)

Exchange the elements of the vectors.

Package

gsll.

Source

blas1.lisp.

Methods
Method: blas-swap ((vec1 vector-single-float) (vec2 vector-single-float))
Method: blas-swap ((vec1 vector-double-float) (vec2 vector-double-float))
Method: blas-swap ((vec1 vector-complex-single-float) (vec2 vector-complex-single-float))
Method: blas-swap ((vec1 vector-complex-double-float) (vec2 vector-complex-double-float))
Generic Function: cdot (x y)

The complex conjugate scalar product x^H y for the vectors.

Package

gsll.

Source

blas1.lisp.

Methods
Method: cdot ((x vector-complex-single-float) (y vector-complex-single-float))
Method: cdot ((x vector-complex-double-float) (y vector-complex-double-float))
Generic Function: cholesky-decomposition (a)

Factorize the positive-definite square matrix A into the Cholesky decomposition A = L L^T (real) or A = L L^H (complex). On output the diagonal and lower triangular part of the input matrix A contain the matrix L. The upper triangular part of the input matrix contains L^T, the diagonal terms being identical for both L and L^T. If the matrix is not positive-definite then the decomposition will fail, returning the error input-domain.

Package

gsll.

Source

cholesky.lisp.

Methods
Method: cholesky-decomposition ((a matrix-double-float))
Method: cholesky-decomposition ((a matrix-complex-double-float))
Generic Function: cholesky-solve (a b &optional x-spec)

Solve the system A x = b using the Cholesky
decomposition of A into the matrix given by
#’cholesky-decomposition. If x-spec is NIL (default), the solution
will replace b. If x-spec is T, then an array will be created and the solution returned in it. If x-spec is a grid:foreign-array, the solution will be returned in it.

Package

gsll.

Source

cholesky.lisp.

Methods
Method: cholesky-solve ((a matrix-double-float) (b vector-double-float) &optional x-spec)
Method: cholesky-solve ((a matrix-complex-double-float) (b vector-complex-double-float) &optional x-spec)
Generic Function: column (matrix i &optional vector)

Copy the elements of the ith column of the matrix into the vector. The length of the vector must be the same as the length of the column.

Package

gsll.

Source

matrix.lisp.

Methods
Method: column ((matrix matrix-single-float) i &optional vector)
Method: column ((matrix matrix-double-float) i &optional vector)
Method: column ((matrix matrix-complex-single-float) i &optional vector)
Method: column ((matrix matrix-complex-double-float) i &optional vector)
Method: column ((matrix matrix-signed-byte-8) i &optional vector)
Method: column ((matrix matrix-unsigned-byte-8) i &optional vector)
Method: column ((matrix matrix-signed-byte-16) i &optional vector)
Method: column ((matrix matrix-unsigned-byte-16) i &optional vector)
Method: column ((matrix matrix-signed-byte-32) i &optional vector)
Method: column ((matrix matrix-unsigned-byte-32) i &optional vector)
Method: column ((matrix matrix-signed-byte-64) i &optional vector)
Method: column ((matrix matrix-unsigned-byte-64) i &optional vector)
Generic Function: (setf column) (matrix i)

Copy the elements of the vector into the ith column of the matrix. The length of the vector must be the same as the length of the column.

Package

gsll.

Source

matrix.lisp.

Methods
Method: (setf column) ((matrix matrix-single-float) i)
Method: (setf column) ((matrix matrix-double-float) i)
Method: (setf column) ((matrix matrix-complex-single-float) i)
Method: (setf column) ((matrix matrix-complex-double-float) i)
Method: (setf column) ((matrix matrix-signed-byte-8) i)
Method: (setf column) ((matrix matrix-unsigned-byte-8) i)
Method: (setf column) ((matrix matrix-signed-byte-16) i)
Method: (setf column) ((matrix matrix-unsigned-byte-16) i)
Method: (setf column) ((matrix matrix-signed-byte-32) i)
Method: (setf column) ((matrix matrix-unsigned-byte-32) i)
Method: (setf column) ((matrix matrix-signed-byte-64) i)
Method: (setf column) ((matrix matrix-unsigned-byte-64) i)
Generic Function: conjugate-rank-1-update (alpha x y a)

The conjugate rank-1 update A = alpha x y^H + A of the matrix A.

Package

gsll.

Source

blas2.lisp.

Methods
Method: conjugate-rank-1-update (alpha (x vector-complex-single-float) (y vector-complex-single-float) (a matrix-complex-single-float))
Method: conjugate-rank-1-update (alpha (x vector-complex-double-float) (y vector-complex-double-float) (a matrix-complex-double-float))
Generic Function: correlation (data1 data2)

Efficiently compute the Pearson correlation coefficient between the datasets data1 and data2 which must both be of the same length

Package

gsll.

Source

covariance.lisp.

Methods
Method: correlation ((data1 vector-single-float) (data2 vector-single-float))
Method: correlation ((data1 vector-double-float) (data2 vector-double-float))
Method: correlation ((data1 vector-signed-byte-8) (data2 vector-signed-byte-8))
Method: correlation ((data1 vector-unsigned-byte-8) (data2 vector-unsigned-byte-8))
Method: correlation ((data1 vector-signed-byte-16) (data2 vector-signed-byte-16))
Method: correlation ((data1 vector-unsigned-byte-16) (data2 vector-unsigned-byte-16))
Method: correlation ((data1 vector-signed-byte-32) (data2 vector-signed-byte-32))
Method: correlation ((data1 vector-unsigned-byte-32) (data2 vector-unsigned-byte-32))
Method: correlation ((data1 vector-signed-byte-64) (data2 vector-signed-byte-64))
Method: correlation ((data1 vector-unsigned-byte-64) (data2 vector-unsigned-byte-64))
Generic Function: covariance (data1 data2 &optional mean1 mean2)

The covariance of the datasets data1 and data2 which must be of the same length,
covar = {1 over (n - 1)} sum_{i = 1}^{n}
(x_{i} - Hat x) (y_{i} - Hat y).

Package

gsll.

Source

covariance.lisp.

Methods
Method: covariance ((data1 vector-single-float) (data2 vector-single-float) &optional mean1 mean2)
Method: covariance ((data1 vector-double-float) (data2 vector-double-float) &optional mean1 mean2)
Method: covariance ((data1 vector-signed-byte-8) (data2 vector-signed-byte-8) &optional mean1 mean2)
Method: covariance ((data1 vector-unsigned-byte-8) (data2 vector-unsigned-byte-8) &optional mean1 mean2)
Method: covariance ((data1 vector-signed-byte-16) (data2 vector-signed-byte-16) &optional mean1 mean2)
Method: covariance ((data1 vector-unsigned-byte-16) (data2 vector-unsigned-byte-16) &optional mean1 mean2)
Method: covariance ((data1 vector-signed-byte-32) (data2 vector-signed-byte-32) &optional mean1 mean2)
Method: covariance ((data1 vector-unsigned-byte-32) (data2 vector-unsigned-byte-32) &optional mean1 mean2)
Method: covariance ((data1 vector-signed-byte-64) (data2 vector-signed-byte-64) &optional mean1 mean2)
Method: covariance ((data1 vector-unsigned-byte-64) (data2 vector-unsigned-byte-64) &optional mean1 mean2)
Generic Function: cylindrical-bessel-i (order x)

The regular modified cylindrical Bessel function of order n, I_n(x).

Package

gsll.

Source

bessel.lisp.

Methods
Method: cylindrical-bessel-i ((nu float) x)

The regular modified Bessel function of fractional order nu, I_nu(x) for x>0, nu>0.

Method: cylindrical-bessel-i ((n integer) x)
Generic Function: cylindrical-bessel-i-scaled (order x)

The scaled regular modified cylindrical Bessel function of order n, exp(-|x|) I_n(x)}.

Package

gsll.

Source

bessel.lisp.

Methods
Method: cylindrical-bessel-i-scaled ((nu float) x)

The scaled regular modified Bessel function of fractional order nu, exp(-|x|)I_nu(x) for x>0, nu>0.

Method: cylindrical-bessel-i-scaled ((n integer) x)

The scaled regular modified cylindrical Bessel function of order n, exp(-|x|) I_n(x)}.

Generic Function: cylindrical-bessel-j (order x)

The regular cylindrical Bessel function of order n, J_n(x).

Package

gsll.

Source

bessel.lisp.

Methods
Method: cylindrical-bessel-j ((nu float) x)
Method: cylindrical-bessel-j ((n integer) x)
Generic Function: cylindrical-bessel-k (order x)

The irregular modified cylindrical Bessel function of order n, K_n(x).

Package

gsll.

Source

bessel.lisp.

Methods
Method: cylindrical-bessel-k ((nu float) x)

The irregular modified Bessel function of fractional order nu, K_nu(x) for x>0, nu>0.

Method: cylindrical-bessel-k ((n integer) x)
Generic Function: cylindrical-bessel-k-scaled (order x)

The scaled irregular modified cylindrical Bessel function of order n, exp(-|x|) K_n(x).

Package

gsll.

Source

bessel.lisp.

Methods
Method: cylindrical-bessel-k-scaled ((nu float) x)

The scaled irregular modified Bessel function of fractional order nu, exp(+|x|) K_nu(x) for x>0, nu>0.

Method: cylindrical-bessel-k-scaled ((n integer) x)
Generic Function: cylindrical-bessel-y (order x)

The irregular cylindrical Bessel function of order n, Y_n(x).

Package

gsll.

Source

bessel.lisp.

Methods
Method: cylindrical-bessel-y ((nu float) x)
Method: cylindrical-bessel-y ((n integer) x)

The irregular cylindrical Bessel function of order n, Y_n(x).

Generic Function: dilogarithm (x)

The dilogarithm.

Package

gsll.

Source

dilogarithm.lisp.

Methods
Method: dilogarithm ((x complex))
Method: dilogarithm ((x float))
Generic Function: discrete-fourier-transform (vector &key stride result)

Discrete Fourier transform in selectable direction provided to check the FFT routines.

Package

gsll.

Source

discrete.lisp.

Methods
Method: discrete-fourier-transform ((vector vector-complex-single-float) &key stride result)
Method: discrete-fourier-transform ((vector vector-complex-double-float) &key stride result)
Generic Function: eigenvalues (a &optional eigenvalues ws)

Eigenvalues of the real symmetric or complex hermitian matrix A. Additional workspace of the appropriate size and type must be provided in w. The diagonal and lower triangular part of A are destroyed during the computation, but the strict upper triangular part is not referenced. For the complex hermitian case, The imaginary parts of the diagonal are assumed to be zero and are not referenced. The eigenvalues are stored in the vector eigenvalues and are unordered.

Package

gsll.

Source

symmetric-hermitian.lisp.

Methods
Method: eigenvalues ((a matrix-double-float) &optional eigenvalues ws)
Method: eigenvalues ((a matrix-complex-double-float) &optional eigenvalues ws)
Generic Function: eigenvalues-eigenvectors (a &optional eigenvalues eigenvectors ws)

The eigenvalues and eigenvectors of the real symmetric or complex hermitian matrix A. Additional workspace of the appropriate size must be provided in w. The diagonal and lower triangular part of A are destroyed during the computation, but the strict upper triangular part is not referenced. For complex hermitian matrices, the imaginary parts of the diagonal are assumed to be zero and are not referenced. The eigenvalues are stored in the vector eigenvalues and are unordered. The corresponding eigenvectors are stored in the columns of the matrix eigenvectors. For example, the eigenvector in the first column corresponds to the first eigenvalue. The eigenvectors are guaranteed to be mutually orthogonal and normalised to unit magnitude.

Package

gsll.

Source

symmetric-hermitian.lisp.

Methods
Method: eigenvalues-eigenvectors ((a matrix-double-float) &optional eigenvalues eigenvectors ws)
Method: eigenvalues-eigenvectors ((a matrix-complex-double-float) &optional eigenvalues eigenvectors ws)
Generic Function: eigenvalues-eigenvectors-gensymm (a b &optional eigenvalues eigenvectors ws)

Computes the eigenvalues and eigenvectors of the real generalized symmetric-definite matrix pair (A, B), and stores them in eval and evec respectively. The computed eigenvectors are normalized to have unit magnitude. On output, B contains its Cholesky decomposition and A is destroyed.

Package

gsll.

Source

generalized.lisp.

Methods
Method: eigenvalues-eigenvectors-gensymm ((a matrix-double-float) (b matrix-double-float) &optional eigenvalues eigenvectors ws)
Method: eigenvalues-eigenvectors-gensymm ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional eigenvalues eigenvectors ws)
Generic Function: eigenvalues-gensymm (a b &optional eigenvalues ws)

Compute the eigenvalues of the real generalized symmetric-definite matrix pair (A, B), and stores them in eval, using the method outlined above. On output, B contains its Cholesky decomposition and A is destroyed.

Package

gsll.

Source

generalized.lisp.

Methods
Method: eigenvalues-gensymm ((a matrix-double-float) (b matrix-double-float) &optional eigenvalues ws)
Method: eigenvalues-gensymm ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional eigenvalues ws)
Generic Function: elt* (a b)

Multiply the elements of a by the elements of b. The two must have the same dimensions.

Package

gsll.

Source

both.lisp.

Methods
Method: elt* ((histogram histogram2d) scale)

Multiply the contents of the bins of histogram by the constant scale, i.e. h’_1(i) = h_1(i) * scale.

Source

operations.lisp.

Method: elt* ((histogram histogram) scale)

Multiply the contents of the bins of histogram by the constant scale, i.e. h’_1(i) = h_1(i) * scale.

Source

operations.lisp.

Method: elt* ((histogram1 histogram2d) (histogram2 histogram2d))

Multiply the contents of the bins of histogram1 by the contents of the corresponding bins in histogram2 i.e. h’_1(i) = h_1(i) * h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt* ((histogram1 histogram) (histogram2 histogram))

Multiply the contents of the bins of histogram1 by the contents of the corresponding bins in histogram2 i.e. h’_1(i) = h_1(i) * h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt* ((x float) (a foreign-array))
Method: elt* ((a matrix-complex-double-float) (x complex))
Method: elt* ((a matrix-complex-single-float) (x complex))
Method: elt* ((a vector-complex-double-float) (x complex))
Method: elt* ((a vector-complex-single-float) (x complex))
Method: elt* ((a matrix-unsigned-byte-64) (x float))
Method: elt* ((a matrix-signed-byte-64) (x float))
Method: elt* ((a matrix-unsigned-byte-32) (x float))
Method: elt* ((a matrix-signed-byte-32) (x float))
Method: elt* ((a matrix-unsigned-byte-16) (x float))
Method: elt* ((a matrix-signed-byte-16) (x float))
Method: elt* ((a matrix-unsigned-byte-8) (x float))
Method: elt* ((a matrix-signed-byte-8) (x float))
Method: elt* ((a matrix-double-float) (x float))
Method: elt* ((a matrix-single-float) (x float))
Method: elt* ((a vector-unsigned-byte-64) (x float))
Method: elt* ((a vector-signed-byte-64) (x float))
Method: elt* ((a vector-unsigned-byte-32) (x float))
Method: elt* ((a vector-signed-byte-32) (x float))
Method: elt* ((a vector-unsigned-byte-16) (x float))
Method: elt* ((a vector-signed-byte-16) (x float))
Method: elt* ((a vector-unsigned-byte-8) (x float))
Method: elt* ((a vector-signed-byte-8) (x float))
Method: elt* ((a vector-double-float) (x float))
Method: elt* ((a vector-single-float) (x float))
Method: elt* ((a matrix-unsigned-byte-64) (b matrix-unsigned-byte-64))
Method: elt* ((a matrix-signed-byte-64) (b matrix-signed-byte-64))
Method: elt* ((a matrix-unsigned-byte-32) (b matrix-unsigned-byte-32))
Method: elt* ((a matrix-signed-byte-32) (b matrix-signed-byte-32))
Method: elt* ((a matrix-unsigned-byte-16) (b matrix-unsigned-byte-16))
Method: elt* ((a matrix-signed-byte-16) (b matrix-signed-byte-16))
Method: elt* ((a matrix-unsigned-byte-8) (b matrix-unsigned-byte-8))
Method: elt* ((a matrix-signed-byte-8) (b matrix-signed-byte-8))
Method: elt* ((a matrix-double-float) (b matrix-double-float))
Method: elt* ((a matrix-single-float) (b matrix-single-float))
Method: elt* ((a vector-single-float) (b vector-single-float))
Method: elt* ((a vector-double-float) (b vector-double-float))
Method: elt* ((a vector-complex-single-float) (b vector-complex-single-float))
Method: elt* ((a vector-complex-double-float) (b vector-complex-double-float))
Method: elt* ((a vector-signed-byte-8) (b vector-signed-byte-8))
Method: elt* ((a vector-unsigned-byte-8) (b vector-unsigned-byte-8))
Method: elt* ((a vector-signed-byte-16) (b vector-signed-byte-16))
Method: elt* ((a vector-unsigned-byte-16) (b vector-unsigned-byte-16))
Method: elt* ((a vector-signed-byte-32) (b vector-signed-byte-32))
Method: elt* ((a vector-unsigned-byte-32) (b vector-unsigned-byte-32))
Method: elt* ((a vector-signed-byte-64) (b vector-signed-byte-64))
Method: elt* ((a vector-unsigned-byte-64) (b vector-unsigned-byte-64))
Generic Function: elt+ (a b)

Add the elements of b to the elements of vector a The two must have the same dimensions.

Package

gsll.

Source

both.lisp.

Methods
Method: elt+ ((histogram1 histogram2d) (histogram2 histogram2d))

Add the contents of the bins in histogram2 to the corresponding bins of histogram1 i.e. h’_1(i) =
h_1(i) + h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt+ ((histogram1 histogram) (histogram2 histogram))

Add the contents of the bins in histogram2 to the corresponding bins of histogram1 i.e. h’_1(i) =
h_1(i) + h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt+ ((x float) (a foreign-array))
Method: elt+ ((a matrix-complex-double-float) (x complex))
Method: elt+ ((a matrix-complex-single-float) (x complex))
Method: elt+ ((a vector-complex-double-float) (x complex))
Method: elt+ ((a vector-complex-single-float) (x complex))
Method: elt+ ((a matrix-unsigned-byte-64) (x float))
Method: elt+ ((a matrix-signed-byte-64) (x float))
Method: elt+ ((a matrix-unsigned-byte-32) (x float))
Method: elt+ ((a matrix-signed-byte-32) (x float))
Method: elt+ ((a matrix-unsigned-byte-16) (x float))
Method: elt+ ((a matrix-signed-byte-16) (x float))
Method: elt+ ((a matrix-unsigned-byte-8) (x float))
Method: elt+ ((a matrix-signed-byte-8) (x float))
Method: elt+ ((a matrix-double-float) (x float))
Method: elt+ ((a matrix-single-float) (x float))
Method: elt+ ((a vector-unsigned-byte-64) (x float))
Method: elt+ ((a vector-signed-byte-64) (x float))
Method: elt+ ((a vector-unsigned-byte-32) (x float))
Method: elt+ ((a vector-signed-byte-32) (x float))
Method: elt+ ((a vector-unsigned-byte-16) (x float))
Method: elt+ ((a vector-signed-byte-16) (x float))
Method: elt+ ((a vector-unsigned-byte-8) (x float))
Method: elt+ ((a vector-signed-byte-8) (x float))
Method: elt+ ((a vector-double-float) (x float))
Method: elt+ ((a vector-single-float) (x float))
Method: elt+ ((a vector-single-float) (b vector-single-float))
Method: elt+ ((a vector-double-float) (b vector-double-float))
Method: elt+ ((a vector-complex-single-float) (b vector-complex-single-float))
Method: elt+ ((a vector-complex-double-float) (b vector-complex-double-float))
Method: elt+ ((a vector-signed-byte-8) (b vector-signed-byte-8))
Method: elt+ ((a vector-unsigned-byte-8) (b vector-unsigned-byte-8))
Method: elt+ ((a vector-signed-byte-16) (b vector-signed-byte-16))
Method: elt+ ((a vector-unsigned-byte-16) (b vector-unsigned-byte-16))
Method: elt+ ((a vector-signed-byte-32) (b vector-signed-byte-32))
Method: elt+ ((a vector-unsigned-byte-32) (b vector-unsigned-byte-32))
Method: elt+ ((a vector-signed-byte-64) (b vector-signed-byte-64))
Method: elt+ ((a vector-unsigned-byte-64) (b vector-unsigned-byte-64))
Method: elt+ ((a matrix-single-float) (b matrix-single-float))
Method: elt+ ((a matrix-double-float) (b matrix-double-float))
Method: elt+ ((a matrix-complex-single-float) (b matrix-complex-single-float))
Method: elt+ ((a matrix-complex-double-float) (b matrix-complex-double-float))
Method: elt+ ((a matrix-signed-byte-8) (b matrix-signed-byte-8))
Method: elt+ ((a matrix-unsigned-byte-8) (b matrix-unsigned-byte-8))
Method: elt+ ((a matrix-signed-byte-16) (b matrix-signed-byte-16))
Method: elt+ ((a matrix-unsigned-byte-16) (b matrix-unsigned-byte-16))
Method: elt+ ((a matrix-signed-byte-32) (b matrix-signed-byte-32))
Method: elt+ ((a matrix-unsigned-byte-32) (b matrix-unsigned-byte-32))
Method: elt+ ((a matrix-signed-byte-64) (b matrix-signed-byte-64))
Method: elt+ ((a matrix-unsigned-byte-64) (b matrix-unsigned-byte-64))
Generic Function: elt- (a b)

Subtract the elements of b from the elements of a. The two must have the same dimensions.

Package

gsll.

Source

both.lisp.

Methods
Method: elt- ((histogram1 histogram2d) (histogram2 histogram2d))

Subtract the contents of the bins in histogram2 from the corresponding bins of histogram1 i.e. h’_1(i) = h_1(i) - h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt- ((histogram1 histogram) (histogram2 histogram))

Subtract the contents of the bins in histogram2 from the corresponding bins of histogram1 i.e. h’_1(i) = h_1(i) - h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt- ((a foreign-array) (x float))
Method: elt- ((a vector-single-float) (b vector-single-float))
Method: elt- ((a vector-double-float) (b vector-double-float))
Method: elt- ((a vector-complex-single-float) (b vector-complex-single-float))
Method: elt- ((a vector-complex-double-float) (b vector-complex-double-float))
Method: elt- ((a vector-signed-byte-8) (b vector-signed-byte-8))
Method: elt- ((a vector-unsigned-byte-8) (b vector-unsigned-byte-8))
Method: elt- ((a vector-signed-byte-16) (b vector-signed-byte-16))
Method: elt- ((a vector-unsigned-byte-16) (b vector-unsigned-byte-16))
Method: elt- ((a vector-signed-byte-32) (b vector-signed-byte-32))
Method: elt- ((a vector-unsigned-byte-32) (b vector-unsigned-byte-32))
Method: elt- ((a vector-signed-byte-64) (b vector-signed-byte-64))
Method: elt- ((a vector-unsigned-byte-64) (b vector-unsigned-byte-64))
Method: elt- ((a matrix-single-float) (b matrix-single-float))
Method: elt- ((a matrix-double-float) (b matrix-double-float))
Method: elt- ((a matrix-complex-single-float) (b matrix-complex-single-float))
Method: elt- ((a matrix-complex-double-float) (b matrix-complex-double-float))
Method: elt- ((a matrix-signed-byte-8) (b matrix-signed-byte-8))
Method: elt- ((a matrix-unsigned-byte-8) (b matrix-unsigned-byte-8))
Method: elt- ((a matrix-signed-byte-16) (b matrix-signed-byte-16))
Method: elt- ((a matrix-unsigned-byte-16) (b matrix-unsigned-byte-16))
Method: elt- ((a matrix-signed-byte-32) (b matrix-signed-byte-32))
Method: elt- ((a matrix-unsigned-byte-32) (b matrix-unsigned-byte-32))
Method: elt- ((a matrix-signed-byte-64) (b matrix-signed-byte-64))
Method: elt- ((a matrix-unsigned-byte-64) (b matrix-unsigned-byte-64))
Generic Function: elt/ (a b)

Divide the elements of a by the elements of b. The two must have the same dimensions.

Package

gsll.

Source

both.lisp.

Methods
Method: elt/ ((histogram1 histogram2d) (histogram2 histogram2d))

Divide the contents of the bins of histogram1 by the contents of the corresponding bins in histogram2 i.e. h’_1(i) = h_1(i) / h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt/ ((histogram1 histogram) (histogram2 histogram))

Divide the contents of the bins of histogram1 by the contents of the corresponding bins in histogram2 i.e. h’_1(i) = h_1(i) / h_2(i). The two histograms must have identical bin ranges.

Source

operations.lisp.

Method: elt/ ((a foreign-array) (x number))
Method: elt/ ((a matrix-unsigned-byte-64) (b matrix-unsigned-byte-64))
Method: elt/ ((a matrix-signed-byte-64) (b matrix-signed-byte-64))
Method: elt/ ((a matrix-unsigned-byte-32) (b matrix-unsigned-byte-32))
Method: elt/ ((a matrix-signed-byte-32) (b matrix-signed-byte-32))
Method: elt/ ((a matrix-unsigned-byte-16) (b matrix-unsigned-byte-16))
Method: elt/ ((a matrix-signed-byte-16) (b matrix-signed-byte-16))
Method: elt/ ((a matrix-unsigned-byte-8) (b matrix-unsigned-byte-8))
Method: elt/ ((a matrix-signed-byte-8) (b matrix-signed-byte-8))
Method: elt/ ((a matrix-double-float) (b matrix-double-float))
Method: elt/ ((a matrix-single-float) (b matrix-single-float))
Method: elt/ ((a vector-single-float) (b vector-single-float))
Method: elt/ ((a vector-double-float) (b vector-double-float))
Method: elt/ ((a vector-complex-single-float) (b vector-complex-single-float))
Method: elt/ ((a vector-complex-double-float) (b vector-complex-double-float))
Method: elt/ ((a vector-signed-byte-8) (b vector-signed-byte-8))
Method: elt/ ((a vector-unsigned-byte-8) (b vector-unsigned-byte-8))
Method: elt/ ((a vector-signed-byte-16) (b vector-signed-byte-16))
Method: elt/ ((a vector-unsigned-byte-16) (b vector-unsigned-byte-16))
Method: elt/ ((a vector-signed-byte-32) (b vector-signed-byte-32))
Method: elt/ ((a vector-unsigned-byte-32) (b vector-unsigned-byte-32))
Method: elt/ ((a vector-signed-byte-64) (b vector-signed-byte-64))
Method: elt/ ((a vector-unsigned-byte-64) (b vector-unsigned-byte-64))
Generic Function: equal-bins-p (histogram1 histogram2)

Are all of the individual bin ranges of the two histograms are identical?

Package

gsll.

Source

operations.lisp.

Methods
Method: equal-bins-p ((histogram1 histogram2d) (histogram2 histogram2d))
Method: equal-bins-p ((histogram1 histogram) (histogram2 histogram))
Generic Function: euclidean-norm (vec)

The Euclidean norm ||x||_2 = sqrt {sum x_i^2} of the vector x.

Package

gsll.

Source

blas1.lisp.

Methods
Method: euclidean-norm ((vec vector-single-float))
Method: euclidean-norm ((vec vector-double-float))
Method: euclidean-norm ((vec vector-complex-single-float))
Method: euclidean-norm ((vec vector-complex-double-float))
Generic Function: evaluate (object point &key b order acceleration xa ya divided-difference &allow-other-keys)

Evaluate the GSL object.

Package

gsll.

Source

mobject.lisp.

Methods
Method: evaluate ((workspace basis-spline) x &key b)

Evaluate all B-spline basis functions at the position x and store them in the GSL vector B, so that the ith element of B is B_i(x). B must be of length n = nbreak + k - 2. This value is
also stored in the workspace. It is far more
efficient to compute all of the basis functions at once than to compute them individually, due to the nature of the defining recurrence relation.

Source

basis-splines.lisp.

Method: evaluate ((object chebyshev) x &key order)

Evaluate the Chebyshev series at a point x. If order is supplied, evaluate to at most the given order.

Source

chebyshev.lisp.

Method: evaluate ((spline spline) x &key acceleration)
Source

evaluation.lisp.

Method: evaluate ((interpolation interpolation) x &key xa ya acceleration)

Find the interpolated value of y for a given
point x, using the interpolation object interpolation, data arrays xa and ya and the accelerator acceleration.

Source

evaluation.lisp.

Method: evaluate ((coefficients vector-complex-double-float) (x complex) &key)

Evaluate the polyonomial with coefficients at the complex value x.

Source

polynomial.lisp.

Method: evaluate ((coefficients vector-double-float) (x complex) &key)

Evaluate the polyonomial with coefficients at the complex value x.

Source

polynomial.lisp.

Method: evaluate ((coefficients vector-double-float) (x float) &key divided-difference)

Evaluate the polyonomial with coefficients at the point x.

Source

polynomial.lisp.

Generic Function: evaluate-derivative (object point &key acceleration xa ya)

Find the derivative of an interpolated function for a given point x, using the interpolation object interpolation, data arrays xa and ya and the accelerator acceleration.

Package

gsll.

Source

evaluation.lisp.

Methods
Method: evaluate-derivative ((spline spline) x &key acceleration)
Method: evaluate-derivative ((interpolation interpolation) x &key xa ya acceleration)
Generic Function: evaluate-integral (object lower-limit upper-limit &key acceleration xa ya)

Find the numerical integral of an interpolated function over the range [low, high], using the interpolation object interpolation, data arrays xa and ya and the accelerator ’acceleration.

Package

gsll.

Source

evaluation.lisp.

Methods
Method: evaluate-integral ((spline spline) low high &key acceleration)
Method: evaluate-integral ((interpolation interpolation) low high &key xa ya acceleration)
Generic Function: evaluate-second-derivative (object point &key acceleration xa ya)

Find the second derivative of an interpolated function for a given point x, using the interpolation object interpolation, data arrays
xa and ya and the accelerator acceleration.

Package

gsll.

Source

evaluation.lisp.

Methods
Method: evaluate-second-derivative ((spline spline) x &key acceleration)
Method: evaluate-second-derivative ((interpolation interpolation) x &key xa ya acceleration)
Generic Function: forward-discrete-fourier-transform (vector &key stride result)

Forward discrete Fourier transform provided to check the FFT routines.

Package

gsll.

Source

discrete.lisp.

Methods
Method: forward-discrete-fourier-transform ((vector vector-complex-single-float) &key stride result)
Method: forward-discrete-fourier-transform ((vector vector-complex-double-float) &key stride result)
Generic Function: function-value (object)

The current value of the function that solves this object.

Package

gsll.

Source

generic.lisp.

Methods
Method: function-value ((solver nonlinear-fdffit))
Source

nonlinear-least-squares.lisp.

Method: function-value ((minimizer multi-dimensional-minimizer-fdf))

The current best estimate of the value of the minimum.

Source

minimization-multi.lisp.

Method: function-value ((minimizer multi-dimensional-minimizer-f))

The current best estimate of the value of the minimum.

Source

minimization-multi.lisp.

Method: function-value ((solver multi-dimensional-root-solver-fdf))

The function value f(x) at the current estimate x of the root for the solver.

Source

roots-multi.lisp.

Method: function-value ((solver multi-dimensional-root-solver-f))

The function value f(x) at the current estimate x of the root for the solver.

Source

roots-multi.lisp.

Method: function-value ((minimizer one-dimensional-minimizer))

The value of the function at the current estimate of the minimum for the minimizer.

Source

minimization-one.lisp.

Generic Function: givens-rotation (x y c s)

These functions compute a Givens rotation (c,s) to the vector (x,y), [ c s ] [ x ] = [ r ]
[ -s c ] [ y ] [ 0 ]
The variables x and y are overwritten by the routine.

Package

gsll.

Source

blas1.lisp.

Methods
Method: givens-rotation ((x vector-single-float) (y vector-single-float) (c vector-single-float) (s vector-single-float))
Method: givens-rotation ((x vector-double-float) (y vector-double-float) (c vector-double-float) (s vector-double-float))
Generic Function: givens-rotation-m (x y c s)

These functions compute a Givens rotation (c,s) to the vector (x,y), [ c s ] [ x ] = [ r ]
[ -s c ] [ y ] [ 0 ]
The variables x and y are overwritten by the routine.

Package

gsll.

Source

blas1.lisp.

Methods
Method: givens-rotation-m ((x vector-single-float) (y vector-single-float) (c vector-single-float) (s vector-single-float))
Method: givens-rotation-m ((x vector-double-float) (y vector-double-float) (c vector-double-float) (s vector-double-float))
Generic Function: gsl-cos (x)

The cosine function cos(x).

Package

gsll.

Source

trigonometry.lisp.

Methods
Method: gsl-cos ((x complex))
Method: gsl-cos ((x float))
Generic Function: gsl-log (x)

The natural logarithm of x, log(x), for x > 0.

Package

gsll.

Source

logarithm.lisp.

Methods
Method: gsl-log ((x complex))

Results are returned as lnr, theta such that
exp(lnr + i theta) = z_r + i z_i, where theta lies in the range [-pi,pi].

Method: gsl-log ((x float))
Generic Function: gsl-sin (x)

The sine function sin(x).

Package

gsll.

Source

trigonometry.lisp.

Methods
Method: gsl-sin ((x complex))
Method: gsl-sin ((x float))
Generic Function: hermitian-rank-1-update (x a &optional alpha beta uplo trans)

If the first argument is a vector,
compute the hermitian rank-1 update A = alpha x x^H + A of the hermitian matrix A. Since the matrix A is hermitian only its upper half or lower half need to be stored. When Uplo is :upper then the upper triangle and diagonal of A are used, and when Uplo is :lower then the lower triangle and diagonal of A are used. The imaginary elements of the diagonal are automatically set to zero. If the first argument is a matrix, compute a rank-k update of the hermitian matrix C, C = alpha A A^H + beta C when Trans is :notrans and C = alpha A^H A + beta C when Trans is
:trans. Since the matrix C is hermitian only its upper half or lower half need to be stored. When Uplo is :upper then the upper triangle and diagonal of C are used, and when Uplo is :lower then the lower triangle and diagonal of C are used. The imaginary elements of the diagonal are automatically set to zero.

Package

gsll.

Source

blas2.lisp.

Methods
Method: hermitian-rank-1-update ((a matrix-complex-double-float) (c matrix-complex-double-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: hermitian-rank-1-update ((a matrix-complex-single-float) (c matrix-complex-single-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: hermitian-rank-1-update ((x vector-complex-single-float) (a matrix-complex-single-float) &optional alpha beta uplo trans)
Method: hermitian-rank-1-update ((x vector-complex-double-float) (a matrix-complex-double-float) &optional alpha beta uplo trans)
Generic Function: hermitian-rank-2-update (x y a &optional alpha beta uplo trans)

If the first two arguments are vectors, compute the
hermitian rank-2 update A = alpha x y^H + alpha^* y x^H A of
the hermitian matrix A. Since the matrix A is hermitian only its upper half or lower half need to be stored. When uplo is :upper then the upper triangle and diagonal of A are used, and when uplo is :lower then the lower triangle and diagonal of A are used. The imaginary elements of the diagonal are automatically set to zero. If the first two arguments are matrices, compute a rank-2k update of the hermitian matrix C, C = alpha A B^H + alpha^* B A^H + beta C when Trans is :notrans and C = alpha A^H B + alpha^* B^H A + beta C when Trans is :conjtrans. Since the matrix C is
hermitian only its upper half or lower half need to be stored. When Uplo is :upper then the upper triangle and diagonal of C are used, and when Uplo is :lower then the lower triangle and diagonal of C are used. The imaginary elements of the diagonal are automatically set to zero.

Package

gsll.

Source

blas2.lisp.

Methods
Method: hermitian-rank-2-update ((a matrix-complex-double-float) (b matrix-complex-double-float) (c matrix-complex-double-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: hermitian-rank-2-update ((a matrix-complex-single-float) (b matrix-complex-single-float) (c matrix-complex-single-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: hermitian-rank-2-update ((x vector-complex-single-float) (y vector-complex-single-float) (a matrix-complex-single-float) &optional alpha beta uplo trans)
Method: hermitian-rank-2-update ((x vector-complex-double-float) (y vector-complex-double-float) (a matrix-complex-double-float) &optional alpha beta uplo trans)
Generic Function: hypergeometric-1f1 (m n x)

The confluent hypergeometric function 1F1(m,n,x) = M(m,n,x).

Package

gsll.

Source

hypergeometric.lisp.

Methods
Method: hypergeometric-1f1 ((a float) (b float) x)

The confluent hypergeometric function
1F1(a,b,x) = M(a,b,x) for general parameters a, b.

Method: hypergeometric-1f1 ((m integer) (n integer) x)

The confluent hypergeometric function 1F1(m,n,x) = M(m,n,x) for integer parameters m, n.

Generic Function: hypergeometric-u (m n x)

The confluent hypergeometric function U(m,n,x).

Package

gsll.

Source

hypergeometric.lisp.

Methods
Method: hypergeometric-u ((a float) (b float) x)

The confluent hypergeometric function U(a,b,x).

Method: hypergeometric-u ((m integer) (n integer) x)

The confluent hypergeometric function U(m,n,x) for integer parameters m, n.

Generic Function: hypergeometric-u-e10 (m n x)

The confluent hypergeometric function
U(m,n,x) that returns a result with extended range.

Package

gsll.

Source

hypergeometric.lisp.

Methods
Method: hypergeometric-u-e10 ((a float) (b float) x)

The confluent hypergeometric function
U(a,b,x) using that returns a result with extended range.

Method: hypergeometric-u-e10 ((m integer) (n integer) x)

The confluent hypergeometric function
U(m,n,x) for integer parameters m, n that returns a result with extended range.

Generic Function: increment (histogram value &optional weight)

Update the histogram by adding the weight
(which defaults to 1.0) to the
bin whose range contains the coordinate x.

If x lies in the valid range of the histogram then the function
returns zero to indicate success. If x is less than the lower
limit of the histogram then the function issues a warning input-domain, and none of bins are modified. Similarly, if the value of x is greater
than or equal to the upper limit of the histogram then the function issues a warning input-domain, and none of the bins are modified. The error handler is not called, however, since it is often necessary to compute histograms for a small range of a larger dataset, ignoring the values outside the range of interest.

Package

gsll.

Source

updating-accessing.lisp.

Methods
Method: increment ((histogram histogram2d) values &optional weight)
Method: increment ((histogram histogram) value &optional weight)
Generic Function: index-max (vec)

The index of the largest element of the vector
x. The largest element is determined by its absolute magnitude for real vectors and by the sum of the magnitudes of the real and imaginary parts |Re(x_i)| + |Im(x_i)| for complex vectors. If the largest value occurs several times then the index of the first occurrence is returned.

Package

gsll.

Source

blas1.lisp.

Methods
Method: index-max ((vec vector-single-float))
Method: index-max ((vec vector-double-float))
Method: index-max ((vec vector-complex-single-float))
Method: index-max ((vec vector-complex-double-float))
Generic Function: inverse-discrete-fourier-transform (vector &key stride result)

Inverse discrete Fourier transform provided to check the FFT routines.

Package

gsll.

Source

discrete.lisp.

Methods
Method: inverse-discrete-fourier-transform ((vector vector-complex-single-float) &key stride result)
Method: inverse-discrete-fourier-transform ((vector vector-complex-double-float) &key stride result)
Generic Function: inverse-matrix-product (a x &optional alpha uplo transa diag side)

If the second argument is a vector, compute
inv(op(A)) x for x, where op(A) = A, A^T, A^H for
TransA = :NoTrans, :Trans, :ConjTrans. When Uplo is :Upper then the upper triangle of A is used, and when Uplo is :Lower then the lower triangle of A is used. If Diag is :NonUnit then the diagonal of the matrix is used, but if Diag is :Unit then the diagonal elements of the matrix A are taken as unity and are not referenced.
If the second argument is a matrix, compute
the inverse-matrix matrix product B = alpha op(inv(A))B if Side is :Left and B = alpha B op(inv(A)) if Side is :Right. The matrix A is triangular and op(A) = A, A^T, A^H for TransA = :NoTrans, :Trans, :ConjTrans When
Uplo is :Upper then the upper triangle of A is used, and when Uplo is :Lower then the lower triangle of A is
used. If Diag is :NonUnit then the diagonal of A is used, but if Diag is :Unit then the diagonal elements of the matrix A are taken as unity and are not referenced.

Package

gsll.

Source

blas2.lisp.

Methods
Method: inverse-matrix-product ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: inverse-matrix-product ((a matrix-complex-single-float) (b matrix-complex-single-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: inverse-matrix-product ((a matrix-double-float) (b matrix-double-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: inverse-matrix-product ((a matrix-single-float) (b matrix-single-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: inverse-matrix-product ((a matrix-single-float) (x vector-single-float) &optional alpha uplo transa diag side)
Method: inverse-matrix-product ((a matrix-double-float) (x vector-double-float) &optional alpha uplo transa diag side)
Method: inverse-matrix-product ((a matrix-complex-single-float) (x vector-complex-single-float) &optional alpha uplo transa diag side)
Method: inverse-matrix-product ((a matrix-complex-double-float) (x vector-complex-double-float) &optional alpha uplo transa diag side)
Generic Function: iterate (object)

Take the next iteration step for this object.

Package

gsll.

Source

generic.lisp.

Methods
Method: iterate ((solver nonlinear-fdffit))

Perform a single iteration of the solver. The solver maintains a current estimate of the best-fit parameters at all times.

Source

nonlinear-least-squares.lisp.

Method: iterate ((solver nonlinear-ffit))

Perform a single iteration of the solver. The solver maintains a current estimate of the best-fit parameters at all times.

Source

nonlinear-least-squares.lisp.

Method: iterate ((minimizer multi-dimensional-minimizer-fdf))

Perform a single iteration of the minimizer. If the iteration encounters an unexpected problem then an error code will be returned.

Source

minimization-multi.lisp.

Method: iterate ((minimizer multi-dimensional-minimizer-f))

Perform a single iteration of the minimizer. If the iteration encounters an unexpected problem then an error code will be returned.

Source

minimization-multi.lisp.

Method: iterate ((solver multi-dimensional-root-solver-fdf))

Perform a single iteration of the solver. The following errors may be signalled: ’bad-function-supplied, the iteration encountered a singular point where the function or its derivative evaluated to infinity or NaN, or ’gsl-division-by-zero, the derivative of the function vanished at the iteration point, preventing the algorithm from continuing without a division by zero.

Source

roots-multi.lisp.

Method: iterate ((solver multi-dimensional-root-solver-f))

Perform a single iteration of the solver. The following errors may be signalled: ’bad-function-supplied, the iteration encountered a singular point where the function or its derivative evaluated to infinity or NaN, or ’gsl-division-by-zero, the derivative of the function vanished at the iteration point, preventing the algorithm from continuing without a division by zero.

Source

roots-multi.lisp.

Method: iterate ((minimizer one-dimensional-minimizer))

Perform a single iteration of the minimizer. The following
errors may be signalled: ’bad-function-supplied,
the iteration encountered a singular point where the function or its derivative evaluated to infinity or NaN, or
:FAILURE, the algorithm could not improve the current best approximation or bounding interval.

Source

minimization-one.lisp.

Method: iterate ((solver one-dimensional-root-solver-fdf))

Perform a single iteration of the solver. The following errors may be signalled: ’bad-function-supplied, the iteration encountered a singular point where the function or its derivative evaluated to infinity or NaN, or ’gsl-division-by-zero, the derivative of the function vanished at the iteration point, preventing the algorithm from continuing without a division by zero.

Source

roots-one.lisp.

Method: iterate ((solver one-dimensional-root-solver-f))

Perform a single iteration of the solver. The following errors may be signalled: ’bad-function-supplied, the iteration encountered a singular point where the function or its derivative evaluated to infinity or NaN, or ’gsl-division-by-zero, the derivative of the function vanished at the iteration point, preventing the algorithm from continuing without a division by zero.

Source

roots-one.lisp.

Generic Function: kurtosis (data &optional mean standard-deviation)

The kurtosis of data defined as
kurtosis = ((1/N) sum ((x_i - Hatmu)/Hatsigma)^4) - 3 The kurtosis measures how sharply peaked a distribution is, relative to its width. The kurtosis is normalized to zero for a gaussian distribution.

Package

gsll.

Source

higher-moments.lisp.

Methods
Method: kurtosis ((data vector-single-float) &optional mean standard-deviation)
Method: kurtosis ((data vector-double-float) &optional mean standard-deviation)
Method: kurtosis ((data vector-signed-byte-8) &optional mean standard-deviation)
Method: kurtosis ((data vector-unsigned-byte-8) &optional mean standard-deviation)
Method: kurtosis ((data vector-signed-byte-16) &optional mean standard-deviation)
Method: kurtosis ((data vector-unsigned-byte-16) &optional mean standard-deviation)
Method: kurtosis ((data vector-signed-byte-32) &optional mean standard-deviation)
Method: kurtosis ((data vector-unsigned-byte-32) &optional mean standard-deviation)
Method: kurtosis ((data vector-signed-byte-64) &optional mean standard-deviation)
Method: kurtosis ((data vector-unsigned-byte-64) &optional mean standard-deviation)
Generic Function: last-step (object)

The last step dx taken by the solver.

Package

gsll.

Source

generic.lisp.

Methods
Method: last-step ((solver nonlinear-fdffit))
Source

nonlinear-least-squares.lisp.

Method: last-step ((solver multi-dimensional-root-solver-fdf))

The last step dx taken by the solver.

Source

roots-multi.lisp.

Method: last-step ((solver multi-dimensional-root-solver-f))

The last step dx taken by the solver.

Source

roots-multi.lisp.

Generic Function: lu-decomposition (a &optional permutation)

Factorize the square matrix A into the LU decomposition PA = LU, and return the sign of the permutation. On output the diagonal and upper triangular part of the input matrix A contain the matrix U. The lower triangular part of the input matrix (excluding the diagonal) contains L. The diagonal elements of L are unity, and are not stored.

The permutation matrix P is encoded in the permutation supplied as the second argument and returned as the second value. The j-th column of the matrix P is given by the k-th column of the identity matrix, where k = p_j the j-th element of the permutation vector. The sign of the permutation is returned as the second value; it is the value (-1)^n, where n is the number of interchanges in the permutation.

The algorithm used in the decomposition is Gaussian Elimination with partial pivoting (Golub & Van Loan, Matrix Computations, Algorithm 3.4.1).

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-decomposition ((a matrix-double-float) &optional permutation)
Method: lu-decomposition ((a matrix-complex-double-float) &optional permutation)
Generic Function: lu-determinant (lu signum)

Compute the determinant of a matrix from its LU
decomposition, LU. The determinant is computed as the product of the diagonal elements of U and the sign of the row permutation signum.

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-determinant ((lu matrix-double-float) signum)
Method: lu-determinant ((lu matrix-complex-double-float) signum)
Generic Function: lu-invert (lu p &optional inverse)

Compute the inverse of a matrix A from its LU
decomposition (LU,p), storing the result in the matrix inverse. The inverse is computed by solving the system A x = b for each column of the identity matrix. It is preferable to avoid direct use of the inverse whenever possible, as the linear solver functions can obtain the same result more efficiently and reliably (consult any introductory textbook on numerical linear algebra for details).

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-invert ((lu matrix-double-float) p &optional inverse)
Method: lu-invert ((lu matrix-complex-double-float) p &optional inverse)
Generic Function: lu-log-determinant (lu)

The logarithm of the absolute value of the
determinant of a matrix A, ln|det(A)|, from its LU decomposition, LU. This function may be useful if the direct computation of the determinant would overflow or underflow.

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-log-determinant ((lu matrix-double-float))
Method: lu-log-determinant ((lu matrix-complex-double-float))
Generic Function: lu-refine (a lu p b x &optional residual)

Apply an iterative improvement to x, the solution of
A x = b, using the LU decomposition of A into (LU,p). The initial residual r = A x - b is also computed and stored in residual.

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-refine ((a matrix-double-float) lu p (b vector-double-float) (x vector-double-float) &optional residual)
Method: lu-refine ((a matrix-complex-double-float) lu p (b vector-complex-double-float) (x vector-complex-double-float) &optional residual)
Generic Function: lu-sgndet (lu signum)

Compute the sign or phase factor of the determinant of a matrix A, det(A)/|det(A)|, from its LU decomposition, LU.

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-sgndet ((lu matrix-double-float) signum)
Method: lu-sgndet ((lu matrix-complex-double-float) signum)
Generic Function: lu-solve (a b permutation &optional x-spec)

Solve the square system A x = b using the LU
decomposition of A into (LU, p) given by LU-decomp.
If x-spec is nil, the solution will be computed in-place replacing b, if it is T, an appropriate vector will be created and the solution will be computed there. Otherwise it should be a supplied vector.

Package

gsll.

Source

lu.lisp.

Methods
Method: lu-solve ((a matrix-double-float) (b vector-double-float) permutation &optional x-spec)
Method: lu-solve ((a matrix-complex-double-float) (b vector-complex-double-float) permutation &optional x-spec)
Generic Function: matrix-product (a x &optional y alpha beta transa transb)

If the second and third arguments are vectors, compute the matrix-vector product and sum
y = alpha op(A) x + beta y, where op(A) = A, A^T, A^H for TransA = :notrans, :trans, :conjtrans.
If the second and third arguments are matrices, compute the matrix-matrix product and sum C = alpha
op(A) op(B) + beta C where op(A) = A, A^T, A^H for TransA = :notrans, :trans, :conjtrans and similarly for the parameter TransB.

Package

gsll.

Source

blas2.lisp.

Methods
Method: matrix-product ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional c alpha beta transa transb)
Source

blas3.lisp.

Method: matrix-product ((a matrix-complex-single-float) (b matrix-complex-single-float) &optional c alpha beta transa transb)
Source

blas3.lisp.

Method: matrix-product ((a matrix-double-float) (b matrix-double-float) &optional c alpha beta transa transb)
Source

blas3.lisp.

Method: matrix-product ((a matrix-single-float) (b matrix-single-float) &optional c alpha beta transa transb)
Source

blas3.lisp.

Method: matrix-product ((a matrix-single-float) (x vector-single-float) &optional y alpha beta transa transb)
Method: matrix-product ((a matrix-double-float) (x vector-double-float) &optional y alpha beta transa transb)
Method: matrix-product ((a matrix-complex-single-float) (x vector-complex-single-float) &optional y alpha beta transa transb)
Method: matrix-product ((a matrix-complex-double-float) (x vector-complex-double-float) &optional y alpha beta transa transb)
Generic Function: matrix-product-hermitian (a x &optional y alpha beta uplo side)

If the second and third arguments are vectors, compute the matrix-vector product and sum y = alpha A x + beta y for the hermitian matrix A. Since the matrix A is hermitian only its upper half or lower half need to be stored. When Uplo is :upper then the upper triangle and diagonal of A are used, and when Uplo is :lower then the lower triangle and diagonal of A are used. The imaginary elements of the diagonal are automatically assumed to be zero and are not referenced. If the second and third arguments are matrices, compute the matrix-matrix product and sum C = alpha A B + beta C if Side is :left and C = alpha B A + beta C if Side
is :right, where the matrix A is hermitian. When Uplo is
:upper then the upper triangle and diagonal of A are used, and when Uplo is :lower then the lower triangle and diagonal of A are used. The imaginary elements of the diagonal are automatically set to zero.

Package

gsll.

Source

blas2.lisp.

Methods
Method: matrix-product-hermitian ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional c alpha beta uplo side)
Source

blas3.lisp.

Method: matrix-product-hermitian ((a matrix-complex-single-float) (b matrix-complex-single-float) &optional c alpha beta uplo side)
Source

blas3.lisp.

Method: matrix-product-hermitian ((a matrix-complex-single-float) (x vector-complex-single-float) &optional y alpha beta uplo side)
Method: matrix-product-hermitian ((a matrix-complex-double-float) (x vector-complex-double-float) &optional y alpha beta uplo side)
Generic Function: matrix-product-symmetric (a x &optional y alpha beta uplo side)

If the second and third arguments are vectors, compute
the matrix-vector product and sum y = alpha A
x + beta y for the symmetric matrix A. Since the matrix A is symmetric only its upper half or lower half need to be stored. When Uplo is :Upper then the upper triangle and diagonal of A are used, and when Uplo is :Lower then the lower triangle and diagonal of A are used.
If the second and third arguments are matrices, compute the matrix-matrix product and sum C = alpha A
B + beta C for Side is :Left and C = alpha B A + beta C for Side is :Right, where the matrix A is symmetric. When Uplo is :Upper then the upper triangle and diagonal of A are used, and when Uplo is :Lower then the lower triangle and diagonal of A are used.

Package

gsll.

Source

blas2.lisp.

Methods
Method: matrix-product-symmetric ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional c alpha beta uplo side)
Source

blas3.lisp.

Method: matrix-product-symmetric ((a matrix-complex-single-float) (b matrix-complex-single-float) &optional c alpha beta uplo side)
Source

blas3.lisp.

Method: matrix-product-symmetric ((a matrix-double-float) (b matrix-double-float) &optional c alpha beta uplo side)
Source

blas3.lisp.

Method: matrix-product-symmetric ((a matrix-single-float) (b matrix-single-float) &optional c alpha beta uplo side)
Source

blas3.lisp.

Method: matrix-product-symmetric ((a matrix-single-float) (x vector-single-float) &optional y alpha beta uplo side)
Method: matrix-product-symmetric ((a matrix-double-float) (x vector-double-float) &optional y alpha beta uplo side)
Generic Function: matrix-product-triangular (a x &optional alpha uplo transa diag side)

If the second argument is a vector, compute
the matrix-vector product x = op(A) x
for the triangular matrix A, where op(A) = A, A^T, A^H for TransA = :NoTrans, :Trans, :ConjTrans. When Uplo
is :Upper then the upper triangle of A is used, and when Uplo is :Lower then the lower triangle of A is used. If Diag is :NonUnit then the diagonal of the matrix is used, but if Diag is :Unit then the diagonal elements of the matrix A are taken as unity and are not referenced.
If the second argument is a matrix, compute
the matrix-matrix product B = alpha op(A) B
if Side is :Left and B = alpha B op(A) if Side is :Right. The matrix A is triangular and op(A) = A, A^T, A^H for TransA = :NoTrans, :Trans, :ConjTrans When Uplo
is :Upper then the upper triangle of A is used, and when Uplo is :Lower then the lower triangle of A is used. If Diag is :NonUnit then the diagonal of A is used, but if Diag is :Unit then the diagonal elements of the matrix A are taken as unity and are not referenced.

Package

gsll.

Source

blas2.lisp.

Methods
Method: matrix-product-triangular ((a matrix-complex-double-float) (b matrix-complex-double-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: matrix-product-triangular ((a matrix-complex-single-float) (b matrix-complex-single-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: matrix-product-triangular ((a matrix-double-float) (b matrix-double-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: matrix-product-triangular ((a matrix-single-float) (b matrix-single-float) &optional alpha uplo transa diag side)
Source

blas3.lisp.

Method: matrix-product-triangular ((a matrix-single-float) (x vector-single-float) &optional alpha uplo transa diag side)
Method: matrix-product-triangular ((a matrix-double-float) (x vector-double-float) &optional alpha uplo transa diag side)
Method: matrix-product-triangular ((a matrix-complex-single-float) (x vector-complex-single-float) &optional alpha uplo transa diag side)
Method: matrix-product-triangular ((a matrix-complex-double-float) (x vector-complex-double-float) &optional alpha uplo transa diag side)
Generic Function: matrix-transpose (source &optional destination)

Make the destination matrix the transpose of the source matrix by copying the elements. The dimensions of the destination matrix must match the transposed dimensions of the source.

Package

gsll.

Source

matrix.lisp.

Methods
Method: matrix-transpose ((source matrix-single-float) &optional destination)
Method: matrix-transpose ((source matrix-double-float) &optional destination)
Method: matrix-transpose ((source matrix-complex-single-float) &optional destination)
Method: matrix-transpose ((source matrix-complex-double-float) &optional destination)
Method: matrix-transpose ((source matrix-signed-byte-8) &optional destination)
Method: matrix-transpose ((source matrix-unsigned-byte-8) &optional destination)
Method: matrix-transpose ((source matrix-signed-byte-16) &optional destination)
Method: matrix-transpose ((source matrix-unsigned-byte-16) &optional destination)
Method: matrix-transpose ((source matrix-signed-byte-32) &optional destination)
Method: matrix-transpose ((source matrix-unsigned-byte-32) &optional destination)
Method: matrix-transpose ((source matrix-signed-byte-64) &optional destination)
Method: matrix-transpose ((source matrix-unsigned-byte-64) &optional destination)
Generic Function: matrix-transpose* (matrix)

Replace the matrix by its transpose by copying the elements of the matrix in-place. The matrix must be square for this operation to be possible.

Package

gsll.

Source

matrix.lisp.

Methods
Method: matrix-transpose* ((matrix matrix-single-float))
Method: matrix-transpose* ((matrix matrix-double-float))
Method: matrix-transpose* ((matrix matrix-complex-single-float))
Method: matrix-transpose* ((matrix matrix-complex-double-float))
Method: matrix-transpose* ((matrix matrix-signed-byte-8))
Method: matrix-transpose* ((matrix matrix-unsigned-byte-8))
Method: matrix-transpose* ((matrix matrix-signed-byte-16))
Method: matrix-transpose* ((matrix matrix-unsigned-byte-16))
Method: matrix-transpose* ((matrix matrix-signed-byte-32))
Method: matrix-transpose* ((matrix matrix-unsigned-byte-32))
Method: matrix-transpose* ((matrix matrix-signed-byte-64))
Method: matrix-transpose* ((matrix matrix-unsigned-byte-64))
Generic Function: max-index (a)

The index of the maximum value in a. When there are several equal maximum elements, then the lowest index is returned.

Package

gsll.

Source

both.lisp.

Methods
Method: max-index ((histogram histogram2d))

The indices of the bin containing the maximum value. In the case where several bins contain the same maximum value the first bin found is returned.

Source

statistics.lisp.

Method: max-index ((histogram histogram))

The index of the bin containing the maximum value. In the case where several bins contain the same maximum value the smallest index is returned.

Source

statistics.lisp.

Method: max-index ((a matrix-unsigned-byte-64))
Method: max-index ((a matrix-signed-byte-64))
Method: max-index ((a matrix-unsigned-byte-32))
Method: max-index ((a matrix-signed-byte-32))
Method: max-index ((a matrix-unsigned-byte-16))
Method: max-index ((a matrix-signed-byte-16))
Method: max-index ((a matrix-unsigned-byte-8))
Method: max-index ((a matrix-signed-byte-8))
Method: max-index ((a matrix-double-float))
Method: max-index ((a matrix-single-float))
Method: max-index ((a vector-single-float))
Method: max-index ((a vector-double-float))
Method: max-index ((a vector-signed-byte-8))
Method: max-index ((a vector-unsigned-byte-8))
Method: max-index ((a vector-signed-byte-16))
Method: max-index ((a vector-unsigned-byte-16))
Method: max-index ((a vector-signed-byte-32))
Method: max-index ((a vector-unsigned-byte-32))
Method: max-index ((a vector-signed-byte-64))
Method: max-index ((a vector-unsigned-byte-64))
Generic Function: max-range (histogram)

The maximum upper range limit(s) of the histogram.

Package

gsll.

Source

updating-accessing.lisp.

Methods
Method: max-range ((histogram histogram))
Method: max-range ((histogram histogram2d))
Generic Function: mean (array)

The arithmetic mean of the array.
The arithmetic mean, or sample mean, is denoted by
Hatmu and defined as Hatmu = (1/N) sum x_i. Returns a double-float.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: mean ((histogram histogram2d))
Source

statistics.lisp.

Method: mean ((histogram histogram))

The mean of the histogrammed variable, where the histogram is regarded as a probability distribution. Negative bin values are ignored for the purposes of this calculation. The resolution of the result is limited by the bin width.

Source

statistics.lisp.

Method: mean ((array vector-single-float))
Method: mean ((array vector-double-float))
Method: mean ((array vector-signed-byte-8))
Method: mean ((array vector-unsigned-byte-8))
Method: mean ((array vector-signed-byte-16))
Method: mean ((array vector-unsigned-byte-16))
Method: mean ((array vector-signed-byte-32))
Method: mean ((array vector-unsigned-byte-32))
Method: mean ((array vector-signed-byte-64))
Method: mean ((array vector-unsigned-byte-64))
Method: mean ((array matrix-single-float))
Method: mean ((array matrix-double-float))
Method: mean ((array matrix-signed-byte-8))
Method: mean ((array matrix-unsigned-byte-8))
Method: mean ((array matrix-signed-byte-16))
Method: mean ((array matrix-unsigned-byte-16))
Method: mean ((array matrix-signed-byte-32))
Method: mean ((array matrix-unsigned-byte-32))
Method: mean ((array matrix-signed-byte-64))
Method: mean ((array matrix-unsigned-byte-64))
Generic Function: median (sorted-data)

The median value of sorted-data. The elements of the array
must be in ascending numerical order. There are no checks to see whether the data are sorted, so the function #’sort should
always be used first.
When the dataset has an odd number of elements the median is the value of element (n-1)/2. When the dataset has an even number of
elements the median is the mean of the two nearest middle values, elements (n-1)/2 and n/2. Since the algorithm for
computing the median involves interpolation this function always returns a floating-point number, even for integer data types.

Package

gsll.

Source

median-percentile.lisp.

Methods
Method: median ((sorted-data vector-single-float))
Method: median ((sorted-data vector-double-float))
Method: median ((sorted-data vector-signed-byte-8))
Method: median ((sorted-data vector-unsigned-byte-8))
Method: median ((sorted-data vector-signed-byte-16))
Method: median ((sorted-data vector-unsigned-byte-16))
Method: median ((sorted-data vector-signed-byte-32))
Method: median ((sorted-data vector-unsigned-byte-32))
Method: median ((sorted-data vector-signed-byte-64))
Method: median ((sorted-data vector-unsigned-byte-64))
Generic Function: min-index (a)

The index of the minimum value in a. When there are several equal minimum elements, then the lowest index is returned.

Package

gsll.

Source

both.lisp.

Methods
Method: min-index ((histogram histogram2d))

The indices of the bin containing the minimum value. In the case where several bins contain the same minimum value the first bin found is returned.

Source

statistics.lisp.

Method: min-index ((histogram histogram))

The index of the bin containing the minimum value. In the case where several bins contain the same minimum value the smallest index is returned.

Source

statistics.lisp.

Method: min-index ((a matrix-unsigned-byte-64))
Method: min-index ((a matrix-signed-byte-64))
Method: min-index ((a matrix-unsigned-byte-32))
Method: min-index ((a matrix-signed-byte-32))
Method: min-index ((a matrix-unsigned-byte-16))
Method: min-index ((a matrix-signed-byte-16))
Method: min-index ((a matrix-unsigned-byte-8))
Method: min-index ((a matrix-signed-byte-8))
Method: min-index ((a matrix-double-float))
Method: min-index ((a matrix-single-float))
Method: min-index ((a vector-single-float))
Method: min-index ((a vector-double-float))
Method: min-index ((a vector-signed-byte-8))
Method: min-index ((a vector-unsigned-byte-8))
Method: min-index ((a vector-signed-byte-16))
Method: min-index ((a vector-unsigned-byte-16))
Method: min-index ((a vector-signed-byte-32))
Method: min-index ((a vector-unsigned-byte-32))
Method: min-index ((a vector-signed-byte-64))
Method: min-index ((a vector-unsigned-byte-64))
Generic Function: min-range (histogram)

The minimum lower range limit(s) of the histogram.

Package

gsll.

Source

updating-accessing.lisp.

Methods
Method: min-range ((histogram histogram))
Method: min-range ((histogram histogram2d))
Generic Function: minimum-size (object)

The minimum number of points required by the interpolation. For example, Akima spline interpolation requires a minimum of 5 points.

Package

gsll.

Source

types.lisp.

Methods
Method: minimum-size ((object spline))
Method: minimum-size ((object interpolation))
Generic Function: minmax (a)

The minimum and maximum values in a.

Package

gsll.

Source

both.lisp.

Methods
Method: minmax ((a vector-single-float))
Method: minmax ((a vector-double-float))
Method: minmax ((a vector-signed-byte-8))
Method: minmax ((a vector-unsigned-byte-8))
Method: minmax ((a vector-signed-byte-16))
Method: minmax ((a vector-unsigned-byte-16))
Method: minmax ((a vector-signed-byte-32))
Method: minmax ((a vector-unsigned-byte-32))
Method: minmax ((a vector-signed-byte-64))
Method: minmax ((a vector-unsigned-byte-64))
Method: minmax ((a matrix-single-float))
Method: minmax ((a matrix-double-float))
Method: minmax ((a matrix-signed-byte-8))
Method: minmax ((a matrix-unsigned-byte-8))
Method: minmax ((a matrix-signed-byte-16))
Method: minmax ((a matrix-unsigned-byte-16))
Method: minmax ((a matrix-signed-byte-32))
Method: minmax ((a matrix-unsigned-byte-32))
Method: minmax ((a matrix-signed-byte-64))
Method: minmax ((a matrix-unsigned-byte-64))
Generic Function: minmax-index (a)

The indices of the minimum and maximum values in a.
When there are several equal minimum elements then the lowest index is returned. Returned indices are minimum, maximum; for matrices imin, jmin, imax, jmax.

Package

gsll.

Source

both.lisp.

Methods
Method: minmax-index ((a matrix-unsigned-byte-64))
Method: minmax-index ((a matrix-signed-byte-64))
Method: minmax-index ((a matrix-unsigned-byte-32))
Method: minmax-index ((a matrix-signed-byte-32))
Method: minmax-index ((a matrix-unsigned-byte-16))
Method: minmax-index ((a matrix-signed-byte-16))
Method: minmax-index ((a matrix-unsigned-byte-8))
Method: minmax-index ((a matrix-signed-byte-8))
Method: minmax-index ((a matrix-double-float))
Method: minmax-index ((a matrix-single-float))
Method: minmax-index ((a vector-single-float))
Method: minmax-index ((a vector-double-float))
Method: minmax-index ((a vector-signed-byte-8))
Method: minmax-index ((a vector-unsigned-byte-8))
Method: minmax-index ((a vector-signed-byte-16))
Method: minmax-index ((a vector-unsigned-byte-16))
Method: minmax-index ((a vector-signed-byte-32))
Method: minmax-index ((a vector-unsigned-byte-32))
Method: minmax-index ((a vector-signed-byte-64))
Method: minmax-index ((a vector-unsigned-byte-64))
Generic Function: mmax (a)

The maximum value in a.

Package

gsll.

Source

both.lisp.

Methods
Method: mmax ((histogram histogram2d))

The maximum value contained in the histogram bins.

Source

statistics.lisp.

Method: mmax ((histogram histogram))

The maximum value contained in the histogram bins.

Source

statistics.lisp.

Method: mmax ((a vector-single-float))
Method: mmax ((a vector-double-float))
Method: mmax ((a vector-signed-byte-8))
Method: mmax ((a vector-unsigned-byte-8))
Method: mmax ((a vector-signed-byte-16))
Method: mmax ((a vector-unsigned-byte-16))
Method: mmax ((a vector-signed-byte-32))
Method: mmax ((a vector-unsigned-byte-32))
Method: mmax ((a vector-signed-byte-64))
Method: mmax ((a vector-unsigned-byte-64))
Method: mmax ((a matrix-single-float))
Method: mmax ((a matrix-double-float))
Method: mmax ((a matrix-signed-byte-8))
Method: mmax ((a matrix-unsigned-byte-8))
Method: mmax ((a matrix-signed-byte-16))
Method: mmax ((a matrix-unsigned-byte-16))
Method: mmax ((a matrix-signed-byte-32))
Method: mmax ((a matrix-unsigned-byte-32))
Method: mmax ((a matrix-signed-byte-64))
Method: mmax ((a matrix-unsigned-byte-64))
Generic Function: mmin (a)

The minimum value in a.

Package

gsll.

Source

both.lisp.

Methods
Method: mmin ((histogram histogram2d))

The minimum value contained in the histogram bins.

Source

statistics.lisp.

Method: mmin ((histogram histogram))

The minimum value contained in the histogram bins.

Source

statistics.lisp.

Method: mmin ((a vector-single-float))
Method: mmin ((a vector-double-float))
Method: mmin ((a vector-signed-byte-8))
Method: mmin ((a vector-unsigned-byte-8))
Method: mmin ((a vector-signed-byte-16))
Method: mmin ((a vector-unsigned-byte-16))
Method: mmin ((a vector-signed-byte-32))
Method: mmin ((a vector-unsigned-byte-32))
Method: mmin ((a vector-signed-byte-64))
Method: mmin ((a vector-unsigned-byte-64))
Method: mmin ((a matrix-single-float))
Method: mmin ((a matrix-double-float))
Method: mmin ((a matrix-signed-byte-8))
Method: mmin ((a matrix-unsigned-byte-8))
Method: mmin ((a matrix-signed-byte-16))
Method: mmin ((a matrix-unsigned-byte-16))
Method: mmin ((a matrix-signed-byte-32))
Method: mmin ((a matrix-unsigned-byte-32))
Method: mmin ((a matrix-signed-byte-64))
Method: mmin ((a matrix-unsigned-byte-64))
Generic Function: mminusp (a)

All elements of a are negative.

Package

gsll.

Source

both.lisp.

Methods
Method: mminusp ((a vector-single-float))
Method: mminusp ((a vector-double-float))
Method: mminusp ((a vector-complex-single-float))
Method: mminusp ((a vector-complex-double-float))
Method: mminusp ((a vector-signed-byte-8))
Method: mminusp ((a vector-unsigned-byte-8))
Method: mminusp ((a vector-signed-byte-16))
Method: mminusp ((a vector-unsigned-byte-16))
Method: mminusp ((a vector-signed-byte-32))
Method: mminusp ((a vector-unsigned-byte-32))
Method: mminusp ((a vector-signed-byte-64))
Method: mminusp ((a vector-unsigned-byte-64))
Method: mminusp ((a matrix-single-float))
Method: mminusp ((a matrix-double-float))
Method: mminusp ((a matrix-complex-single-float))
Method: mminusp ((a matrix-complex-double-float))
Method: mminusp ((a matrix-signed-byte-8))
Method: mminusp ((a matrix-unsigned-byte-8))
Method: mminusp ((a matrix-signed-byte-16))
Method: mminusp ((a matrix-unsigned-byte-16))
Method: mminusp ((a matrix-signed-byte-32))
Method: mminusp ((a matrix-unsigned-byte-32))
Method: mminusp ((a matrix-signed-byte-64))
Method: mminusp ((a matrix-unsigned-byte-64))
Generic Function: modified-givens-rotation (d1 d2 b1 b2 p)

Not explained

Package

gsll.

Source

blas1.lisp.

Methods
Method: modified-givens-rotation ((d1 vector-single-float) (d2 vector-single-float) (b1 vector-single-float) b2 (p vector-single-float))
Method: modified-givens-rotation ((d1 vector-double-float) (d2 vector-double-float) (b1 vector-double-float) b2 (p vector-double-float))
Generic Function: modified-givens-rotation-m (x y p)

Not explained

Package

gsll.

Source

blas1.lisp.

Methods
Method: modified-givens-rotation-m ((x vector-single-float) (y vector-single-float) (p vector-single-float))
Method: modified-givens-rotation-m ((x vector-double-float) (y vector-double-float) (p vector-double-float))
Generic Function: mplusp (a)

All elements of a are positive.

Package

gsll.

Source

both.lisp.

Methods
Method: mplusp ((a vector-single-float))
Method: mplusp ((a vector-double-float))
Method: mplusp ((a vector-complex-single-float))
Method: mplusp ((a vector-complex-double-float))
Method: mplusp ((a vector-signed-byte-8))
Method: mplusp ((a vector-unsigned-byte-8))
Method: mplusp ((a vector-signed-byte-16))
Method: mplusp ((a vector-unsigned-byte-16))
Method: mplusp ((a vector-signed-byte-32))
Method: mplusp ((a vector-unsigned-byte-32))
Method: mplusp ((a vector-signed-byte-64))
Method: mplusp ((a vector-unsigned-byte-64))
Method: mplusp ((a matrix-single-float))
Method: mplusp ((a matrix-double-float))
Method: mplusp ((a matrix-complex-single-float))
Method: mplusp ((a matrix-complex-double-float))
Method: mplusp ((a matrix-signed-byte-8))
Method: mplusp ((a matrix-unsigned-byte-8))
Method: mplusp ((a matrix-signed-byte-16))
Method: mplusp ((a matrix-unsigned-byte-16))
Method: mplusp ((a matrix-signed-byte-32))
Method: mplusp ((a matrix-unsigned-byte-32))
Method: mplusp ((a matrix-signed-byte-64))
Method: mplusp ((a matrix-unsigned-byte-64))
Generic Function: msort (v)

Sort the n elements of the array data with stride stride into ascending numerical order.

Package

gsll.

Source

sorting.lisp.

Methods
Method: msort ((v vector-single-float))
Method: msort ((v vector-double-float))
Method: msort ((v vector-signed-byte-8))
Method: msort ((v vector-unsigned-byte-8))
Method: msort ((v vector-signed-byte-16))
Method: msort ((v vector-unsigned-byte-16))
Method: msort ((v vector-signed-byte-32))
Method: msort ((v vector-unsigned-byte-32))
Method: msort ((v vector-signed-byte-64))
Method: msort ((v vector-unsigned-byte-64))
Method: msort ((v matrix-single-float))
Method: msort ((v matrix-double-float))
Method: msort ((v matrix-signed-byte-8))
Method: msort ((v matrix-unsigned-byte-8))
Method: msort ((v matrix-signed-byte-16))
Method: msort ((v matrix-unsigned-byte-16))
Method: msort ((v matrix-signed-byte-32))
Method: msort ((v matrix-unsigned-byte-32))
Method: msort ((v matrix-signed-byte-64))
Method: msort ((v matrix-unsigned-byte-64))
Generic Function: mzerop (a)

All elements of a are zero.

Package

gsll.

Source

both.lisp.

Methods
Method: mzerop ((a vector-single-float))
Method: mzerop ((a vector-double-float))
Method: mzerop ((a vector-complex-single-float))
Method: mzerop ((a vector-complex-double-float))
Method: mzerop ((a vector-signed-byte-8))
Method: mzerop ((a vector-unsigned-byte-8))
Method: mzerop ((a vector-signed-byte-16))
Method: mzerop ((a vector-unsigned-byte-16))
Method: mzerop ((a vector-signed-byte-32))
Method: mzerop ((a vector-unsigned-byte-32))
Method: mzerop ((a vector-signed-byte-64))
Method: mzerop ((a vector-unsigned-byte-64))
Method: mzerop ((a matrix-single-float))
Method: mzerop ((a matrix-double-float))
Method: mzerop ((a matrix-complex-single-float))
Method: mzerop ((a matrix-complex-double-float))
Method: mzerop ((a matrix-signed-byte-8))
Method: mzerop ((a matrix-unsigned-byte-8))
Method: mzerop ((a matrix-signed-byte-16))
Method: mzerop ((a matrix-unsigned-byte-16))
Method: mzerop ((a matrix-signed-byte-32))
Method: mzerop ((a matrix-unsigned-byte-32))
Method: mzerop ((a matrix-signed-byte-64))
Method: mzerop ((a matrix-unsigned-byte-64))
Generic Function: name (object)

The name given to the GSL object.

Package

gsll.

Source

mobject.lisp.

Methods
Method: name ((solver nonlinear-fdffit))

The name of the solver type.

Source

nonlinear-least-squares.lisp.

Method: name ((solver nonlinear-ffit))

The name of the solver type.

Source

nonlinear-least-squares.lisp.

Method: name ((minimizer multi-dimensional-minimizer-fdf))

The name of the minimizer.

Source

minimization-multi.lisp.

Method: name ((minimizer multi-dimensional-minimizer-f))

The name of the minimizer.

Source

minimization-multi.lisp.

Method: name ((solver multi-dimensional-root-solver-fdf))

The name of the solver.

Source

roots-multi.lisp.

Method: name ((solver multi-dimensional-root-solver-f))

The name of the solver.

Source

roots-multi.lisp.

Method: name ((minimizer one-dimensional-minimizer))

The name of the minimizer.

Source

minimization-one.lisp.

Method: name ((solver one-dimensional-root-solver-fdf))

The name of the solver.

Source

roots-one.lisp.

Method: name ((solver one-dimensional-root-solver-f))

The name of the solver.

Source

roots-one.lisp.

Method: name ((wavelet wavelet))

The name of the wavelet family.

Source

wavelet.lisp.

Method: name ((object spline))

The name of the interpolation type.

Source

types.lisp.

Method: name ((interpolation interpolation))

The name of the interpolation type.

Source

types.lisp.

Method: name ((control ode-control))

The name of the control function.

Source

control.lisp.

Method: name ((object ode-stepper))

The name of the stepping function.

Source

stepping.lisp.

Method: name ((instance quasi-random-number-generator))
Source

quasi.lisp.

Method: name ((rng-instance random-number-generator))
Source

generators.lisp.

Reader Method: name ((condition obsolete-gsl-version))
Source

defmfun-single.lisp.

Target Slot

name.

Generic Function: non-negative-p (a)

All elements of a are non-negative.

Package

gsll.

Source

both.lisp.

Methods
Method: non-negative-p ((a vector-single-float))
Method: non-negative-p ((a vector-double-float))
Method: non-negative-p ((a vector-complex-single-float))
Method: non-negative-p ((a vector-complex-double-float))
Method: non-negative-p ((a vector-signed-byte-8))
Method: non-negative-p ((a vector-unsigned-byte-8))
Method: non-negative-p ((a vector-signed-byte-16))
Method: non-negative-p ((a vector-unsigned-byte-16))
Method: non-negative-p ((a vector-signed-byte-32))
Method: non-negative-p ((a vector-unsigned-byte-32))
Method: non-negative-p ((a vector-signed-byte-64))
Method: non-negative-p ((a vector-unsigned-byte-64))
Method: non-negative-p ((a matrix-single-float))
Method: non-negative-p ((a matrix-double-float))
Method: non-negative-p ((a matrix-complex-single-float))
Method: non-negative-p ((a matrix-complex-double-float))
Method: non-negative-p ((a matrix-signed-byte-8))
Method: non-negative-p ((a matrix-unsigned-byte-8))
Method: non-negative-p ((a matrix-signed-byte-16))
Method: non-negative-p ((a matrix-unsigned-byte-16))
Method: non-negative-p ((a matrix-signed-byte-32))
Method: non-negative-p ((a matrix-unsigned-byte-32))
Method: non-negative-p ((a matrix-signed-byte-64))
Method: non-negative-p ((a matrix-unsigned-byte-64))
Generic Function: order (object)

The order of the GSL object.

Package

gsll.

Source

mobject.lisp.

Methods
Method: order ((bspline basis-spline))
Source

basis-splines.lisp.

Method: order ((object chebyshev))

The order of Chebyshev series.

Source

chebyshev.lisp.

Generic Function: parameter (object parameter)

Get the value of the GSL parameter from the GSL object.

Package

gsll.

Source

generic.lisp.

Methods
Method: parameter ((object monte-carlo-vegas) parameter)
Source

monte-carlo.lisp.

Method: parameter ((object monte-carlo-miser) parameter)
Source

monte-carlo.lisp.

Generic Function: (setf parameter) (object parameter)

Set the value of the GSL parameter from the GSL object.

Package

gsll.

Source

generic.lisp.

Methods
Method: (setf parameter) ((object monte-carlo-vegas) parameter)
Source

monte-carlo.lisp.

Method: (setf parameter) ((object monte-carlo-miser) parameter)
Source

monte-carlo.lisp.

Generic Function: permute (p v &optional size stride)

Apply the permutation p to the elements of the
vector v considered as a row-vector acted on by a permutation matrix from the right, v’ = v P. The jth column of the permutation matrix P is given by the p_j-th column of the identity matrix. The permutation p and the vector v must have the same length.

Package

gsll.

Source

permutation.lisp.

Methods
Method: permute (p (data system-area-pointer) &optional size stride)

Apply the permutation p to the array data of size n with stride stride.

Method: permute ((p permutation) (v vector-single-float) &optional size stride)
Method: permute ((p permutation) (v vector-double-float) &optional size stride)
Method: permute ((p permutation) (v vector-complex-single-float) &optional size stride)
Method: permute ((p permutation) (v vector-complex-double-float) &optional size stride)
Method: permute ((p permutation) (v vector-signed-byte-8) &optional size stride)
Method: permute ((p permutation) (v vector-unsigned-byte-8) &optional size stride)
Method: permute ((p permutation) (v vector-signed-byte-16) &optional size stride)
Method: permute ((p permutation) (v vector-unsigned-byte-16) &optional size stride)
Method: permute ((p permutation) (v vector-signed-byte-32) &optional size stride)
Method: permute ((p permutation) (v vector-unsigned-byte-32) &optional size stride)
Method: permute ((p permutation) (v vector-signed-byte-64) &optional size stride)
Method: permute ((p permutation) (v vector-unsigned-byte-64) &optional size stride)
Generic Function: permute-inverse (p v &optional size stride)

Apply the permutation p to the elements of the vector v considered as a row-vector acted on by a permutation matrix from the right, v’ = v P. The jth column of the permutation matrix P is given by the p_j-th column of the identity matrix. The permutation p and the vector v must have the same length.

Package

gsll.

Source

permutation.lisp.

Methods
Method: permute-inverse (p (data system-area-pointer) &optional size stride)

Apply the inverse of the permutation p to the array data of size n with stride.

Method: permute-inverse ((p permutation) (v vector-single-float) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-double-float) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-complex-single-float) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-complex-double-float) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-signed-byte-8) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-unsigned-byte-8) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-signed-byte-16) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-unsigned-byte-16) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-signed-byte-32) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-unsigned-byte-32) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-signed-byte-64) &optional size stride)
Method: permute-inverse ((p permutation) (v vector-unsigned-byte-64) &optional size stride)
Generic Function: psi (x)

The psi, or digamma, function.

Package

gsll.

Source

psi.lisp.

Methods
Method: psi ((x float))

Domain: x /= 0.0, -1.0, -2.0, ...

Method: psi ((n integer))

Domain: n integer, n > 0.

Generic Function: psi-1 (x)

The Trigamma function.

Package

gsll.

Source

psi.lisp.

Methods
Method: psi-1 ((x float))

Domain: x /= 0.0, -1.0, -2.0, ...

Method: psi-1 ((n integer))

Domain: n integer, n > 0.

Generic Function: quantile (sorted-data fraction)

A quantile value of sorted-data. The
elements of the array must be in ascending numerical order. The quantile is determined by a fraction between 0 and 1. For
example, to compute the value of the 75th percentile
’fraction should have the value 0.75.
There are no checks to see whether the data are sorted, so the function #’sort should always be used first.
hbox{quantile} = (1 - delta) x_i + delta x_{i+1}
where i is floor((n - 1)f) and delta is (n-1)f - i.
Thus the minimum value of the array (data[0*stride]) is given by ’fraction equal to zero, the maximum value (data[(n-1)*stride]) is given by ’fraction equal to one and the median value is given by ’fraction equal to 0.5. Since the algorithm for computing quantiles involves interpolation this function always returns a floating-point number, even for integer data types.

Package

gsll.

Source

median-percentile.lisp.

Methods
Method: quantile ((sorted-data vector-single-float) fraction)
Method: quantile ((sorted-data vector-double-float) fraction)
Method: quantile ((sorted-data vector-signed-byte-8) fraction)
Method: quantile ((sorted-data vector-unsigned-byte-8) fraction)
Method: quantile ((sorted-data vector-signed-byte-16) fraction)
Method: quantile ((sorted-data vector-unsigned-byte-16) fraction)
Method: quantile ((sorted-data vector-signed-byte-32) fraction)
Method: quantile ((sorted-data vector-unsigned-byte-32) fraction)
Method: quantile ((sorted-data vector-signed-byte-64) fraction)
Method: quantile ((sorted-data vector-unsigned-byte-64) fraction)
Generic Function: range (histogram i)

Find the upper and lower range limits of the i-th
bin of the histogram. If the index i is valid then the corresponding range limits are stored in lower and upper.
The lower limit is inclusive (i.e. events with this coordinate are included in the bin) and the upper limit is exclusive (i.e. events with the coordinate of the upper limit are excluded and fall in the neighboring higher bin, if it exists).
If i lies outside the valid range of indices for
the histogram, then the error input-domain is signalled.

Package

gsll.

Source

updating-accessing.lisp.

Methods
Method: range ((histogram histogram) i)
Method: range ((histogram histogram2d) i)
Generic Function: rank-1-update (alpha x y a)

The rank-1 update A = alpha x y^T + A of the matrix A.

Package

gsll.

Source

blas2.lisp.

Methods
Method: rank-1-update (alpha (x vector-single-float) (y vector-single-float) (a matrix-single-float))
Method: rank-1-update (alpha (x vector-double-float) (y vector-double-float) (a matrix-double-float))
Method: rank-1-update (alpha (x vector-complex-single-float) (y vector-complex-single-float) (a matrix-complex-single-float))
Method: rank-1-update (alpha (x vector-complex-double-float) (y vector-complex-double-float) (a matrix-complex-double-float))
Generic Function: rng-state (rng-instance)

A pointer to the state of generator.

Package

gsll.

Source

generators.lisp.

Methods
Method: rng-state ((instance quasi-random-number-generator))
Source

quasi.lisp.

Method: rng-state ((rng-instance random-number-generator))
Generic Function: row (matrix i &optional vector)

Copy the elements of the ith row of the matrix
into the vector. The length of the vector must be the same as the length of the row.

Package

gsll.

Source

matrix.lisp.

Methods
Method: row ((matrix matrix-single-float) i &optional vector)
Method: row ((matrix matrix-double-float) i &optional vector)
Method: row ((matrix matrix-complex-single-float) i &optional vector)
Method: row ((matrix matrix-complex-double-float) i &optional vector)
Method: row ((matrix matrix-signed-byte-8) i &optional vector)
Method: row ((matrix matrix-unsigned-byte-8) i &optional vector)
Method: row ((matrix matrix-signed-byte-16) i &optional vector)
Method: row ((matrix matrix-unsigned-byte-16) i &optional vector)
Method: row ((matrix matrix-signed-byte-32) i &optional vector)
Method: row ((matrix matrix-unsigned-byte-32) i &optional vector)
Method: row ((matrix matrix-signed-byte-64) i &optional vector)
Method: row ((matrix matrix-unsigned-byte-64) i &optional vector)
Generic Function: (setf row) (matrix i)

Copy the elements of the vector into the jth row of the matrix. The length of the vector must be the same as the length of the row.

Package

gsll.

Source

matrix.lisp.

Methods
Method: (setf row) ((matrix matrix-single-float) i)
Method: (setf row) ((matrix matrix-double-float) i)
Method: (setf row) ((matrix matrix-complex-single-float) i)
Method: (setf row) ((matrix matrix-complex-double-float) i)
Method: (setf row) ((matrix matrix-signed-byte-8) i)
Method: (setf row) ((matrix matrix-unsigned-byte-8) i)
Method: (setf row) ((matrix matrix-signed-byte-16) i)
Method: (setf row) ((matrix matrix-unsigned-byte-16) i)
Method: (setf row) ((matrix matrix-signed-byte-32) i)
Method: (setf row) ((matrix matrix-unsigned-byte-32) i)
Method: (setf row) ((matrix matrix-signed-byte-64) i)
Method: (setf row) ((matrix matrix-unsigned-byte-64) i)
Generic Function: sample (source distribution &key src dest base probability n1 n2 tt n sum probabilities mu table alpha theta a b vector nu nu1 nu2 zeta sigma c beta sigma-x sigma-y rho upperbound &allow-other-keys)

Sample from the probability distribution.

Package

gsll.

Source

generators.lisp.

Methods
Method: sample ((source random-number-generator) (pdf histogram2d-pdf) &key)
Source

probability-distribution.lisp.

Method: sample ((source random-number-generator) (pdf histogram-pdf) &key)
Source

probability-distribution.lisp.

Method: sample ((value number) (pdf histogram2d-pdf) &key)
Source

probability-distribution.lisp.

Method: sample ((value number) (pdf histogram-pdf) &key)

Given a uniform random number (source) between zero and one, compute a single random sample from the probability distribution ’pdf. The algorithm used to compute the sample s is given by s = range[i] + delta * (range[i+1] - range[i])
where i is the index which satisfies
sum[i] <= value < sum[i+1] and delta is
(value - sum[i])/(sum[i+1] - sum[i]).

Source

probability-distribution.lisp.

Method: sample ((generator random-number-generator) (type (eql :random-sample)) &key src dest)

Like :choose-random, but samples k items from the original array of n items src with replacement, so the same object can appear more than once in the output sequence dest. There is no requirement that k be less than n in this case.

Source

shuffling-sampling.lisp.

Method: sample ((generator random-number-generator) (type (eql :choose-random)) &key src dest)

Fill the array destarr[k] with k objects taken randomly from the n elements of the array src[0...n-1]. The output of the random number generator r is used to make the selection. The algorithm ensures all possible samples are equally likely, assuming a perfect source of randomness.

The objects are sampled without replacement, thus each object can only appear once in destarr[k]. It is required that k be less than or equal to n. The objects in destarr will be in the
same relative order as those in src. You will need to call with :shuffle if you want to randomize the order.

Source

shuffling-sampling.lisp.

Method: sample ((generator random-number-generator) (type (eql :shuffle)) &key base)

Randomly shuffle the order of n objects, each of
size size, stored in the array base[0...n-1]. The
output of the random number generator r is used to produce the permutation. The algorithm generates all possible n!
permutations with equal probability, assuming a perfect source of random numbers.

Source

shuffling-sampling.lisp.

Method: sample ((generator random-number-generator) (type (eql :logarithmic)) &key probability)

A random integer from the logarithmic distribution.
The probability distribution for logarithmic random variates is p(k) = {-1 over log(1-p)} {left( p^k over k right)} for k >= 1.

Source

logarithmic.lisp.

Method: sample ((generator random-number-generator) (type (eql :hypergeometric)) &key n1 n2 tt)

A random integer from the hypergeometric
distribution. The probability distribution for hypergeometric random variates is
p(k) = C(n_1, k) C(n_2, t - k) / C(n_1 + n_2, t)
where C(a,b) = a!/(b!(a-b)!) and
t <= n_1 + n_2. The domain of k is
max(0,t-n_2), ..., min(t,n_1).
If a population contains n_1 elements of “type 1” and n_2 elements of “type 2” then the hypergeometric distribution gives the probability of obtaining k elements of “type 1” in t samples from the population without replacement.

Source

hypergeometric.lisp.

Method: sample ((generator random-number-generator) (type (eql :geometric)) &key probability)

A random integer from the geometric distribution,
the number of independent trials with probability p until the first success. The probability distribution for geometric variates is p(k) = p (1-p)^{k-1} for k >= 1.
Note that the distribution begins with k=1 with this definition. There is another convention in which the exponent k-1 is replaced by k.

Source

geometric.lisp.

Method: sample ((generator random-number-generator) (type (eql :pascal)) &key probability n)

A random integer from the Pascal distribution. The
Pascal distribution is simply a negative binomial distribution with an integer value of n.
p(k) = {(n + k - 1)! over k! (n - 1)! } p^n (1-p)^k
k >= 0.

Source

negative-binomial.lisp.

Method: sample ((generator random-number-generator) (type (eql :negative-binomial)) &key probability n)

A random integer from the negative binomial
distribution, the number of failures occurring before n successes in independent trials with probability of success. The probability distribution for negative binomial variates is given by probability (p):
p(k) = {Gamma(n + k) over Gamma(k+1) Gamma(n) } p^n (1-p)^k Note that n is not required to be an integer.

Source

negative-binomial.lisp.

Method: sample ((generator random-number-generator) (type (eql :multinomial)) &key sum probabilities n)

Returns an array n of (dim0 probabilities) random variates from a multinomial distribution. The sum of the array n is specified
by sum. The distribution function is
P(n_1, n_2, ..., n_K) =
(N!/(n_1! n_2! ... n_K!)) p_1^n_1 p_2^n_2 ... p_K^n_K
where (n_1, n_2, ..., n_K) are nonnegative integers with sum_{k=1}^K n_k = N, and (p_1, p_2, ..., p_K)
is a probability distribution with sum p_i = 1.
If the array p[K] is not normalized then its entries will be
treated as weights and normalized appropriately.
Random variates are generated using the conditional binomial method (see C.S. David, "The computer generation of multinomial random variates," Comp. Stat. Data Anal. 16 (1993) 205–217 for details).

Source

multinomial.lisp.

Method: sample ((generator random-number-generator) (type (eql :bernoulli)) &key probability)

Returns either 0 or 1, the result of a Bernoulli trial with probability p. The probability distribution for a Bernoulli trial is
p(0) = 1 - p
p(1) = p.

Source

bernoulli.lisp.

Method: sample ((generator random-number-generator) (type (eql :poisson)) &key mu)

A random integer from the Poisson distribution with mean mu. The probability distribution for Poisson variates is p(k) = {mu^k over k!} exp(-mu)
k >= 0.

Source

poisson.lisp.

Method: sample ((generator random-number-generator) (type (eql :discrete)) &key table)

Generate discrete random numbers.

Source

discrete.lisp.

Method: sample ((generator random-number-generator) (type (eql :dirichlet)) &key alpha theta)

An array of K=(length alpha) random variates from a Dirichlet distribution of order K-1. The distribution function is p(theta_1,ldots,theta_K) , dtheta_1 cdots dtheta_K =
{1 over Z} prod_{i=1}^{K} theta_i^{alpha_i - 1}
; delta(1 -sum_{i=1}^K theta_i) dtheta_1 cdots dtheta_K theta_i >= 0 and alpha_i >= 0.
The delta function ensures that sum theta_i = 1.
The normalization factor Z is
Z = {prod_{i=1}^K Gamma(alpha_i) over Gamma( sum_{i=1}^K alpha_i)} The random variates are generated by sampling K values
from gamma distributions with parameters a=alpha_i, b=1,
and renormalizing.
See A.M. Law, W.D. Kelton, "Simulation Modeling and Analysis" (1991).

Source

dirichlet.lisp.

Method: sample ((generator random-number-generator) (type (eql :gumbel2)) &key a b)

A random variate from the Type-2 Gumbel
distribution, p(x) dx = a b x^{-a-1} exp(-b x^{-a}) dx for 0 < x < infty.

Source

gumbel2.lisp.

Method: sample ((generator random-number-generator) (type (eql :gumbel1)) &key a b)

A random variate from the Type-1 Gumbel distribution,
p(x) dx = a b exp(-(b exp(-ax) + ax)) dx for -infty < x < infty.

Source

gumbel1.lisp.

Method: sample ((generator random-number-generator) (type (eql :weibull)) &key a b)

A random variate from the Weibull distribution. The distribution function is p(x) dx = {b over a^b} x^{b-1} exp(-(x/a)^b) dx
for x >= 0.

Source

weibull.lisp.

Method: sample ((generator random-number-generator) (type (eql :direction-nd)) &key vector)

A random direction vector v = (x_1,x_2,...,x_n) in n dimensions,
where n is the length of the vector x passed in. The vector is normalized such that |v|^2 = x_1^2 + x_2^2 + ... + x_n^2 = 1. The method
uses the fact that a multivariate gaussian distribution is spherically symmetric. Each component is generated to have a gaussian distribution,
and then the components are normalized. The method is described by
Knuth, v2, 3rd ed, p135–136, and attributed to G. W. Brown, Modern
Mathematics for the Engineer (1956).

Source

spherical-vector.lisp.

Method: sample ((generator random-number-generator) (type (eql :direction-3d)) &key)

A random direction vector v =
(x,y,z) in three dimensions. The vector is normalized
such that |v|^2 = x^2 + y^2 + z^2 = 1. The method employed is
due to Robert E. Knop (CACM 13, 326 (1970)), and explained in Knuth, v2, 3rd ed, p136. It uses the surprising fact that the distribution projected along any axis is actually uniform (this is only true for 3 dimensions).

Source

spherical-vector.lisp.

Method: sample ((generator random-number-generator) (type (eql :direction-2d-trig-method)) &key)

A random direction vector v = (x,y) in
two dimensions. The vector is normalized such that |v|^2 = x^2 + y^2 = 1. Uses trigonometric functions.

Source

spherical-vector.lisp.

Method: sample ((generator random-number-generator) (type (eql :direction-2d)) &key)

A random direction vector v = (x,y) in
two dimensions. The vector is normalized such that |v|^2 = x^2 + y^2 = 1.

Source

spherical-vector.lisp.

Method: sample ((generator random-number-generator) (type (eql :pareto)) &key a b)

A random variate from the Pareto distribution of order a. The distribution function is
p(x) dx = (a/b) / (x/b)^{a+1} dx
x >= b.

Source

pareto.lisp.

Method: sample ((generator random-number-generator) (type (eql :logistic)) &key a)

A random variate from the logistic distribution. The distribution function is p(x) dx = { exp(-x/a) over a (1 + exp(-x/a))^2 } dx
for -infty < x < +infty.

Source

logistic.lisp.

Method: sample ((generator random-number-generator) (type (eql :beta)) &key a b)

A random variate from the beta distribution. The distribution function is p(x) dx = {Gamma(a+b) over Gamma(a) Gamma(b)} x^{a-1} (1-x)^{b-1} dx 0 <= x <= 1.

Source

beta.lisp.

Method: sample ((generator random-number-generator) (type (eql :tdist)) &key nu)

A random variate from the Student t-distribution. The distribution function is,
p(x) dx = {Gamma((nu + 1)/2) over sqrt{pi nu} Gamma(nu/2)} (1 + x^2/nu)^{-(nu + 1)/2} dx
for -infty < x < +infty.

Source

tdist.lisp.

Method: sample ((generator random-number-generator) (type (eql :fdist)) &key nu1 nu2)

A random variate from the F-distribution with degrees of freedom nu1 and nu2. The distribution function is
p(x) dx =
{ Gamma((nu_1 + nu_2)/2)
over Gamma(nu_1/2) Gamma(nu_2/2) }
nu_1^{nu_1/2} nu_2^{nu_2/2}
x^{nu_1/2 - 1} (nu_2 + nu_1 x)^{-nu_1/2 -nu_2/2}
for x >= 0.

Source

fdist.lisp.

Method: sample ((generator random-number-generator) (type (eql :chi-squared)) &key nu)

A random variate from the chi-squared distribution
with nu degrees of freedom. The distribution function is p(x) dx = {1 over 2 Gamma(nu/2) } (x/2)^{nu/2 - 1} exp(-x/2) dx x >= 0.

Source

chi-squared.lisp.

Method: sample ((generator random-number-generator) (type (eql :lognormal)) &key zeta sigma)

A random variate from the lognormal distribution.
The distribution function is
p(x) dx = {1 over x sqrt{2 pi sigma^2}} exp(-(ln(x) - zeta)^2/2 sigma^2) dx for x > 0.

Source

lognormal.lisp.

Method: sample ((generator random-number-generator) (type (eql :flat)) &key a b)

A random variate from the flat (uniform) distribution from a to b. The distribution is p(x) dx = {1 over (b-a)} dx
if a <= x < b, and 0 otherwise.

Source

flat.lisp.

Method: sample ((generator random-number-generator) (type (eql :gamma-mt)) &key a b)

A gamma variate using the Marsaglia-Tsang fast gamma method.

Source

gamma.lisp.

Method: sample ((generator random-number-generator) (type (eql :gamma)) &key a b)

A random variate from the gamma distribution.
The distribution function is
p(x) dx = {1 over Gamma(a) b^a} x^{a-1} e^{-x/b} dx
for x > 0. The gamma distribution with an integer parameter a
is known as the Erlang distribution. The variates are computed using the algorithms from Knuth (vol 2).

Source

gamma.lisp.

Method: sample ((generator random-number-generator) (type (eql :levy-skew)) &key c alpha beta)

A random variate from the Levy skew stable
distribution with scale c exponent alpha and skewness
parameter beta. The skewness parameter must lie in the range
[-1,1]. The Levy skew stable probability distribution is defined
by a fourier transform,
p(x) = {1 over 2 pi} int_{-infty}^{+infty} dt
exp(-it x - |c t|^alpha (1-i beta sign(t) tan(pialpha/2)))
When alpha = 1 the term tan(pi alpha/2) is replaced by
-(2/pi)log|t|. There is no explicit solution for the form of
p(x)} and the library does not define a corresponding pdf
function. For alpha = 2 the distribution reduces to a Gaussian distribution with sigma = sqrt{2} c and the skewness parameter
has no effect. For alpha < 1 the tails of the distribution
become extremely wide. The symmetric distribution corresponds to beta = 0. The algorithm only works for 0 < alpha le 2.

Source

levy.lisp.

Method: sample ((generator random-number-generator) (type (eql :levy)) &key c alpha)

A random variate from the Levy symmetric stable
distribution with scale c and exponent alpha. The symmetric stable probability distribution is defined by a fourier transform, p(x) = {1 over 2 pi} int_{-infty}^{+infty} dt exp(-it x - |c t|^alpha) There is no explicit solution for the form of p(x) and the
library does not define a corresponding pdf function. For
alpha = 1 the distribution reduces to the Cauchy distribution. For alpha = 2 it is a Gaussian distribution with sigma = sqrt{2} c
For alpha < 1 the tails of the distribution become extremely wide. The algorithm only works for 0 < alpha <= 2.

Source

levy.lisp.

Method: sample ((generator random-number-generator) (type (eql :landau)) &key)

A random variate from the Landau distribution. The
probability distribution for Landau random variates is defined analytically by the complex integral,
{1 over {2 pi i}} int_{c-iinfty}^{c+iinfty} ds, exp(s log(s) + x s) For numerical purposes it is more convenient to use the following equivalent form of the integral,
p(x) = (1/pi) int_0^infty dt exp(-t log(t) - x t) sin(pi t).

Source

landau.lisp.

Method: sample ((generator random-number-generator) (type (eql :rayleigh-tail)) &key a sigma)

A random variate from the tail of the Rayleigh distribution with scale parameter sigma and a lower limit of a. The distribution is
p(x) dx = {x over sigma^2} exp ((a^2 - x^2) /(2 sigma^2)) dx for x > a.

Source

rayleigh-tail.lisp.

Method: sample ((generator random-number-generator) (type (eql :rayleigh)) &key sigma)

A random variate from the Rayleigh distribution with scale parameter sigma. The distribution is
p(x) dx = {x over sigma^2} exp(- x^2/(2 sigma^2)) dx for x > 0.

Source

rayleigh.lisp.

Method: sample ((generator random-number-generator) (type (eql :cauchy)) &key a)

A random variate from the Cauchy distribution with
scale parameter a. The probability distribution for Cauchy random variates is,
p(x) dx = {1 over api (1 + (x/a)^2) } dx
for x in the range -infty to +infty. The Cauchy distribution is also known as the Lorentz distribution.

Source

cauchy.lisp.

Method: sample ((generator random-number-generator) (type (eql :exponential-power)) &key a b)

A random variate from the exponential power distribution with scale parameter a and exponent b. The distribution is p(x) dx = {1 over 2 a Gamma(1+1/b)} exp(-|x/a|^b) dx for x >= 0. For b = 1 this reduces to the Laplace distribution. For b = 2 it has the same form as a gaussian distribution, but with a = sqrt{2} sigma.

Source

exponential-power.lisp.

Method: sample ((generator random-number-generator) (type (eql :laplace)) &key a)

A random variate from the Laplace distribution with width a. The distribution is
p(x) dx = {1 over 2 a} exp(-|x/a|) dx
for -infty < x < infty.

Source

laplace.lisp.

Method: sample ((generator random-number-generator) (type (eql :exponential)) &key mu)

A random variate from the exponential distribution with mean mu. The distribution is
p(x) dx = {1 over mu} exp(-x/mu) dx
x >= 0.

Source

exponential.lisp.

Method: sample ((generator random-number-generator) (type (eql :bivariate-gaussian)) &key sigma-x sigma-y rho)

Generate a pair of correlated Gaussian variates, with
mean zero, correlation coefficient rho and standard deviations sigma_x and sigma_y in the x and y directions.
The probability distribution for bivariate Gaussian random variates is, p(x,y) dx dy
= {1 over 2 pi sigma_x sigma_y sqrt{1-rho^2}}
exp left(-{(x^2/sigma_x^2 + y^2/sigma_y^2 - 2 rho x y/(sigma_xsigma_y)) over 2(1-rho^2)}right) dx dy
for x,y in the range -infty to +infty. The
correlation coefficient rho should lie between 1 and -1.

Source

gaussian-bivariate.lisp.

Method: sample ((generator random-number-generator) (type (eql :ugaussian-tail)) &key a)

Equivalent to gaussian-tail with sigma=1.

Source

gaussian-tail.lisp.

Method: sample ((generator random-number-generator) (type (eql :gaussian-tail)) &key a sigma)

Random variates from the upper tail of a Gaussian
distribution with standard deviation sigma. The values returned
are larger than the lower limit a, which must be positive. The
method is based on Marsaglia’s famous rectangle-wedge-tail algorithm (Ann. Math. Stat. 32, 894–899 (1961)), with this aspect explained in Knuth, v2, 3rd ed, p139,586 (exercise 11).
The probability distribution for Gaussian tail random variates is,
p(x) dx = {1 over N(a;sigma) sqrt{2 pi sigma^2}}
exp (- x^2 / 2sigma^2) dx
for x > a where N(a;sigma) is the normalization constant,
N(a;sigma) = (1/2) erfc(a / sqrt(2 sigma^2)).

Source

gaussian-tail.lisp.

Method: sample ((generator random-number-generator) (type (eql :ugaussian-ratio-method)) &key)

Compute results for the unit Gaussian distribution,
equivalent to the #’sample :gaussian-ration-method with a standard deviation of one, sigma = 1.

Source

gaussian.lisp.

Method: sample ((generator random-number-generator) (type (eql :ugaussian)) &key)

Compute results for the unit Gaussian distribution,
equivalent to the #’sample :gaussian with a standard deviation of one, sigma = 1.

Source

gaussian.lisp.

Method: sample ((generator random-number-generator) (type (eql :gaussian-ratio-method)) &key sigma)

Compute a Gaussian random variate using the Kinderman-Monahan-Leva ratio method.

Source

gaussian.lisp.

Method: sample ((generator random-number-generator) (type (eql :gaussian-ziggurat)) &key sigma)

Compute a Gaussian random variate using the alternative Marsaglia-Tsang ziggurat method. The Ziggurat algorithm is the fastest available algorithm in most cases.

Source

gaussian.lisp.

Method: sample ((generator random-number-generator) (type (eql :gaussian)) &key sigma)

A Gaussian random variate, with mean zero and
standard deviation sigma. The probability distribution for Gaussian random variates is
p(x) dx = {1 over sqrt{2 pi sigma^2}} exp (-x^2 / 2sigma^2) dx for x in the range -infty to +infty. Use the
transformation z = mu + x on the numbers returned by
this function to obtain a Gaussian distribution with mean
mu. This function uses the Box-Mueller algorithm which requires two calls to the random number generator r.

Source

gaussian.lisp.

Method: sample ((source random-number-generator) (type (eql :uniform-fixnum)) &key upperbound)

Generate a random integer from 0 to upperbound-1 inclusive.
All integers in the range are equally likely, regardless
of the generator used. An offset correction is applied so that zero is always returned with the correct probability, for any minimum value of the underlying generator. If upperbound is larger than the range of the generator then the function signals an error.

Method: sample ((source random-number-generator) (type (eql :uniform>0)) &key)

Return a positive double precision floating point number uniformly distributed in the range (0,1), excluding both 0.0 and 1.0. The number is obtained by sampling the generator with the algorithm for type ’uniform until a non-zero value is obtained. You can use this function if you need to avoid a singularity at 0.0.

Method: sample ((source random-number-generator) (type (eql :uniform)) &key)

A double precision floating point number uniformly
distributed in the range [0,1). The range includes 0.0 but excludes 1.0. The value is typically obtained by dividing the result of #’get-random-number by (+ (rng-max generator) 1.0) in double precision. Some generators compute this ratio internally so that they can provide floating point numbers with more than 32 bits of randomness (the maximum number of bits that can be portably represented in a single :ulong.

Generic Function: scale (alpha x)

Rescale the vector x by the multiplicative factor alpha.

Package

gsll.

Source

blas1.lisp.

Methods
Method: scale ((alpha float) (x vector-complex-double-float))
Method: scale ((alpha float) (x vector-complex-single-float))
Method: scale ((alpha float) (x vector-single-float))
Method: scale ((alpha float) (x vector-double-float))
Method: scale ((alpha complex) (x vector-complex-single-float))
Method: scale ((alpha complex) (x vector-complex-double-float))
Generic Function: set-all (object value)

Set all elements to the value.

Package

gsll.

Source

both.lisp.

Methods
Method: set-all ((object vector-single-float) value)
Method: set-all ((object vector-double-float) value)
Method: set-all ((object vector-complex-single-float) value)
Method: set-all ((object vector-complex-double-float) value)
Method: set-all ((object vector-signed-byte-8) value)
Method: set-all ((object vector-unsigned-byte-8) value)
Method: set-all ((object vector-signed-byte-16) value)
Method: set-all ((object vector-unsigned-byte-16) value)
Method: set-all ((object vector-signed-byte-32) value)
Method: set-all ((object vector-unsigned-byte-32) value)
Method: set-all ((object vector-signed-byte-64) value)
Method: set-all ((object vector-unsigned-byte-64) value)
Method: set-all ((object matrix-single-float) value)
Method: set-all ((object matrix-double-float) value)
Method: set-all ((object matrix-complex-single-float) value)
Method: set-all ((object matrix-complex-double-float) value)
Method: set-all ((object matrix-signed-byte-8) value)
Method: set-all ((object matrix-unsigned-byte-8) value)
Method: set-all ((object matrix-signed-byte-16) value)
Method: set-all ((object matrix-unsigned-byte-16) value)
Method: set-all ((object matrix-signed-byte-32) value)
Method: set-all ((object matrix-unsigned-byte-32) value)
Method: set-all ((object matrix-signed-byte-64) value)
Method: set-all ((object matrix-unsigned-byte-64) value)
Generic Function: set-basis (object index)

Set the index element to 1, and the rest to 0.

Package

gsll.

Source

vector.lisp.

Methods
Method: set-basis ((object vector-single-float) index)
Method: set-basis ((object vector-double-float) index)
Method: set-basis ((object vector-complex-single-float) index)
Method: set-basis ((object vector-complex-double-float) index)
Method: set-basis ((object vector-signed-byte-8) index)
Method: set-basis ((object vector-unsigned-byte-8) index)
Method: set-basis ((object vector-signed-byte-16) index)
Method: set-basis ((object vector-unsigned-byte-16) index)
Method: set-basis ((object vector-signed-byte-32) index)
Method: set-basis ((object vector-unsigned-byte-32) index)
Method: set-basis ((object vector-signed-byte-64) index)
Method: set-basis ((object vector-unsigned-byte-64) index)
Generic Function: set-identity (matrix)

Set the elements of the matrix to the
corresponding elements of the identity matrix, m(i,j) = delta(i,j), i.e. a unit diagonal with all off-diagonal elements zero. This applies to both square and rectangular matrices.

Package

gsll.

Source

matrix.lisp.

Methods
Method: set-identity ((p permutation))

Initialize the permutation p to the identity, i.e. (0,1,2,...,n-1).

Source

permutation.lisp.

Method: set-identity ((matrix matrix-single-float))
Method: set-identity ((matrix matrix-double-float))
Method: set-identity ((matrix matrix-complex-single-float))
Method: set-identity ((matrix matrix-complex-double-float))
Method: set-identity ((matrix matrix-signed-byte-8))
Method: set-identity ((matrix matrix-unsigned-byte-8))
Method: set-identity ((matrix matrix-signed-byte-16))
Method: set-identity ((matrix matrix-unsigned-byte-16))
Method: set-identity ((matrix matrix-signed-byte-32))
Method: set-identity ((matrix matrix-unsigned-byte-32))
Method: set-identity ((matrix matrix-signed-byte-64))
Method: set-identity ((matrix matrix-unsigned-byte-64))
Generic Function: set-ranges-uniform (histogram minimum maximum &optional minimum2 maximum2)

Set the ranges of the existing histogram h to cover
the range xmin to xmax uniformly. The values of the
histogram bins are reset to zero. The bin ranges are shown in the table below,
bin[0] corresponds to xmin <= x < xmin + d
bin[1] corresponds to xmin + d <= x < xmin + 2 d
......
bin[n-1] corresponds to xmin + (n-1)d <= x < xmax
where d is the bin spacing, d = (xmax-xmin)/n.

Package

gsll.

Source

histogram.lisp.

Methods
Method: set-ranges-uniform ((histogram histogram2d) x-minimum x-maximum &optional y-minimum y-maximum)
Method: set-ranges-uniform ((histogram histogram) minimum maximum &optional minimum2 maximum2)
Generic Function: set-zero (object)

Set all elements to 0.

Package

gsll.

Source

both.lisp.

Methods
Method: set-zero ((histogram histogram2d))

Reset all the bins in the histogram to zero.

Source

updating-accessing.lisp.

Method: set-zero ((histogram histogram))

Reset all the bins in the histogram to zero.

Source

updating-accessing.lisp.

Method: set-zero ((object vector-single-float))
Method: set-zero ((object vector-double-float))
Method: set-zero ((object vector-complex-single-float))
Method: set-zero ((object vector-complex-double-float))
Method: set-zero ((object vector-signed-byte-8))
Method: set-zero ((object vector-unsigned-byte-8))
Method: set-zero ((object vector-signed-byte-16))
Method: set-zero ((object vector-unsigned-byte-16))
Method: set-zero ((object vector-signed-byte-32))
Method: set-zero ((object vector-unsigned-byte-32))
Method: set-zero ((object vector-signed-byte-64))
Method: set-zero ((object vector-unsigned-byte-64))
Method: set-zero ((object matrix-single-float))
Method: set-zero ((object matrix-double-float))
Method: set-zero ((object matrix-complex-single-float))
Method: set-zero ((object matrix-complex-double-float))
Method: set-zero ((object matrix-signed-byte-8))
Method: set-zero ((object matrix-unsigned-byte-8))
Method: set-zero ((object matrix-signed-byte-16))
Method: set-zero ((object matrix-unsigned-byte-16))
Method: set-zero ((object matrix-signed-byte-32))
Method: set-zero ((object matrix-unsigned-byte-32))
Method: set-zero ((object matrix-signed-byte-64))
Method: set-zero ((object matrix-unsigned-byte-64))
Generic Function: shift (histogram offset)

Shift the contents of the bins of histogram h by the constant offset, i.e. h’_1(i) = h_1(i) + offset.

Package

gsll.

Source

operations.lisp.

Methods
Method: shift ((histogram histogram2d) offset)
Method: shift ((histogram histogram) offset)
Generic Function: sigma (histogram)

The standard deviation of the histogrammed variable, where the histogram is regarded as a probability distribution. Negative bin values are ignored for the purposes of this calculation. The resolution of the result is limited by the bin width. For 2d histograms, the sigmas are returned as multiple values.

Package

gsll.

Source

statistics.lisp.

Methods
Method: sigma ((histogram histogram2d))
Method: sigma ((histogram histogram))
Generic Function: size (object)

The size of the GSL object.

Package

gsll.

Source

mobject.lisp.

Methods
Method: size ((minimizer multi-dimensional-minimizer-f))

A minimizer-specific characteristic size for the minimizer.

Source

minimization-multi.lisp.

Method: size ((chebyshev chebyshev))

The length of the Chebyshev coefficient array.

Source

chebyshev.lisp.

Method: size ((instance quasi-random-number-generator))
Source

quasi.lisp.

Method: size ((rng-instance random-number-generator))
Source

generators.lisp.

Method: size ((c combination))

The number of elements (k) in the combination c.

Source

combination.lisp.

Method: size ((p permutation))

The size of the permutation p.

Source

permutation.lisp.

Method: size ((object array))
Method: size ((object foreign-array))
Generic Function: skewness (data &optional mean standard-deviation)

The skewness of data, defined as skew = (1/N) sum ((x_i - Hatmu)/Hatsigma)^3 where x_i are the elements of the dataset data. The skewness measures the asymmetry of the tails of a distribution. If mean and standard deviation are supplied, compute skewness of the dataset data using the given values skew = (1/N) sum ((x_i - mean)/sd)^3. This is useful if you have
already computed the mean and standard deviation of data and want to avoid recomputing them.

Package

gsll.

Source

higher-moments.lisp.

Methods
Method: skewness ((data vector-single-float) &optional mean standard-deviation)
Method: skewness ((data vector-double-float) &optional mean standard-deviation)
Method: skewness ((data vector-signed-byte-8) &optional mean standard-deviation)
Method: skewness ((data vector-unsigned-byte-8) &optional mean standard-deviation)
Method: skewness ((data vector-signed-byte-16) &optional mean standard-deviation)
Method: skewness ((data vector-unsigned-byte-16) &optional mean standard-deviation)
Method: skewness ((data vector-signed-byte-32) &optional mean standard-deviation)
Method: skewness ((data vector-unsigned-byte-32) &optional mean standard-deviation)
Method: skewness ((data vector-signed-byte-64) &optional mean standard-deviation)
Method: skewness ((data vector-unsigned-byte-64) &optional mean standard-deviation)
Generic Function: solution (object)

The current value of the independent variable(s) that solves this object.

Package

gsll.

Source

generic.lisp.

Methods
Method: solution ((solver nonlinear-fdffit))

The current best-fit parameters.

Source

nonlinear-least-squares.lisp.

Method: solution ((solver nonlinear-ffit))

The current best-fit parameters.

Source

nonlinear-least-squares.lisp.

Method: solution ((minimizer multi-dimensional-minimizer-fdf))

The current best estimate of the location of the minimum.

Source

minimization-multi.lisp.

Method: solution ((minimizer multi-dimensional-minimizer-f))

The current best estimate of the location of the minimum.

Source

minimization-multi.lisp.

Method: solution ((solver multi-dimensional-root-solver-fdf))

The current estimate of the root for the solver.

Source

roots-multi.lisp.

Method: solution ((solver multi-dimensional-root-solver-f))

The current estimate of the root for the solver.

Source

roots-multi.lisp.

Method: solution ((minimizer one-dimensional-minimizer))

The current estimate of the position of the minimum for the minimizer.

Source

minimization-one.lisp.

Method: solution ((solver one-dimensional-root-solver-fdf))

The current estimate of the root for the solver.

Source

roots-one.lisp.

Method: solution ((solver one-dimensional-root-solver-f))

The current estimate of the root for the solver.

Source

roots-one.lisp.

Generic Function: sort-eigenvalues-eigenvectors (eigenvalues eigenvectors sort-type)

Simultaneously sort the eigenvalues stored in the vector
eigenvalues and the corresponding real eigenvectors stored in the columns of the matrix eigenvectors into ascending or descending order according to the value of the parameter sort-type: :value-ascending, :value-descending, :absolute-ascending, :absolute-descending.

Package

gsll.

Source

symmetric-hermitian.lisp.

Methods
Method: sort-eigenvalues-eigenvectors ((eigenvalues vector-double-float) (eigenvectors matrix-double-float) sort-type)
Method: sort-eigenvalues-eigenvectors ((eigenvalues vector-complex-double-float) (eigenvectors matrix-complex-double-float) sort-type)
Generic Function: sort-index (permutation vector)

Indirectly sort the n elements of the array vector with stride stride into ascending order, storing the resulting permutation. The latter must be created with the same size as the vector.
The elements of permutation give the index of the
array element which would have been stored in that position if the array had been sorted in place. The array data is not changed.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-index ((permutation permutation) (vector vector-single-float))
Method: sort-index ((permutation permutation) (vector vector-double-float))
Method: sort-index ((permutation permutation) (vector vector-signed-byte-8))
Method: sort-index ((permutation permutation) (vector vector-unsigned-byte-8))
Method: sort-index ((permutation permutation) (vector vector-signed-byte-16))
Method: sort-index ((permutation permutation) (vector vector-unsigned-byte-16))
Method: sort-index ((permutation permutation) (vector vector-signed-byte-32))
Method: sort-index ((permutation permutation) (vector vector-unsigned-byte-32))
Method: sort-index ((permutation permutation) (vector vector-signed-byte-64))
Method: sort-index ((permutation permutation) (vector vector-unsigned-byte-64))
Generic Function: sort-largest (dest v)

Find the largest elements of the vector v and put them into dest, which must be shorter than v.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-largest (dest (v vector-single-float))
Method: sort-largest (dest (v vector-double-float))
Method: sort-largest (dest (v vector-signed-byte-8))
Method: sort-largest (dest (v vector-unsigned-byte-8))
Method: sort-largest (dest (v vector-signed-byte-16))
Method: sort-largest (dest (v vector-unsigned-byte-16))
Method: sort-largest (dest (v vector-signed-byte-32))
Method: sort-largest (dest (v vector-unsigned-byte-32))
Method: sort-largest (dest (v vector-signed-byte-64))
Method: sort-largest (dest (v vector-unsigned-byte-64))
Method: sort-largest (dest (v matrix-single-float))
Method: sort-largest (dest (v matrix-double-float))
Method: sort-largest (dest (v matrix-signed-byte-8))
Method: sort-largest (dest (v matrix-unsigned-byte-8))
Method: sort-largest (dest (v matrix-signed-byte-16))
Method: sort-largest (dest (v matrix-unsigned-byte-16))
Method: sort-largest (dest (v matrix-signed-byte-32))
Method: sort-largest (dest (v matrix-unsigned-byte-32))
Method: sort-largest (dest (v matrix-signed-byte-64))
Method: sort-largest (dest (v matrix-unsigned-byte-64))
Generic Function: sort-largest-index (v &optional size-or-array)

The indices of the largest elements of the vector. If size-or-array is an integer, it is the number of smallest elements. If it is an array of sizet elements, it is filled.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-largest-index ((v vector-single-float) &optional size-or-array)
Method: sort-largest-index ((v vector-double-float) &optional size-or-array)
Method: sort-largest-index ((v vector-signed-byte-8) &optional size-or-array)
Method: sort-largest-index ((v vector-unsigned-byte-8) &optional size-or-array)
Method: sort-largest-index ((v vector-signed-byte-16) &optional size-or-array)
Method: sort-largest-index ((v vector-unsigned-byte-16) &optional size-or-array)
Method: sort-largest-index ((v vector-signed-byte-32) &optional size-or-array)
Method: sort-largest-index ((v vector-unsigned-byte-32) &optional size-or-array)
Method: sort-largest-index ((v vector-signed-byte-64) &optional size-or-array)
Method: sort-largest-index ((v vector-unsigned-byte-64) &optional size-or-array)
Generic Function: sort-smallest (dest v)

Find the smallest elements of the vector v and put them into dest, which must be shorter than v.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-smallest (dest (v vector-single-float))
Method: sort-smallest (dest (v vector-double-float))
Method: sort-smallest (dest (v vector-signed-byte-8))
Method: sort-smallest (dest (v vector-unsigned-byte-8))
Method: sort-smallest (dest (v vector-signed-byte-16))
Method: sort-smallest (dest (v vector-unsigned-byte-16))
Method: sort-smallest (dest (v vector-signed-byte-32))
Method: sort-smallest (dest (v vector-unsigned-byte-32))
Method: sort-smallest (dest (v vector-signed-byte-64))
Method: sort-smallest (dest (v vector-unsigned-byte-64))
Method: sort-smallest (dest (v matrix-single-float))
Method: sort-smallest (dest (v matrix-double-float))
Method: sort-smallest (dest (v matrix-signed-byte-8))
Method: sort-smallest (dest (v matrix-unsigned-byte-8))
Method: sort-smallest (dest (v matrix-signed-byte-16))
Method: sort-smallest (dest (v matrix-unsigned-byte-16))
Method: sort-smallest (dest (v matrix-signed-byte-32))
Method: sort-smallest (dest (v matrix-unsigned-byte-32))
Method: sort-smallest (dest (v matrix-signed-byte-64))
Method: sort-smallest (dest (v matrix-unsigned-byte-64))
Generic Function: sort-smallest-index (v &optional size-or-array)

The indices of the smallest elements of the vector. If size-or-array is an integer, it is the number of smallest elements. If it is an array of :sizet elements, it is filled.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-smallest-index ((v vector-single-float) &optional size-or-array)
Method: sort-smallest-index ((v vector-double-float) &optional size-or-array)
Method: sort-smallest-index ((v vector-signed-byte-8) &optional size-or-array)
Method: sort-smallest-index ((v vector-unsigned-byte-8) &optional size-or-array)
Method: sort-smallest-index ((v vector-signed-byte-16) &optional size-or-array)
Method: sort-smallest-index ((v vector-unsigned-byte-16) &optional size-or-array)
Method: sort-smallest-index ((v vector-signed-byte-32) &optional size-or-array)
Method: sort-smallest-index ((v vector-unsigned-byte-32) &optional size-or-array)
Method: sort-smallest-index ((v vector-signed-byte-64) &optional size-or-array)
Method: sort-smallest-index ((v vector-unsigned-byte-64) &optional size-or-array)
Generic Function: sort-vector (v)

Sort the elements of the vector v into ascending numerical order.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-vector ((v vector-single-float))
Method: sort-vector ((v vector-double-float))
Method: sort-vector ((v vector-signed-byte-8))
Method: sort-vector ((v vector-unsigned-byte-8))
Method: sort-vector ((v vector-signed-byte-16))
Method: sort-vector ((v vector-unsigned-byte-16))
Method: sort-vector ((v vector-signed-byte-32))
Method: sort-vector ((v vector-unsigned-byte-32))
Method: sort-vector ((v vector-signed-byte-64))
Method: sort-vector ((v vector-unsigned-byte-64))
Generic Function: sort-vector-index (permutation vector)

Indirectly sort the elements of the vector v into
ascending order, storing the resulting permutation in p. The elements of p give the index of the vector element which would have been stored in that position if the vector had been sorted in place. The first element of p gives the index of the least element in v and the last element of p gives the index of the
greatest element in v. The vector v is not changed.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-vector-index ((permutation permutation) (vector vector-single-float))
Method: sort-vector-index ((permutation permutation) (vector vector-double-float))
Method: sort-vector-index ((permutation permutation) (vector vector-signed-byte-8))
Method: sort-vector-index ((permutation permutation) (vector vector-unsigned-byte-8))
Method: sort-vector-index ((permutation permutation) (vector vector-signed-byte-16))
Method: sort-vector-index ((permutation permutation) (vector vector-unsigned-byte-16))
Method: sort-vector-index ((permutation permutation) (vector vector-signed-byte-32))
Method: sort-vector-index ((permutation permutation) (vector vector-unsigned-byte-32))
Method: sort-vector-index ((permutation permutation) (vector vector-signed-byte-64))
Method: sort-vector-index ((permutation permutation) (vector vector-unsigned-byte-64))
Generic Function: sort-vector-largest (dest v)

Find the largest elements of the vector v and put them into dest, which must be shorter than v.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-vector-largest (dest (v vector-single-float))
Method: sort-vector-largest (dest (v vector-double-float))
Method: sort-vector-largest (dest (v vector-signed-byte-8))
Method: sort-vector-largest (dest (v vector-unsigned-byte-8))
Method: sort-vector-largest (dest (v vector-signed-byte-16))
Method: sort-vector-largest (dest (v vector-unsigned-byte-16))
Method: sort-vector-largest (dest (v vector-signed-byte-32))
Method: sort-vector-largest (dest (v vector-unsigned-byte-32))
Method: sort-vector-largest (dest (v vector-signed-byte-64))
Method: sort-vector-largest (dest (v vector-unsigned-byte-64))
Generic Function: sort-vector-largest-index (combination v)

The indices of the largest elements of the vector stored, returned as a CL vector of element type fixnum. If indices is a positive initeger, a vector will be allocated and returned. If it is a CL vector,
it will be filled with the indices.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-vector-largest-index (combination (v vector-single-float))
Method: sort-vector-largest-index (combination (v vector-double-float))
Method: sort-vector-largest-index (combination (v vector-signed-byte-8))
Method: sort-vector-largest-index (combination (v vector-unsigned-byte-8))
Method: sort-vector-largest-index (combination (v vector-signed-byte-16))
Method: sort-vector-largest-index (combination (v vector-unsigned-byte-16))
Method: sort-vector-largest-index (combination (v vector-signed-byte-32))
Method: sort-vector-largest-index (combination (v vector-unsigned-byte-32))
Method: sort-vector-largest-index (combination (v vector-signed-byte-64))
Method: sort-vector-largest-index (combination (v vector-unsigned-byte-64))
Generic Function: sort-vector-smallest (dest v)

Find the smallest elements of the vector v and put them into dest, which must be shorter than v.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-vector-smallest (dest (v vector-single-float))
Method: sort-vector-smallest (dest (v vector-double-float))
Method: sort-vector-smallest (dest (v vector-signed-byte-8))
Method: sort-vector-smallest (dest (v vector-unsigned-byte-8))
Method: sort-vector-smallest (dest (v vector-signed-byte-16))
Method: sort-vector-smallest (dest (v vector-unsigned-byte-16))
Method: sort-vector-smallest (dest (v vector-signed-byte-32))
Method: sort-vector-smallest (dest (v vector-unsigned-byte-32))
Method: sort-vector-smallest (dest (v vector-signed-byte-64))
Method: sort-vector-smallest (dest (v vector-unsigned-byte-64))
Generic Function: sort-vector-smallest-index (combination v)

The indices of the smallest elements of the vector stored, returned as a CL vector of element type fixnum. If indices is a positive initeger, a vector will be allocated and returned. If it is a CL vector,
it will be filled with the indices.

Package

gsll.

Source

sorting.lisp.

Methods
Method: sort-vector-smallest-index (combination (v vector-single-float))
Method: sort-vector-smallest-index (combination (v vector-double-float))
Method: sort-vector-smallest-index (combination (v vector-signed-byte-8))
Method: sort-vector-smallest-index (combination (v vector-unsigned-byte-8))
Method: sort-vector-smallest-index (combination (v vector-signed-byte-16))
Method: sort-vector-smallest-index (combination (v vector-unsigned-byte-16))
Method: sort-vector-smallest-index (combination (v vector-signed-byte-32))
Method: sort-vector-smallest-index (combination (v vector-unsigned-byte-32))
Method: sort-vector-smallest-index (combination (v vector-signed-byte-64))
Method: sort-vector-smallest-index (combination (v vector-unsigned-byte-64))
Generic Function: standard-deviation (array &optional mean)

The standard deviation, square root of the variance.
If the mean value is known, it may be supplied which will use more efficient routines to compute the variance.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: standard-deviation ((array vector-single-float) &optional mean)
Method: standard-deviation ((array vector-double-float) &optional mean)
Method: standard-deviation ((array vector-signed-byte-8) &optional mean)
Method: standard-deviation ((array vector-unsigned-byte-8) &optional mean)
Method: standard-deviation ((array vector-signed-byte-16) &optional mean)
Method: standard-deviation ((array vector-unsigned-byte-16) &optional mean)
Method: standard-deviation ((array vector-signed-byte-32) &optional mean)
Method: standard-deviation ((array vector-unsigned-byte-32) &optional mean)
Method: standard-deviation ((array vector-signed-byte-64) &optional mean)
Method: standard-deviation ((array vector-unsigned-byte-64) &optional mean)
Method: standard-deviation ((array matrix-single-float) &optional mean)
Method: standard-deviation ((array matrix-double-float) &optional mean)
Method: standard-deviation ((array matrix-signed-byte-8) &optional mean)
Method: standard-deviation ((array matrix-unsigned-byte-8) &optional mean)
Method: standard-deviation ((array matrix-signed-byte-16) &optional mean)
Method: standard-deviation ((array matrix-unsigned-byte-16) &optional mean)
Method: standard-deviation ((array matrix-signed-byte-32) &optional mean)
Method: standard-deviation ((array matrix-unsigned-byte-32) &optional mean)
Method: standard-deviation ((array matrix-signed-byte-64) &optional mean)
Method: standard-deviation ((array matrix-unsigned-byte-64) &optional mean)
Generic Function: standard-deviation-with-fixed-mean (array mean)

The standard deviation of data for a fixed population mean. The result is the square root of the corresponding variance function.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: standard-deviation-with-fixed-mean ((array vector-single-float) mean)
Method: standard-deviation-with-fixed-mean ((array vector-double-float) mean)
Method: standard-deviation-with-fixed-mean ((array vector-signed-byte-8) mean)
Method: standard-deviation-with-fixed-mean ((array vector-unsigned-byte-8) mean)
Method: standard-deviation-with-fixed-mean ((array vector-signed-byte-16) mean)
Method: standard-deviation-with-fixed-mean ((array vector-unsigned-byte-16) mean)
Method: standard-deviation-with-fixed-mean ((array vector-signed-byte-32) mean)
Method: standard-deviation-with-fixed-mean ((array vector-unsigned-byte-32) mean)
Method: standard-deviation-with-fixed-mean ((array vector-signed-byte-64) mean)
Method: standard-deviation-with-fixed-mean ((array vector-unsigned-byte-64) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-single-float) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-double-float) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-signed-byte-8) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-unsigned-byte-8) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-signed-byte-16) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-unsigned-byte-16) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-signed-byte-32) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-unsigned-byte-32) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-signed-byte-64) mean)
Method: standard-deviation-with-fixed-mean ((array matrix-unsigned-byte-64) mean)
Generic Function: sum (histogram)

The sum of all bin values. Negative bin values are included in the sum.

Package

gsll.

Source

statistics.lisp.

Methods
Method: sum ((histogram histogram2d))
Method: sum ((histogram histogram))
Generic Function: swap (a b)

Exchange the elements of a and b
by copying. The two must have the same dimensions.

Package

gsll.

Source

both.lisp.

Methods
Method: swap ((a vector-single-float) (b vector-single-float))
Method: swap ((a vector-double-float) (b vector-double-float))
Method: swap ((a vector-complex-single-float) (b vector-complex-single-float))
Method: swap ((a vector-complex-double-float) (b vector-complex-double-float))
Method: swap ((a vector-signed-byte-8) (b vector-signed-byte-8))
Method: swap ((a vector-unsigned-byte-8) (b vector-unsigned-byte-8))
Method: swap ((a vector-signed-byte-16) (b vector-signed-byte-16))
Method: swap ((a vector-unsigned-byte-16) (b vector-unsigned-byte-16))
Method: swap ((a vector-signed-byte-32) (b vector-signed-byte-32))
Method: swap ((a vector-unsigned-byte-32) (b vector-unsigned-byte-32))
Method: swap ((a vector-signed-byte-64) (b vector-signed-byte-64))
Method: swap ((a vector-unsigned-byte-64) (b vector-unsigned-byte-64))
Method: swap ((a matrix-single-float) (b matrix-single-float))
Method: swap ((a matrix-double-float) (b matrix-double-float))
Method: swap ((a matrix-complex-single-float) (b matrix-complex-single-float))
Method: swap ((a matrix-complex-double-float) (b matrix-complex-double-float))
Method: swap ((a matrix-signed-byte-8) (b matrix-signed-byte-8))
Method: swap ((a matrix-unsigned-byte-8) (b matrix-unsigned-byte-8))
Method: swap ((a matrix-signed-byte-16) (b matrix-signed-byte-16))
Method: swap ((a matrix-unsigned-byte-16) (b matrix-unsigned-byte-16))
Method: swap ((a matrix-signed-byte-32) (b matrix-signed-byte-32))
Method: swap ((a matrix-unsigned-byte-32) (b matrix-unsigned-byte-32))
Method: swap ((a matrix-signed-byte-64) (b matrix-signed-byte-64))
Method: swap ((a matrix-unsigned-byte-64) (b matrix-unsigned-byte-64))
Generic Function: swap-columns (matrix i j)

Exchange the ith and jth columns of the matrix in-place.

Package

gsll.

Source

matrix.lisp.

Methods
Method: swap-columns ((matrix matrix-single-float) i j)
Method: swap-columns ((matrix matrix-double-float) i j)
Method: swap-columns ((matrix matrix-complex-single-float) i j)
Method: swap-columns ((matrix matrix-complex-double-float) i j)
Method: swap-columns ((matrix matrix-signed-byte-8) i j)
Method: swap-columns ((matrix matrix-unsigned-byte-8) i j)
Method: swap-columns ((matrix matrix-signed-byte-16) i j)
Method: swap-columns ((matrix matrix-unsigned-byte-16) i j)
Method: swap-columns ((matrix matrix-signed-byte-32) i j)
Method: swap-columns ((matrix matrix-unsigned-byte-32) i j)
Method: swap-columns ((matrix matrix-signed-byte-64) i j)
Method: swap-columns ((matrix matrix-unsigned-byte-64) i j)
Generic Function: swap-elements (vec i j)

Exchange the i-th and j-th elements of the vector vec in-place.

Package

gsll.

Source

vector.lisp.

Methods
Method: swap-elements ((p permutation) i j)

Exchanges the ith and jth elements of the permutation p.

Source

permutation.lisp.

Method: swap-elements ((vec vector-single-float) i j)
Method: swap-elements ((vec vector-double-float) i j)
Method: swap-elements ((vec vector-complex-single-float) i j)
Method: swap-elements ((vec vector-complex-double-float) i j)
Method: swap-elements ((vec vector-signed-byte-8) i j)
Method: swap-elements ((vec vector-unsigned-byte-8) i j)
Method: swap-elements ((vec vector-signed-byte-16) i j)
Method: swap-elements ((vec vector-unsigned-byte-16) i j)
Method: swap-elements ((vec vector-signed-byte-32) i j)
Method: swap-elements ((vec vector-unsigned-byte-32) i j)
Method: swap-elements ((vec vector-signed-byte-64) i j)
Method: swap-elements ((vec vector-unsigned-byte-64) i j)
Generic Function: swap-row-column (matrix i j)

Exchange the ith row and jth column of the
matrix in-place. The matrix must be square for this operation to be possible.

Package

gsll.

Source

matrix.lisp.

Methods
Method: swap-row-column ((matrix matrix-single-float) i j)
Method: swap-row-column ((matrix matrix-double-float) i j)
Method: swap-row-column ((matrix matrix-complex-single-float) i j)
Method: swap-row-column ((matrix matrix-complex-double-float) i j)
Method: swap-row-column ((matrix matrix-signed-byte-8) i j)
Method: swap-row-column ((matrix matrix-unsigned-byte-8) i j)
Method: swap-row-column ((matrix matrix-signed-byte-16) i j)
Method: swap-row-column ((matrix matrix-unsigned-byte-16) i j)
Method: swap-row-column ((matrix matrix-signed-byte-32) i j)
Method: swap-row-column ((matrix matrix-unsigned-byte-32) i j)
Method: swap-row-column ((matrix matrix-signed-byte-64) i j)
Method: swap-row-column ((matrix matrix-unsigned-byte-64) i j)
Generic Function: swap-rows (matrix i j)

Exchange the ith and jth rows of the matrix in-place.

Package

gsll.

Source

matrix.lisp.

Methods
Method: swap-rows ((matrix matrix-single-float) i j)
Method: swap-rows ((matrix matrix-double-float) i j)
Method: swap-rows ((matrix matrix-complex-single-float) i j)
Method: swap-rows ((matrix matrix-complex-double-float) i j)
Method: swap-rows ((matrix matrix-signed-byte-8) i j)
Method: swap-rows ((matrix matrix-unsigned-byte-8) i j)
Method: swap-rows ((matrix matrix-signed-byte-16) i j)
Method: swap-rows ((matrix matrix-unsigned-byte-16) i j)
Method: swap-rows ((matrix matrix-signed-byte-32) i j)
Method: swap-rows ((matrix matrix-unsigned-byte-32) i j)
Method: swap-rows ((matrix matrix-signed-byte-64) i j)
Method: swap-rows ((matrix matrix-unsigned-byte-64) i j)
Generic Function: symmetric-rank-1-update (x a &optional alpha beta uplo trans)

If the first argument is a vector,
the symmetric rank-1 update A = alpha x x^T + A of the symmetric matrix A. Since the matrix A is symmetric only its upper half or lower half need to be stored. When Uplo is :Upper then the upper triangle and diagonal of A are used, and when Uplo is :Lower then the lower triangle and diagonal of A are used. If the first argument is a matrix, a rank-k update of the symmetric matrix C, C = alpha A A^T + beta C when Trans is CblasNoTrans and C = alpha A^T A + beta C when Trans is CblasTrans. Since the matrix C is symmetric only its upper half or lower half need to be stored. When Uplo is CblasUpper then the upper triangle and diagonal of C are used, and when Uplo is CblasLower then the lower triangle and diagonal of C are used.

Package

gsll.

Source

blas2.lisp.

Methods
Method: symmetric-rank-1-update ((a matrix-complex-double-float) (c matrix-complex-double-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-1-update ((a matrix-complex-single-float) (c matrix-complex-single-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-1-update ((a matrix-double-float) (c matrix-double-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-1-update ((a matrix-single-float) (c matrix-single-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-1-update ((x vector-single-float) (a matrix-single-float) &optional alpha beta uplo trans)
Method: symmetric-rank-1-update ((x vector-double-float) (a matrix-double-float) &optional alpha beta uplo trans)
Generic Function: symmetric-rank-2-update (x y a &optional alpha beta uplo trans)

If the first two arguments are vectors, compute
the symmetric rank-2 update A = alpha x y^T + alpha y x^T + A of the symmetric matrix A. Since the matrix A is symmetric only its upper half or lower half need to be stored. When Uplo is :upper then the upper triangle and diagonal of A are used, and when Uplo is :lower then the lower triangle and diagonal of A are used. If the first two arguments are matrices, compute a rank-2k update of the symmetric matrix C, C = alpha A B^T + alpha B A^T + beta C when Trans is :notrans and C = alpha A^T B + alpha B^T A + beta C when Trans is :trans. Since the matrix C is symmetric only its upper half or lower half need to be stored. When Uplo is :upper then the upper triangle and diagonal of C are used, and when Uplo is :lower then the lower triangle and diagonal of C are used.

Package

gsll.

Source

blas2.lisp.

Methods
Method: symmetric-rank-2-update ((a matrix-complex-double-float) (b matrix-complex-double-float) (c matrix-complex-double-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-2-update ((a matrix-complex-single-float) (b matrix-complex-single-float) (c matrix-complex-single-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-2-update ((a matrix-double-float) (b matrix-double-float) (c matrix-double-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-2-update ((a matrix-single-float) (b matrix-single-float) (c matrix-single-float) &optional alpha beta uplo trans)
Source

blas3.lisp.

Method: symmetric-rank-2-update ((x vector-single-float) (y vector-single-float) (a matrix-single-float) &optional alpha beta uplo trans)
Method: symmetric-rank-2-update ((x vector-double-float) (y vector-double-float) (a matrix-double-float) &optional alpha beta uplo trans)
Generic Function: tridiagonal-decomposition (a tau)

Factorizes the symmetric square matrix or hermitian matrix A into the symmetric tridiagonal decomposition Q T Q^T. On output the diagonal and subdiagonal part of the input matrix A contain the tridiagonal matrix T. The remaining lower triangular part of the input matrix contains the Householder vectors which, together with the Householder coefficients tau, encode the orthogonal matrix
Q. This storage scheme is the same as used by lapack. The
upper triangular part of A is not referenced.

Package

gsll.

Source

diagonal.lisp.

Methods
Method: tridiagonal-decomposition ((a matrix-double-float) tau)
Method: tridiagonal-decomposition ((a matrix-complex-double-float) tau)
Generic Function: tridiagonal-unpack (a tau q diag subdiag)

Unpacks the encoded symmetric tridiagonal decomposition
(A, tau) obtained from #’tridiagonal-decomposition into the orthogonal or unitary matrix Q, the vector of diagonal elements diag and the real vector of subdiagonal elements subdiag.

Package

gsll.

Source

diagonal.lisp.

Methods
Method: tridiagonal-unpack ((a matrix-double-float) tau q diag subdiag)
Method: tridiagonal-unpack ((a matrix-complex-double-float) tau q diag subdiag)
Generic Function: tridiagonal-unpack-t (a diag subdiag)

Unpack the diagonal and subdiagonal of the encoded symmetric tridiagonal decomposition (A, tau) obtained from #’tridiagonal-decomposition into the real vectors diag and subdiag.

Package

gsll.

Source

diagonal.lisp.

Methods
Method: tridiagonal-unpack-t ((a matrix-double-float) diag subdiag)
Method: tridiagonal-unpack-t ((a matrix-complex-double-float) diag subdiag)
Generic Function: validp (object)

Check that the object p is valid.

Package

gsll.

Source

permutation.lisp.

Methods
Method: validp ((combination combination))

Check that the combination is valid. The k
elements should lie in the range 0 to n-1, with each value occurring once at most and in increasing order.

Source

combination.lisp.

Method: validp ((permutation permutation))

Check that the permutation p is valid. The n
elements should contain each of the numbers 0 to n-1 once and only once.

Generic Function: variance (array &optional mean)

The estimated, or sample, variance of data. The
estimated variance is denoted by Hatsigma^2 and is defined by Hatsigma^2 = (1/(N-1)) sum (x_i - Hatmu)^2
where x_i are the elements of the dataset data. Note that
the normalization factor of 1/(N-1) results from the derivation of Hatsigma^2 as an unbiased estimator of the population variance sigma^2. For samples drawn from a gaussian distribution the variance of Hatsigma^2 itself is 2 sigma^4 / N.
If the mean value is known, it may be supplied which will use more efficient routines to compute the variance.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: variance ((array vector-single-float) &optional mean)
Method: variance ((array vector-double-float) &optional mean)
Method: variance ((array vector-signed-byte-8) &optional mean)
Method: variance ((array vector-unsigned-byte-8) &optional mean)
Method: variance ((array vector-signed-byte-16) &optional mean)
Method: variance ((array vector-unsigned-byte-16) &optional mean)
Method: variance ((array vector-signed-byte-32) &optional mean)
Method: variance ((array vector-unsigned-byte-32) &optional mean)
Method: variance ((array vector-signed-byte-64) &optional mean)
Method: variance ((array vector-unsigned-byte-64) &optional mean)
Method: variance ((array matrix-single-float) &optional mean)
Method: variance ((array matrix-double-float) &optional mean)
Method: variance ((array matrix-signed-byte-8) &optional mean)
Method: variance ((array matrix-unsigned-byte-8) &optional mean)
Method: variance ((array matrix-signed-byte-16) &optional mean)
Method: variance ((array matrix-unsigned-byte-16) &optional mean)
Method: variance ((array matrix-signed-byte-32) &optional mean)
Method: variance ((array matrix-unsigned-byte-32) &optional mean)
Method: variance ((array matrix-signed-byte-64) &optional mean)
Method: variance ((array matrix-unsigned-byte-64) &optional mean)
Generic Function: variance-with-fixed-mean (array mean)

An unbiased estimate of the variance of
data when the population mean of the underlying distribution is known a priori. In this case the estimator for the variance uses the factor 1/N and the sample mean
Hatmu is replaced by the known population mean mu, Hatsigma^2 = (1/N) sum (x_i - mu)^2.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: variance-with-fixed-mean ((array vector-single-float) mean)
Method: variance-with-fixed-mean ((array vector-double-float) mean)
Method: variance-with-fixed-mean ((array vector-signed-byte-8) mean)
Method: variance-with-fixed-mean ((array vector-unsigned-byte-8) mean)
Method: variance-with-fixed-mean ((array vector-signed-byte-16) mean)
Method: variance-with-fixed-mean ((array vector-unsigned-byte-16) mean)
Method: variance-with-fixed-mean ((array vector-signed-byte-32) mean)
Method: variance-with-fixed-mean ((array vector-unsigned-byte-32) mean)
Method: variance-with-fixed-mean ((array vector-signed-byte-64) mean)
Method: variance-with-fixed-mean ((array vector-unsigned-byte-64) mean)
Method: variance-with-fixed-mean ((array matrix-single-float) mean)
Method: variance-with-fixed-mean ((array matrix-double-float) mean)
Method: variance-with-fixed-mean ((array matrix-signed-byte-8) mean)
Method: variance-with-fixed-mean ((array matrix-unsigned-byte-8) mean)
Method: variance-with-fixed-mean ((array matrix-signed-byte-16) mean)
Method: variance-with-fixed-mean ((array matrix-unsigned-byte-16) mean)
Method: variance-with-fixed-mean ((array matrix-signed-byte-32) mean)
Method: variance-with-fixed-mean ((array matrix-unsigned-byte-32) mean)
Method: variance-with-fixed-mean ((array matrix-signed-byte-64) mean)
Method: variance-with-fixed-mean ((array matrix-unsigned-byte-64) mean)
Generic Function: vector-reverse (vec)

Reverse the order of the elements of the vector vec.

Package

gsll.

Source

vector.lisp.

Methods
Method: vector-reverse ((vec vector-single-float))
Method: vector-reverse ((vec vector-double-float))
Method: vector-reverse ((vec vector-complex-single-float))
Method: vector-reverse ((vec vector-complex-double-float))
Method: vector-reverse ((vec vector-signed-byte-8))
Method: vector-reverse ((vec vector-unsigned-byte-8))
Method: vector-reverse ((vec vector-signed-byte-16))
Method: vector-reverse ((vec vector-unsigned-byte-16))
Method: vector-reverse ((vec vector-signed-byte-32))
Method: vector-reverse ((vec vector-unsigned-byte-32))
Method: vector-reverse ((vec vector-signed-byte-64))
Method: vector-reverse ((vec vector-unsigned-byte-64))
Generic Function: weighted-absolute-deviation (data weights &optional mean)

The weighted absolute deviation from the weighted mean, defined as
absdev = (sum w_i |x_i - Hatmu|) / (sum w_i).

Package

gsll.

Source

absolute-deviation.lisp.

Methods
Method: weighted-absolute-deviation ((data vector-single-float) (weights vector-single-float) &optional mean)
Method: weighted-absolute-deviation ((data vector-double-float) (weights vector-double-float) &optional mean)
Generic Function: weighted-kurtosis (data weights &optional mean standard-deviation)

The weighted kurtosis of the dataset.
kurtosis = ((sum w_i ((x_i - xbar)/sigma)^4) / (sum w_i)) - 3.

Package

gsll.

Source

higher-moments.lisp.

Methods
Method: weighted-kurtosis ((data vector-single-float) (weights vector-single-float) &optional mean standard-deviation)
Method: weighted-kurtosis ((data vector-double-float) (weights vector-double-float) &optional mean standard-deviation)
Generic Function: weighted-mean (array weights)

The weighted mean of the dataset, using the set of weights The weighted mean is defined as
Hatmu = (sum w_i x_i) / (sum w_i).

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: weighted-mean ((array vector-single-float) (weights vector-single-float))
Method: weighted-mean ((array vector-double-float) (weights vector-double-float))
Method: weighted-mean ((array matrix-single-float) (weights matrix-single-float))
Method: weighted-mean ((array matrix-double-float) (weights matrix-double-float))
Generic Function: weighted-skewness (data weights &optional mean standard-deviation)

The weighted skewness of the dataset.
skew = (sum w_i ((x_i - xbar)/sigma)^3) / (sum w_i).

Package

gsll.

Source

higher-moments.lisp.

Methods
Method: weighted-skewness ((data vector-single-float) (weights vector-single-float) &optional mean standard-deviation)
Method: weighted-skewness ((data vector-double-float) (weights vector-double-float) &optional mean standard-deviation)
Generic Function: weighted-standard-deviation (array weights &optional mean)

The weighted standard deviation, square root of the variance.
If the mean value is known, it may be supplied which will use more efficient routines to compute the variance.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: weighted-standard-deviation ((array vector-single-float) (weights vector-single-float) &optional mean)
Method: weighted-standard-deviation ((array vector-double-float) (weights vector-double-float) &optional mean)
Method: weighted-standard-deviation ((array matrix-single-float) (weights matrix-single-float) &optional mean)
Method: weighted-standard-deviation ((array matrix-double-float) (weights matrix-double-float) &optional mean)
Generic Function: weighted-standard-deviation-with-fixed-mean (array weights mean)

The square root of the corresponding variance function #’weighted-variance-with-fixed-mean.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: weighted-standard-deviation-with-fixed-mean ((array vector-single-float) (weights vector-single-float) mean)
Method: weighted-standard-deviation-with-fixed-mean ((array vector-double-float) (weights vector-double-float) mean)
Method: weighted-standard-deviation-with-fixed-mean ((array matrix-single-float) (weights matrix-single-float) mean)
Method: weighted-standard-deviation-with-fixed-mean ((array matrix-double-float) (weights matrix-double-float) mean)
Generic Function: weighted-variance (array weights &optional mean)

The estimated variance of a weighted dataset is defined as Hatsigma^2 = ((sum w_i)/((sum w_i)^2 - sum (w_i^2)))
sum w_i (x_i - Hatmu)^2
Note that this expression reduces to an unweighted variance with the familiar 1/(N-1) factor when there are N equal non-zero weights. If the mean value is known, it may be supplied which will use more efficient routines to compute the variance.

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: weighted-variance ((array vector-single-float) (weights vector-single-float) &optional mean)
Method: weighted-variance ((array vector-double-float) (weights vector-double-float) &optional mean)
Method: weighted-variance ((array matrix-single-float) (weights matrix-single-float) &optional mean)
Method: weighted-variance ((array matrix-double-float) (weights matrix-double-float) &optional mean)
Generic Function: weighted-variance-with-fixed-mean (array weights mean)

An unbiased estimate of the variance of weighted
dataset when the population mean of the underlying distribution is known a priori. In this case the estimator for the variance replaces the sample mean Hatmu by the known population mean mu,
Hatsigma^2 = (sum w_i (x_i - mu)^2) / (sum w_i).

Package

gsll.

Source

mean-variance.lisp.

Methods
Method: weighted-variance-with-fixed-mean ((array vector-single-float) (weights vector-single-float) mean)
Method: weighted-variance-with-fixed-mean ((array vector-double-float) (weights vector-double-float) mean)
Method: weighted-variance-with-fixed-mean ((array matrix-single-float) (weights matrix-single-float) mean)
Method: weighted-variance-with-fixed-mean ((array matrix-double-float) (weights matrix-double-float) mean)
Generic Function: zeta (x)

The Riemann zeta function zeta(n).

Package

gsll.

Source

zeta.lisp.

Methods
Method: zeta ((s float))

The Riemann zeta function zeta(s) for arbitrary s, s ne 1.

Method: zeta ((n integer))

The Riemann zeta function zeta(n) for integer n, n ne 1.

Generic Function: zeta-1 (x)

zeta - 1.

Package

gsll.

Source

zeta.lisp.

Methods
Method: zeta-1 ((s float))

The Riemann zeta function zeta(s) for arbitrary s, s ne 1.

Method: zeta-1 ((n integer))

The Riemann zeta function zeta(n) for integer n, n ne 1.


5.1.8 Standalone methods

Method: aref ((histogram histogram) &rest indices)

Return the contents of the i-th bin of the histogram. If i lies outside the valid range of index for the histogram then an error (input-domain) is signalled.

Package

grid.

Source

updating-accessing.lisp.

Method: aref ((histogram histogram2d) &rest indices)

Return the contents of the i-th, j-th bin of the 2D histogram. If either index lies outside the valid range of index for the histogram then an error (input-domain) is signalled.

Package

grid.

Source

updating-accessing.lisp.

Method: aref ((p permutation) &rest indices)
Package

grid.

Source

permutation.lisp.

Method: copy ((source random-number-generator) &key destination &allow-other-keys)
Package

grid.

Source

generators.lisp.

Method: copy ((source histogram) &key destination &allow-other-keys)
Package

grid.

Source

histogram.lisp.

Method: copy ((source quasi-random-number-generator) &key destination &allow-other-keys)
Package

grid.

Source

quasi.lisp.

Method: copy ((source histogram2d) &key destination &allow-other-keys)
Package

grid.

Source

histogram.lisp.

Method: copy ((source permutation) &key grid-type destination &allow-other-keys)
Package

grid.

Source

permutation.lisp.

Method: copy ((source combination) &key grid-type destination &allow-other-keys)
Package

grid.

Source

combination.lisp.

Method: dimensions ((histogram histogram))

The number of bins in the histogram.

Package

grid.

Source

updating-accessing.lisp.

Method: dimensions ((histogram histogram2d))
Package

grid.

Source

updating-accessing.lisp.

Method: dimensions ((p permutation))
Package

grid.

Source

permutation.lisp.

Reader Method: dimensions ((callback-included callback-included))

automatically generated reader method

Package

grid.

Source

callback-included.lisp.

Target Slot

dimensions.

Method: initialize-instance :after ((object interpolation) &key mpointer size type xa ya)
Source

interpolation.lisp.

Method: initialize-instance :after ((object monte-carlo-plain) &key mpointer dim)
Source

monte-carlo.lisp.

Method: initialize-instance :after ((object eigen-genherm) &key mpointer n)
Source

generalized.lisp.

Method: initialize-instance :after ((object histogram-pdf) &key mpointer number-of-bins histogram)
Source

probability-distribution.lisp.

Method: initialize-instance :after ((object wavelet) &key mpointer type member)
Source

wavelet.lisp.

Method: initialize-instance :after ((object random-number-generator) &key mpointer rng-type value)
Source

generators.lisp.

Method: initialize-instance :after ((object eigen-symmv) &key mpointer n)
Source

symmetric-hermitian.lisp.

Method: initialize-instance :after ((object eigen-nonsymm) &key mpointer n)
Source

nonsymmetric.lisp.

Method: initialize-instance :after ((object multi-dimensional-root-solver-f) &key mpointer dimensions type functions initial)
Source

roots-multi.lisp.

Method: initialize-instance :after ((object yp-control) &key mpointer dydt-scaling y-scaling absolute-error relative-error)
Source

control.lisp.

Method: initialize-instance :after ((object basis-spline) &key mpointer order number-of-breakpoints)
Source

basis-splines.lisp.

Method: initialize-instance :after ((object fit-workspace) &key mpointer number-of-observations number-of-parameters)
Source

linear-least-squares.lisp.

Method: initialize-instance :after ((object qawo-table) &key mpointer n omega l trig)
Source

numerical-integration-with-tables.lisp.

Method: initialize-instance :after ((object multi-dimensional-root-solver-fdf) &key mpointer dimensions type functions initial)
Source

roots-multi.lisp.

Method: initialize-instance :after ((object acceleration) &key mpointer)
Source

lookup.lisp.

Method: initialize-instance :after ((object discrete-random) &key mpointer probabilities)
Source

discrete.lisp.

Method: initialize-instance :after ((object mathieu) &key mpointer n qmax)
Source

mathieu.lisp.

Method: initialize-instance :after ((object one-dimensional-root-solver-fdf) &key mpointer root-guess functions type)
Source

roots-one.lisp.

Method: initialize-instance :after ((object eigen-nonsymmv) &key mpointer n)
Source

nonsymmetric.lisp.

Method: initialize-instance :after ((object polynomial-complex-workspace) &key mpointer n)
Source

polynomial.lisp.

Method: initialize-instance :after ((object multi-dimensional-minimizer-fdf) &key mpointer tolerance step-size initial functions type dimensions)
Source

minimization-multi.lisp.

Method: initialize-instance :after ((object nonlinear-fdffit) &key mpointer dimensions solver-type functions initial-guess)
Source

nonlinear-least-squares.lisp.

Method: initialize-instance :after ((object hankel) &key mpointer xmax nu size)
Source

hankel.lisp.

Method: initialize-instance :after ((object multi-dimensional-minimizer-f) &key mpointer step-size initial functions type dimensions)
Source

minimization-multi.lisp.

Method: initialize-instance :after ((object histogram) &key mpointer number-of-bins ranges)
Source

histogram.lisp.

Method: initialize-instance :after ((object eigen-gensymmv) &key mpointer n)
Source

generalized.lisp.

Method: initialize-instance :after ((object wavelet-workspace) &key mpointer size)
Source

wavelet.lisp.

Method: initialize-instance :after ((object eigen-genv) &key mpointer n)
Source

nonsymmetric-generalized.lisp.

Method: initialize-instance :after ((object one-dimensional-root-solver-f) &key mpointer upper lower functions type)
Source

roots-one.lisp.

Method: initialize-instance :after ((object spline) &key mpointer size type xa ya)
Source

interpolation.lisp.

Method: initialize-instance :after ((object qaws-table) &key mpointer alpha beta mu nu)
Source

numerical-integration-with-tables.lisp.

Method: initialize-instance :after ((object integration-workspace) &key mpointer size)
Source

numerical-integration.lisp.

Method: initialize-instance :after ((object scaled-control) &key mpointer dimension absolute-scale absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: initialize-instance :after ((object levin) &key mpointer order)
Source

series-acceleration.lisp.

Method: initialize-instance :after ((object quasi-random-number-generator) &key mpointer rng-type dimension)
Source

quasi.lisp.

Method: initialize-instance :after ((object eigen-symm) &key mpointer n)
Source

symmetric-hermitian.lisp.

Method: initialize-instance :after ((object histogram2d) &key mpointer number-of-bins-y number-of-bins-x x-ranges y-ranges)
Source

histogram.lisp.

Method: initialize-instance :after ((object ode-stepper) &key mpointer type dimensions)
Source

stepping.lisp.

Method: initialize-instance :after ((object one-dimensional-minimizer) &key mpointer f-upper x-upper f-lower x-lower f-minimum x-minimum functions type)
Source

minimization-one.lisp.

Method: initialize-instance :after ((object eigen-gen) &key mpointer n)
Source

nonsymmetric-generalized.lisp.

Method: initialize-instance :after ((object eigen-herm) &key mpointer n)
Source

symmetric-hermitian.lisp.

Method: initialize-instance :after ((object eigen-genhermv) &key mpointer n)
Source

generalized.lisp.

Method: initialize-instance :after ((object monte-carlo-miser) &key mpointer dim)
Source

monte-carlo.lisp.

Method: initialize-instance :after ((object chebyshev) &key mpointer upper-limit lower-limit functions order)
Source

chebyshev.lisp.

Method: initialize-instance :after ((object ode-evolution) &key mpointer dimensions)
Source

evolution.lisp.

Method: initialize-instance :after ((object eigen-hermv) &key mpointer n)
Source

symmetric-hermitian.lisp.

Method: initialize-instance :after ((object nonlinear-ffit) &key mpointer dimensions solver-type functions initial-guess)
Source

nonlinear-least-squares.lisp.

Method: initialize-instance :after ((object standard-control) &key mpointer absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: initialize-instance :after ((object eigen-gensymm) &key mpointer n)
Source

generalized.lisp.

Method: initialize-instance :after ((object monte-carlo-vegas) &key mpointer dim)
Source

monte-carlo.lisp.

Method: initialize-instance :after ((object histogram2d-pdf) &key mpointer number-of-bins-y number-of-bins-x histogram)
Source

probability-distribution.lisp.

Method: initialize-instance :after ((object y-control) &key mpointer dydt-scaling y-scaling absolute-error relative-error)
Source

control.lisp.

Method: initialize-instance :after ((object levin-truncated) &key mpointer order)
Source

series-acceleration.lisp.

Method: initialize-instance :after ((object permutation) &key mpointer size)
Source

permutation.lisp.

Method: initialize-instance :after ((object combination) &key range dimensions &allow-other-keys)
Source

combination.lisp.

Method: initialize-instance :after ((object fft-half-complex-wavetable-double-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-real-workspace-double-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-complex-wavetable-single-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-complex-workspace-double-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-complex-wavetable-double-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-half-complex-wavetable-single-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-real-workspace-single-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-real-wavetable-single-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-complex-workspace-single-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: initialize-instance :after ((object fft-real-wavetable-double-float) &key mpointer n)
Source

wavetable-workspace.lisp.

Method: print-object ((object random-number-generator) stream)
Source

generators.lisp.

Method: print-object ((object permutation) stream)
Source

permutation.lisp.

Method: print-object ((object combination) stream)
Source

combination.lisp.

Method: print-object ((object callback-included) stream)
Source

callback-included.lisp.

Method: reinitialize-instance :after ((object interpolation) &key xa ya)
Source

interpolation.lisp.

Method: reinitialize-instance :after ((object monte-carlo-plain) &key)
Source

monte-carlo.lisp.

Method: reinitialize-instance :after ((object histogram-pdf) &key histogram)
Source

probability-distribution.lisp.

Method: reinitialize-instance :after ((object random-number-generator) &key value)
Source

generators.lisp.

Method: reinitialize-instance :after ((object multi-dimensional-root-solver-f) &key functions initial)
Source

roots-multi.lisp.

Method: reinitialize-instance :after ((object yp-control) &key absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: reinitialize-instance :after ((object qawo-table) &key omega l trig)
Source

numerical-integration-with-tables.lisp.

Method: reinitialize-instance :after ((object multi-dimensional-root-solver-fdf) &key functions initial)
Source

roots-multi.lisp.

Method: reinitialize-instance :after ((object one-dimensional-root-solver-fdf) &key functions root-guess)
Source

roots-one.lisp.

Method: reinitialize-instance :after ((object multi-dimensional-minimizer-fdf) &key functions initial step-size tolerance)
Source

minimization-multi.lisp.

Method: reinitialize-instance :after ((object nonlinear-fdffit) &key functions initial-guess)
Source

nonlinear-least-squares.lisp.

Method: reinitialize-instance :after ((object hankel) &key nu xmax)
Source

hankel.lisp.

Method: reinitialize-instance :after ((object multi-dimensional-minimizer-f) &key functions initial step-size)
Source

minimization-multi.lisp.

Method: reinitialize-instance :after ((object histogram) &key ranges)
Source

histogram.lisp.

Method: reinitialize-instance :after ((object one-dimensional-root-solver-f) &key functions lower upper)
Source

roots-one.lisp.

Method: reinitialize-instance :after ((object spline) &key xa ya)
Source

interpolation.lisp.

Method: reinitialize-instance :after ((object qaws-table) &key alpha beta mu nu)
Source

numerical-integration-with-tables.lisp.

Method: reinitialize-instance :after ((object scaled-control) &key absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: reinitialize-instance :after ((object quasi-random-number-generator) &key)
Source

quasi.lisp.

Method: reinitialize-instance :after ((object histogram2d) &key x-ranges y-ranges)
Source

histogram.lisp.

Method: reinitialize-instance :after ((object ode-stepper) &key)
Source

stepping.lisp.

Method: reinitialize-instance :after ((object one-dimensional-minimizer) &key functions x-minimum f-minimum x-lower f-lower x-upper f-upper)
Source

minimization-one.lisp.

Method: reinitialize-instance :after ((object monte-carlo-miser) &key)
Source

monte-carlo.lisp.

Method: reinitialize-instance :after ((object chebyshev) &key functions lower-limit upper-limit)
Source

chebyshev.lisp.

Method: reinitialize-instance :after ((object ode-evolution) &key)
Source

evolution.lisp.

Method: reinitialize-instance :after ((object nonlinear-ffit) &key functions initial-guess)
Source

nonlinear-least-squares.lisp.

Method: reinitialize-instance :after ((object standard-control) &key absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: reinitialize-instance :after ((object monte-carlo-vegas) &key)
Source

monte-carlo.lisp.

Method: reinitialize-instance :after ((object histogram2d-pdf) &key histogram)
Source

probability-distribution.lisp.

Method: reinitialize-instance :after ((object y-control) &key absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: reinitialize-instance :after ((object permutation) &key)
Source

permutation.lisp.


5.1.9 Conditions

Condition: bad-function-supplied

The condition BAD-FUNCTION-SUPPLIED, ‘Problem with user-supplied function,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+ebadfunc+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "problem with user-supplied function")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: cache-limit-exceeded

The condition CACHE-LIMIT-EXCEEDED, ‘Cache limit exceeded,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+ecache+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "cache limit exceeded")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: divergence

The condition DIVERGENCE, ‘Integral or series is divergent,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+ediverge+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "integral or series is divergent")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: exceeded-maximum-iterations

The condition EXCEEDED-MAXIMUM-ITERATIONS, ‘Exceeded max number of iterations,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+emaxiter+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "exceeded max number of iterations")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: factorization-failure

The condition FACTORIZATION-FAILURE, ‘Factorization failed,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+efactor+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "factorization failed")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: failure-to-reach-tolerance

The condition FAILURE-TO-REACH-TOLERANCE, ‘Failed to reach the specified tolerance,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+etol+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "failed to reach the specified tolerance")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: failure-to-reach-tolerance-f

The condition FAILURE-TO-REACH-TOLERANCE-F, ‘Cannot reach the specified tolerance in F,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+etolf+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "cannot reach the specified tolerance in f")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: failure-to-reach-tolerance-g

The condition FAILURE-TO-REACH-TOLERANCE-G, ‘Cannot reach the specified tolerance in gradient,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+etolg+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "cannot reach the specified tolerance in gradient")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: failure-to-reach-tolerance-x

The condition FAILURE-TO-REACH-TOLERANCE-X, ‘Cannot reach the specified tolerance in X,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+etolx+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "cannot reach the specified tolerance in x")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: generic-failure-1

The condition GENERIC-FAILURE-1, ‘Generic failure,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+efailed+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "generic failure")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: generic-failure-2

The condition GENERIC-FAILURE-2, ‘Generic failure,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+failure+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "generic failure")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: gsl-condition

A condition that has been signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses
  • arithmetic-error.
  • warning.
Direct subclasses
Direct methods
Direct slots
Slot: error-number
Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Slot: explanation
Initargs

:explanation

Readers

explanation.

Writers

This slot is read-only.

Slot: source-file
Initform

(quote nil)

Initargs

:source-file

Readers

source-file.

Writers

This slot is read-only.

Slot: line-number
Initform

(quote 0)

Initargs

:line-number

Readers

line-number.

Writers

This slot is read-only.

Condition: gsl-division-by-zero

The condition GSL-DIVISION-BY-ZERO, ‘Tried to divide by zero,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses
Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+ezerodiv+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "tried to divide by zero")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: gsl-eof

The condition GSL-EOF, ‘End of file,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

end-of-file.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eof+)

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "end of file")

Readers

error-text.

Writers

This slot is read-only.

Condition: input-domain

The condition INPUT-DOMAIN, ‘Input domain error,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+edom+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "input domain error")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: input-range

The condition INPUT-RANGE, ‘Output range error,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+erange+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "output range error")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: invalid-argument

The condition INVALID-ARGUMENT, ‘Invalid argument,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+einval+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "invalid argument")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: invalid-pointer

The condition INVALID-POINTER, ‘Invalid pointer,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+efault+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "invalid pointer")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: invalid-tolerance

The condition INVALID-TOLERANCE, ‘User specified an invalid tolerance,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+ebadtol+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "user specified an invalid tolerance")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: jacobian-not-improving

The condition JACOBIAN-NOT-IMPROVING, ‘Jacobian evaluations are not improving the solution,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+enoprogj+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "jacobian evaluations are not improving the solution")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: loss-of-accuracy

The condition LOSS-OF-ACCURACY, ‘Loss of accuracy,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eloss+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "loss of accuracy")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: memory-allocation-failure

The condition MEMORY-ALLOCATION-FAILURE, ‘Malloc failed,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+enomem+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "malloc failed")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: no-progress

The condition NO-PROGRESS, ‘Iteration is not making progress towards solution,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+enoprog+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "iteration is not making progress towards solution")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: nonconformant-dimensions

The condition NONCONFORMANT-DIMENSIONS, ‘Matrix, vector lengths are not conformant,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+ebadlen+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "matrix, vector lengths are not conformant")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: nonsquare-matrix

The condition NONSQUARE-MATRIX, ‘Matrix not square,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+enotsqr+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "matrix not square")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: overflow

The condition OVERFLOW, ‘Overflow,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eovrflw+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "overflow")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: roundoff-failure

The condition ROUNDOFF-FAILURE, ‘Failed because of roundoff error,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eround+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "failed because of roundoff error")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: runaway-iteration

The condition RUNAWAY-ITERATION, ‘Iterative process is out of control,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+erunaway+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "iterative process is out of control")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: sanity-check-failure

The condition SANITY-CHECK-FAILURE, ‘Sanity check failed - shouldn’t happen,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+esanity+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "sanity check failed - shouldn't happen")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: singularity

The condition SINGULARITY, ‘Apparent singularity detected,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+esing+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "apparent singularity detected")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: table-limit-exceeded

The condition TABLE-LIMIT-EXCEEDED, ‘Table limit exceeded,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+etable+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "table limit exceeded")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: underflow

The condition UNDERFLOW, ‘Underflow,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eundrflw+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "underflow")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: unimplemented-feature

The condition UNIMPLEMENTED-FEATURE, ‘Requested feature not (yet) implemented,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eunimpl+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "requested feature not (yet) implemented")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.

Condition: unsupported-feature

The condition UNSUPPORTED-FEATURE, ‘Requested feature is not supported by the hardware,’ signalled by the GNU Scientific Library.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods
Direct slots
Slot: error-number
Allocation

:class

Initform

(quote gsll::+eunsup+)

Initargs

:error-number

Readers

error-number.

Writers

This slot is read-only.

Slot: error-text
Allocation

:class

Initform

(quote "requested feature is not supported by the hardware")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.


5.1.10 Classes

Class: acceleration

The GSL representation of the acceleration for interpolation.

Package

gsll.

Source

lookup.lisp.

Direct superclasses

mobject.

Direct methods
Class: basis-spline

The GSL representation of the basis spline.

Package

gsll.

Source

basis-splines.lisp.

Direct superclasses

mobject.

Direct methods
Class: chebyshev

The GSL representation of the Chebyshev series.

Package

gsll.

Source

chebyshev.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Slot: dimensions
Package

grid.

Allocation

:class

Initform

(quote (1))

Slot: scalarsp
Allocation

:class

Initform

t

Class: discrete-random

The GSL representation of the lookup table for the discrete random number generator.

Package

gsll.

Source

discrete.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-gen

The GSL representation of the generalized nonsymmetric eigenvalue workspace.

Package

gsll.

Source

nonsymmetric-generalized.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-genherm

The GSL representation of the hermitian generalized eigenvalue workspace.

Package

gsll.

Source

generalized.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-genhermv

The GSL representation of the hermitian generalized eigensystem workspace.

Package

gsll.

Source

generalized.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-gensymm

The GSL representation of the symmetric generalized eigenvalue workspace.

Package

gsll.

Source

generalized.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-gensymmv

The GSL representation of the symmetric generalized eigensystem workspace.

Package

gsll.

Source

generalized.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-genv

The GSL representation of the generalized nonsymmetric eigenvector and eigenvalue workspace.

Package

gsll.

Source

nonsymmetric-generalized.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-herm

The GSL representation of the Hermitian eigenvalue workspace.

Package

gsll.

Source

symmetric-hermitian.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-hermv

The GSL representation of the Hermitian eigensystem workspace.

Package

gsll.

Source

symmetric-hermitian.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-nonsymm

The GSL representation of the non-symmetric eigenvalue workspace.

Package

gsll.

Source

nonsymmetric.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-nonsymmv

The GSL representation of the non-symmetric eigenvector and eigenvalue workspace.

Package

gsll.

Source

nonsymmetric.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-symm

The GSL representation of the symmetric eigenvalue workspace.

Package

gsll.

Source

symmetric-hermitian.lisp.

Direct superclasses

mobject.

Direct methods
Class: eigen-symmv

The GSL representation of the symmetric eigensystem workspace.

Package

gsll.

Source

symmetric-hermitian.lisp.

Direct superclasses

mobject.

Direct methods
Class: fit-workspace

The GSL representation of the multi-dimensional root solver with function only.

Package

gsll.

Source

linear-least-squares.lisp.

Direct superclasses

mobject.

Direct methods
Class: hankel

The GSL representation of the discrete Hankel Transform.

Package

gsll.

Source

hankel.lisp.

Direct superclasses

mobject.

Direct methods
Class: histogram

The GSL representation of the one-dimensional histogram, including bin boundaries and bin contents.

Package

gsll.

Source

histogram.lisp.

Direct superclasses

mobject.

Direct methods
Class: histogram-pdf

The GSL representation of the one-dimensional histogram PDF.

Package

gsll.

Source

probability-distribution.lisp.

Direct superclasses

mobject.

Direct methods
Class: histogram2d

The GSL representation of the two-dimensional histogram, including bin boundaries and bin contents..

Package

gsll.

Source

histogram.lisp.

Direct superclasses

mobject.

Direct methods
Class: histogram2d-pdf

The GSL representation of the two-dimensional histogram PDF.

Package

gsll.

Source

probability-distribution.lisp.

Direct superclasses

mobject.

Direct methods
Class: integration-workspace

The GSL representation of the integration workspace.

Package

gsll.

Source

numerical-integration.lisp.

Direct superclasses

mobject.

Direct methods
Class: interpolation

The GSL representation of the interpolation.

Package

gsll.

Source

interpolation.lisp.

Direct superclasses

mobject.

Direct methods
Class: levin

The GSL representation of the Levin u-transform.

Package

gsll.

Source

series-acceleration.lisp.

Direct superclasses

mobject.

Direct methods
Class: levin-truncated

The GSL representation of the truncated Levin u-transform.

Package

gsll.

Source

series-acceleration.lisp.

Direct superclasses

mobject.

Direct methods
Class: mathieu

The GSL representation of the workspace for Mathieu functions.

Package

gsll.

Source

mathieu.lisp.

Direct superclasses

mobject.

Direct methods
Class: monte-carlo-miser

The GSL representation of the miser Monte Carlo integration.

Package

gsll.

Source

monte-carlo.lisp.

Direct superclasses

mobject.

Direct methods
Class: monte-carlo-plain

The GSL representation of the plain Monte Carlo integration.

Package

gsll.

Source

monte-carlo.lisp.

Direct superclasses

mobject.

Direct methods
Class: monte-carlo-vegas

The GSL representation of the vegas Monte Carlo integration.

Package

gsll.

Source

monte-carlo.lisp.

Direct superclasses

mobject.

Direct methods
Class: multi-dimensional-minimizer-f

The GSL representation of the multi-dimensional minimizer with function only.

Package

gsll.

Source

minimization-multi.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::dimension))

Class: multi-dimensional-minimizer-fdf

The GSL representation of the multi-dimensional minimizer with function and derivative.

Package

gsll.

Source

minimization-multi.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::dimension))

Class: multi-dimensional-root-solver-f

The GSL representation of the multi-dimensional root solver with function only.

Package

gsll.

Source

roots-multi.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::dimension))

Class: multi-dimensional-root-solver-fdf

The GSL representation of the multi-dimensional root solver with function and derivative.

Package

gsll.

Source

roots-multi.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::dimension))

Class: nonlinear-fdffit

The GSL representation of the nonlinear least squares fit with function and derivative.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::number-of-observations gsll::number-of-parameters))

Class: nonlinear-ffit

The GSL representation of the nonlinear least squares fit with function only.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::number-of-observations gsll::number-of-parameters))

Class: ode-evolution

The GSL representation of the evolution for ordinary differential equations.

Package

gsll.

Source

evolution.lisp.

Direct superclasses

mobject.

Direct methods
Class: ode-stepper

The GSL representation of the stepper for ordinary differential equations.

Package

gsll.

Source

stepping.lisp.

Direct superclasses

callback-included-cl.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Initform

(quote (gsll::dimension))

Class: one-dimensional-minimizer

The GSL representation of the one-dimensional minimizer.

Package

gsll.

Source

minimization-one.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Slot: dimensions
Package

grid.

Allocation

:class

Initform

(quote (1))

Slot: scalarsp
Allocation

:class

Initform

t

Class: one-dimensional-root-solver-f

The GSL representation of the one-dimensional root solver with function only.

Package

gsll.

Source

roots-one.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Slot: dimensions
Package

grid.

Allocation

:class

Initform

(quote (1))

Slot: scalarsp
Allocation

:class

Initform

t

Class: one-dimensional-root-solver-fdf

The GSL representation of the one-dimensional root solver with function and derivative.

Package

gsll.

Source

roots-one.lisp.

Direct superclasses

callback-included.

Direct methods
Direct slots
Slot: dimension-names
Allocation

:class

Slot: dimensions
Package

grid.

Allocation

:class

Initform

(quote (1))

Slot: scalarsp
Allocation

:class

Initform

t

Class: permutation

The GSL representation of the permutation.

Package

gsll.

Source

permutation.lisp.

Direct superclasses

mobject.

Direct methods
Class: polynomial-complex-workspace

The GSL representation of the complex workspace for polynomials.

Package

gsll.

Source

polynomial.lisp.

Direct superclasses

mobject.

Direct methods
Class: qawo-table

The GSL representation of the table for QAWO numerical integration method.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Direct superclasses

mobject.

Direct methods
Class: qaws-table

The GSL representation of the table for QAWS numerical integration method.

Package

gsll.

Source

numerical-integration-with-tables.lisp.

Direct superclasses

mobject.

Direct methods
Class: quasi-random-number-generator

The GSL representation of the quasi random number generator.

Package

gsll.

Source

quasi.lisp.

Direct superclasses

mobject.

Direct methods
Class: random-number-generator

The GSL representation of the random number generator.

Package

gsll.

Source

generators.lisp.

Direct superclasses

mobject.

Direct methods
Class: scaled-control

The GSL representation of the scaled control for ordinary differential equations.

Package

gsll.

Source

control.lisp.

Direct superclasses

ode-control.

Direct methods
Class: spline

The GSL representation of the spline.

Package

gsll.

Source

interpolation.lisp.

Direct superclasses

mobject.

Direct methods
Class: standard-control

The GSL representation of the standard control for ordinary differential equations.

Package

gsll.

Source

control.lisp.

Direct superclasses

ode-control.

Direct methods
Class: wavelet

The GSL representation of the wavelet.

Package

gsll.

Source

wavelet.lisp.

Direct superclasses

mobject.

Direct methods
Class: wavelet-workspace

The GSL representation of the wavelet workspace.

Package

gsll.

Source

wavelet.lisp.

Direct superclasses

mobject.

Direct methods
Class: y-control

The GSL representation of the y control for ordinary differential equations.

Package

gsll.

Source

control.lisp.

Direct superclasses

ode-control.

Direct methods
Class: yp-control

The GSL representation of the yp control for ordinary differential equations.

Package

gsll.

Source

control.lisp.

Direct superclasses

ode-control.

Direct methods

5.2 Internals


5.2.1 Constants

Constant: +continue+
Package

gsll.

Source

conditions.lisp.

Constant: +ebadfunc+
Package

gsll.

Source

conditions.lisp.

Constant: +ebadlen+
Package

gsll.

Source

conditions.lisp.

Constant: +ebadtol+
Package

gsll.

Source

conditions.lisp.

Constant: +ecache+
Package

gsll.

Source

conditions.lisp.

Constant: +ediverge+
Package

gsll.

Source

conditions.lisp.

Constant: +edom+
Package

gsll.

Source

conditions.lisp.

Constant: +efactor+
Package

gsll.

Source

conditions.lisp.

Constant: +efailed+
Package

gsll.

Source

conditions.lisp.

Constant: +efault+
Package

gsll.

Source

conditions.lisp.

Constant: +einval+
Package

gsll.

Source

conditions.lisp.

Constant: +eloss+
Package

gsll.

Source

conditions.lisp.

Constant: +emaxiter+
Package

gsll.

Source

conditions.lisp.

Constant: +enomem+
Package

gsll.

Source

conditions.lisp.

Constant: +enoprog+
Package

gsll.

Source

conditions.lisp.

Constant: +enoprogj+
Package

gsll.

Source

conditions.lisp.

Constant: +enotsqr+
Package

gsll.

Source

conditions.lisp.

Constant: +eof+
Package

gsll.

Source

conditions.lisp.

Constant: +eovrflw+
Package

gsll.

Source

conditions.lisp.

Constant: +erange+
Package

gsll.

Source

conditions.lisp.

Constant: +eround+
Package

gsll.

Source

conditions.lisp.

Constant: +erunaway+
Package

gsll.

Source

conditions.lisp.

Constant: +esanity+
Package

gsll.

Source

conditions.lisp.

Constant: +esing+
Package

gsll.

Source

conditions.lisp.

Constant: +etable+
Package

gsll.

Source

conditions.lisp.

Constant: +etol+
Package

gsll.

Source

conditions.lisp.

Constant: +etolf+
Package

gsll.

Source

conditions.lisp.

Constant: +etolg+
Package

gsll.

Source

conditions.lisp.

Constant: +etolx+
Package

gsll.

Source

conditions.lisp.

Constant: +eundrflw+
Package

gsll.

Source

conditions.lisp.

Constant: +eunimpl+
Package

gsll.

Source

conditions.lisp.

Constant: +eunsup+
Package

gsll.

Source

conditions.lisp.

Constant: +exp-x+
Package

gsll.

Source

exponential-functions.lisp.

Constant: +ezerodiv+
Package

gsll.

Source

conditions.lisp.

Constant: +failure+
Package

gsll.

Source

conditions.lisp.

Constant: +gamma-xmax+
Package

gsll.

Source

gamma.lisp.

Constant: +gslt-bin-size+
Package

gsll.

Source

tests.lisp.

Constant: +gslt-bins+
Package

gsll.

Source

tests.lisp.

Constant: +gslt-lower-limit+
Package

gsll.

Source

tests.lisp.

Constant: +gslt-upper-limit+
Package

gsll.

Source

tests.lisp.

Constant: +initial-number-of-samples+
Package

gsll.

Source

tests.lisp.

Constant: +ln2+
Package

gsll.

Source

exponential-functions.lisp.

Constant: +success+
Package

gsll.

Source

conditions.lisp.

Constant: +test-factor+
Package

gsll.

Source

augment.lisp.

Constant: +test-sigma+
Package

gsll.

Source

augment.lisp.

Constant: +test-sqrt-tol0+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol0+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol1+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol2+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol3+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol4+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol5+
Package

gsll.

Source

augment.lisp.

Constant: +test-tol6+
Package

gsll.

Source

augment.lisp.

Constant: dpi
Package

gsll.

Source

mathematical.lisp.


5.2.2 Special variables

Special Variable: *all-generated-tests*
Package

gsll.

Source

generate-examples.lisp.

Special Variable: *allowed-ticks*
Package

gsll.

Source

fast-fourier-transform.lisp.

Special Variable: *blas-splice-fp-types*

The list of floating point types that can be spliced into BLAS function names.

Package

gsll.

Source

types.lisp.

Special Variable: *callbacks-for-classes*

A table of :callbacks arguments for each class.

Package

gsll.

Source

callback-compile-defs.lisp.

Special Variable: *cstd-blas-mapping*

Mapping the C standard types to the BLAS splice name.

Package

gsll.

Source

types.lisp.

Special Variable: *cstd-gsl-mapping*

Mapping the C standard types to the GSL splice name.

Package

gsll.

Source

types.lisp.

Special Variable: *default-sf-array-size*

The default size to make an array returned from a special function.

Package

gsll.

Source

return-structures.lisp.

Special Variable: *defmfun-llk*

Possible lambda-list keywords.

Package

gsll.

Source

forms.lisp.

Special Variable: *defmfun-optk*

Possible optional-argument keywords.

Package

gsll.

Source

forms.lisp.

Special Variable: *double-float-pool*

A sequence of random double floats ranging between -100.0d0 and +100.0d0.

Package

gsll.

Source

generate-examples.lisp.

Special Variable: *elljac-a*
Package

gsll.

Source

elliptic-functions.lisp.

Special Variable: *elljac-b*
Package

gsll.

Source

elliptic-functions.lisp.

Special Variable: *elljac-c*
Package

gsll.

Source

elliptic-functions.lisp.

Special Variable: *elljac-c2*
Package

gsll.

Source

elliptic-functions.lisp.

Special Variable: *elljac-k*
Package

gsll.

Source

elliptic-functions.lisp.

Special Variable: *errorno-keyword*
Package

gsll.

Source

conditions.lisp.

Special Variable: *gsl-splice-fp-types*

The list of floating point types that can be spliced into function names.

Package

gsll.

Source

types.lisp.

Special Variable: *gsl-splice-int-types*

The list of integer types that can be spliced into function names.

Package

gsll.

Source

types.lisp.

Special Variable: *gsl-symbol-equivalence*
Package

gsll.

Source

interface.lisp.

Special Variable: *hilb12*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb12-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb2*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb2-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb3*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb3-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb4*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *hilb4-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *m35*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *m53*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *max-iter*
Package

gsll.

Source

ode-example.lisp.

Special Variable: *mc-lower*
Package

gsll.

Source

monte-carlo.lisp.

Special Variable: *mc-upper*
Package

gsll.

Source

monte-carlo.lisp.

Special Variable: *monte-carlo-default-samples-per-dimension*
Package

gsll.

Source

monte-carlo.lisp.

Special Variable: *nlls-example-data*
Package

gsll.

Source

nonlinear-least-squares.lisp.

Special Variable: *ntuple-example-data-file*

The full path string of the ntuple example data file. This can be created with the function #’make-ntuple-example-data.

Package

gsll.

Source

ntuple.lisp.

Special Variable: *ntuple-example-scale*
Package

gsll.

Source

ntuple.lisp.

Special Variable: *paraboloid-center*
Package

gsll.

Source

minimization-multi.lisp.

Special Variable: *pdf-number-of-tries*
Package

gsll.

Source

tests.lisp.

Special Variable: *pointer-offset*

An arbitrary offset for the generated pointers; non-negative fixnum value is irrelevant and changed for debugging purposes only.

Package

gsll.

Source

simulated-annealing.lisp.

Special Variable: *powell-a*
Package

gsll.

Source

roots-multi.lisp.

Special Variable: *rosenbrock-a*
Package

gsll.

Source

roots-multi.lisp.

Special Variable: *rosenbrock-b*
Package

gsll.

Source

roots-multi.lisp.

Special Variable: *s35*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *s53*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *signed-byte-pool*

A sequence of random integers ranging between -255 and 255.

Package

gsll.

Source

generate-examples.lisp.

Special Variable: *special-c-return*
Package

gsll.

Source

interface.lisp.

Special Variable: *unsigned-byte-pool*

A sequence of random integers ranging between 0 and 255.

Package

gsll.

Source

generate-examples.lisp.

Special Variable: *vander12*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander12-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander2*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander2-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander3*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander3-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander4*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *vander4-soln*
Package

gsll.

Source

matrix-generation.lisp.

Special Variable: *wavelet-sample*

Data for example wavelet transform from doc/examples/ecg.dat.

Package

gsll.

Source

wavelet.lisp.


5.2.3 Macros

Macro: all-fft-test-forms (size-max stride-max &optional additional-single-stride)
Package

gsll.

Source

fast-fourier-transform.lisp.

Macro: assert-neginf (form)
Package

gsll.

Source

augment.lisp.

Macro: assert-posinf (form)
Package

gsll.

Source

augment.lisp.

Macro: assert-sf-scale (form expected-value scale result-tol &optional err-tol)
Package

gsll.

Source

augment.lisp.

Macro: assert-to-tolerance (form expected-value tolerance)
Package

gsll.

Source

augment.lisp.

Macro: def-ci-subclass (class-name superclasses documentation dimension-names)
Package

gsll.

Source

callback-included.lisp.

Macro: def-ci-subclass-1d (class-name superclasses documentation ignore)
Package

gsll.

Source

callback-included.lisp.

Macro: def-rng-type (lisp-name &optional documentation gsl-name gsl-version)

Define the random number generator type.

Package

gsll.

Source

rng-types.lisp.

Macro: defcomparison (name &body body)
Package

gsll.

Source

sorting.lisp.

Macro: define-gsl-condition (keyword number text &rest superclasses)
Package

gsll.

Source

conditions.lisp.

Macro: defmcallback (name dynamic-variable function-spec)
Package

gsll.

Source

callback.lisp.

Macro: defmfun (name arglist gsl-name c-arguments &rest key-args)

Definition of a GSL function.

Package

gsll.

Source

defmfun.lisp.

Macro: defmobject (class prefix allocation-args description &key documentation initialize-when-making initialize-suffix initialize-name initialize-args arglists-function inputs gsl-version allocator allocate-inputs freer callbacks export superclasses singular switch ri-c-return)

Define the class, the allocate, initialize-instance and reinitialize-instance methods, and the make-* function for the GSL object.

Package

gsll.

Source

mobject.lisp.

Macro: defmpar (cl-symbol gsl-symbol documentation &key c-type read-only gsl-version)

Define a library variable pointer.

Package

gsll.

Source

interface.lisp.

Macro: fft-complex-result-check (form element-component-type stride)

T if all FFT tests pass.

Package

gsll.

Source

fast-fourier-transform.lisp.

Macro: fft-real-result-check (form element-type stride)

T if all FFT tests pass.

Package

gsll.

Source

fast-fourier-transform.lisp.

Macro: foreign-pointer-method (pointer form)

Execute this form only if the pointer is of grid:+foreign-pointer-type+; otherwise call the next method.

Package

gsll.

Source

mobject.lisp.

Macro: generate-all-array-tests (name element-types test)
Package

gsll.

Source

generate-examples.lisp.

Macro: pmnil (x)

+1, -1, or nil

Package

gsll.

Source

mathematical.lisp.

Macro: save-test (name &rest forms)

Save the test with the given name.

Package

gsll.

Source

generate-examples.lisp.

Macro: set-maref (mpointer class-name &rest indices-value)
Package

gsll.

Source

both.lisp.

Setf expanders to this macro

(setf maref).

Macro: with-defmfun-key-args (key-args &body body)

Bind defmfun’s key arguments.

Package

gsll.

Source

defmfun.lisp.


5.2.4 Ordinary functions

Function: %var-accessor-*gsl-version* ()
Package

gsll.

Source

gsl-version.lisp.

Function: (setf %var-accessor-*gsl-version*) ()
Package

gsll.

Source

gsl-version.lisp.

Function: %var-accessor-+akima-interpolation+ ()
Package

gsll.

Source

types.lisp.

Function: (setf %var-accessor-+akima-interpolation+) ()
Package

gsll.

Source

types.lisp.

Function: %var-accessor-+bisection-fsolver+ ()
Package

gsll.

Source

roots-one.lisp.

Function: (setf %var-accessor-+bisection-fsolver+) ()
Package

gsll.

Source

roots-one.lisp.

Function: %var-accessor-+borosh13+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+borosh13+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+brent-fminimizer+ ()
Package

gsll.

Source

minimization-one.lisp.

Function: (setf %var-accessor-+brent-fminimizer+) ()
Package

gsll.

Source

minimization-one.lisp.

Function: %var-accessor-+brent-fsolver+ ()
Package

gsll.

Source

roots-one.lisp.

Function: (setf %var-accessor-+brent-fsolver+) ()
Package

gsll.

Source

roots-one.lisp.

Function: %var-accessor-+broyden+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+broyden+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+bspline-wavelet+ ()
Package

gsll.

Source

wavelet.lisp.

Function: (setf %var-accessor-+bspline-wavelet+) ()
Package

gsll.

Source

wavelet.lisp.

Function: %var-accessor-+bspline-wavelet-centered+ ()
Package

gsll.

Source

wavelet.lisp.

Function: (setf %var-accessor-+bspline-wavelet-centered+) ()
Package

gsll.

Source

wavelet.lisp.

Function: %var-accessor-+cmrg+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+cmrg+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+conjugate-fletcher-reeves+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+conjugate-fletcher-reeves+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+conjugate-polak-ribiere+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+conjugate-polak-ribiere+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+coveyou+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+coveyou+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+cubic-spline-interpolation+ ()
Package

gsll.

Source

types.lisp.

Function: (setf %var-accessor-+cubic-spline-interpolation+) ()
Package

gsll.

Source

types.lisp.

Function: %var-accessor-+daubechies-wavelet+ ()
Package

gsll.

Source

wavelet.lisp.

Function: (setf %var-accessor-+daubechies-wavelet+) ()
Package

gsll.

Source

wavelet.lisp.

Function: %var-accessor-+daubechies-wavelet-centered+ ()
Package

gsll.

Source

wavelet.lisp.

Function: (setf %var-accessor-+daubechies-wavelet-centered+) ()
Package

gsll.

Source

wavelet.lisp.

Function: %var-accessor-+default-seed+ ()
Package

gsll.

Source

generators.lisp.

Function: (setf %var-accessor-+default-seed+) ()
Package

gsll.

Source

generators.lisp.

Function: %var-accessor-+default-type+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+default-type+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+discrete-newton+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+discrete-newton+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+false-position-fsolver+ ()
Package

gsll.

Source

roots-one.lisp.

Function: (setf %var-accessor-+false-position-fsolver+) ()
Package

gsll.

Source

roots-one.lisp.

Function: %var-accessor-+fishman18+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+fishman18+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+fishman20+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+fishman20+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+fishman2x+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+fishman2x+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+gfsr4+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+gfsr4+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+gnewton-mfdfsolver+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+gnewton-mfdfsolver+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+golden-section-fminimizer+ ()
Package

gsll.

Source

minimization-one.lisp.

Function: (setf %var-accessor-+golden-section-fminimizer+) ()
Package

gsll.

Source

minimization-one.lisp.

Function: %var-accessor-+haar-wavelet+ ()
Package

gsll.

Source

wavelet.lisp.

Function: (setf %var-accessor-+haar-wavelet+) ()
Package

gsll.

Source

wavelet.lisp.

Function: %var-accessor-+haar-wavelet-centered+ ()
Package

gsll.

Source

wavelet.lisp.

Function: (setf %var-accessor-+haar-wavelet-centered+) ()
Package

gsll.

Source

wavelet.lisp.

Function: %var-accessor-+halton+ ()
Package

gsll.

Source

quasi.lisp.

Function: (setf %var-accessor-+halton+) ()
Package

gsll.

Source

quasi.lisp.

Function: %var-accessor-+hybrid-scaled+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+hybrid-scaled+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+hybrid-unscaled+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+hybrid-unscaled+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+knuthran+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+knuthran+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+knuthran2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+knuthran2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+knuthran2002+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+knuthran2002+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+lecuyer21+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+lecuyer21+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+levenberg-marquardt+ ()
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: (setf %var-accessor-+levenberg-marquardt+) ()
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: %var-accessor-+levenberg-marquardt-unscaled+ ()
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: (setf %var-accessor-+levenberg-marquardt-unscaled+) ()
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: %var-accessor-+linear-interpolation+ ()
Package

gsll.

Source

types.lisp.

Function: (setf %var-accessor-+linear-interpolation+) ()
Package

gsll.

Source

types.lisp.

Function: %var-accessor-+minstd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+minstd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+mrg+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+mrg+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+mt19937+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+mt19937+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+mt19937-1998+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+mt19937-1998+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+mt19937-1999+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+mt19937-1999+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+newton-fdfsolver+ ()
Package

gsll.

Source

roots-one.lisp.

Function: (setf %var-accessor-+newton-fdfsolver+) ()
Package

gsll.

Source

roots-one.lisp.

Function: %var-accessor-+newton-mfdfsolver+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+newton-mfdfsolver+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+niederreiter2+ ()
Package

gsll.

Source

quasi.lisp.

Function: (setf %var-accessor-+niederreiter2+) ()
Package

gsll.

Source

quasi.lisp.

Function: %var-accessor-+periodic-akima-interpolation+ ()
Package

gsll.

Source

types.lisp.

Function: (setf %var-accessor-+periodic-akima-interpolation+) ()
Package

gsll.

Source

types.lisp.

Function: %var-accessor-+periodic-cubic-spline-interpolation+ ()
Package

gsll.

Source

types.lisp.

Function: (setf %var-accessor-+periodic-cubic-spline-interpolation+) ()
Package

gsll.

Source

types.lisp.

Function: %var-accessor-+polynomial-interpolation+ ()
Package

gsll.

Source

types.lisp.

Function: (setf %var-accessor-+polynomial-interpolation+) ()
Package

gsll.

Source

types.lisp.

Function: %var-accessor-+powells-hybrid+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+powells-hybrid+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+powells-hybrid-unscaled+ ()
Package

gsll.

Source

roots-multi.lisp.

Function: (setf %var-accessor-+powells-hybrid-unscaled+) ()
Package

gsll.

Source

roots-multi.lisp.

Function: %var-accessor-+quad-golden-fminimizer+ ()
Package

gsll.

Source

minimization-one.lisp.

Function: (setf %var-accessor-+quad-golden-fminimizer+) ()
Package

gsll.

Source

minimization-one.lisp.

Function: %var-accessor-+r250+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+r250+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ran0+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ran0+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ran1+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ran1+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ran2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ran2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ran3+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ran3+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+rand+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+rand+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+rand48+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+rand48+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random128_bsd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random128_bsd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random128_glibc2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random128_glibc2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random128_libc5+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random128_libc5+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random256_bsd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random256_bsd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random256_glibc2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random256_glibc2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random256_libc5+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random256_libc5+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random32_bsd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random32_bsd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random32_glibc2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random32_glibc2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random32_libc5+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random32_libc5+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random64_bsd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random64_bsd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random64_glibc2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random64_glibc2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random64_libc5+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random64_libc5+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random8_bsd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random8_bsd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random8_glibc2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random8_glibc2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random8_libc5+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random8_libc5+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random_bsd+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random_bsd+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random_glibc2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random_glibc2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+random_libc5+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+random_libc5+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+randu+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+randu+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranf+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranf+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlux+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlux+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlux389+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlux389+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlxd1+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlxd1+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlxd2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlxd2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlxs0+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlxs0+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlxs1+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlxs1+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranlxs2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranlxs2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+ranmar+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+ranmar+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+reverse-halton+ ()
Package

gsll.

Source

quasi.lisp.

Function: (setf %var-accessor-+reverse-halton+) ()
Package

gsll.

Source

quasi.lisp.

Function: %var-accessor-+secant-fdfsolver+ ()
Package

gsll.

Source

roots-one.lisp.

Function: (setf %var-accessor-+secant-fdfsolver+) ()
Package

gsll.

Source

roots-one.lisp.

Function: %var-accessor-+simplex-nelder-mead+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+simplex-nelder-mead+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+simplex-nelder-mead-on2+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+simplex-nelder-mead-on2+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+simplex-nelder-mead-random+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+simplex-nelder-mead-random+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+slatec+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+slatec+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+sobol+ ()
Package

gsll.

Source

quasi.lisp.

Function: (setf %var-accessor-+sobol+) ()
Package

gsll.

Source

quasi.lisp.

Function: %var-accessor-+steffenson-fdfsolver+ ()
Package

gsll.

Source

roots-one.lisp.

Function: (setf %var-accessor-+steffenson-fdfsolver+) ()
Package

gsll.

Source

roots-one.lisp.

Function: %var-accessor-+step-bsimp+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-bsimp+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-gear1+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-gear1+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-gear2+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-gear2+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rk2+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rk2+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rk2imp+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rk2imp+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rk4+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rk4+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rk4imp+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rk4imp+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rk8pd+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rk8pd+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rkck+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rkck+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+step-rkf45+ ()
Package

gsll.

Source

stepping.lisp.

Function: (setf %var-accessor-+step-rkf45+) ()
Package

gsll.

Source

stepping.lisp.

Function: %var-accessor-+taus+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+taus+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+taus113+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+taus113+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+taus2+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+taus2+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+transputer+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+transputer+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+tt800+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+tt800+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+uni+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+uni+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+uni32+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+uni32+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+vax+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+vax+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+vector-bfgs+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+vector-bfgs+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+vector-bfgs2+ ()
Package

gsll.

Source

minimization-multi.lisp.

Function: (setf %var-accessor-+vector-bfgs2+) ()
Package

gsll.

Source

minimization-multi.lisp.

Function: %var-accessor-+waterman14+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+waterman14+) ()
Package

gsll.

Source

rng-types.lisp.

Function: %var-accessor-+zuf+ ()
Package

gsll.

Source

rng-types.lisp.

Function: (setf %var-accessor-+zuf+) ()
Package

gsll.

Source

rng-types.lisp.

Function: acceleration-example (&optional print-explanation)
Package

gsll.

Source

series-acceleration.lisp.

Function: access-value-int (mpointer class-name value indices)

Create a form to access the GSL array value from the mpointer. If value is not nil, set the value; otherwise, get the value.

Package

gsll.

Source

both.lisp.

Function: actual-array-c-type (category c-arguments &optional map-down)

Replace the declared proto-type with an actual GSL struct type in the GSL function name.

Package

gsll.

Source

defmfun-array.lisp.

Function: actual-array-class (category element-type &optional replace-both)

From the category (’vector, ’grid:matrix, or ’both) and element type, find the class name.

Package

gsll.

Source

defmfun-array.lisp.

Function: actual-class-arglist (arglist element-type c-arguments &optional replace-both)

Replace the prototype arglist with an actual arglist.

Package

gsll.

Source

defmfun-array.lisp.

Function: actual-element-c-type (element-type c-arguments)

Replace the generic element type :element-c-type with the actual element type.

Package

gsll.

Source

defmfun-array.lisp.

Function: actual-gsl-function-name (base-name category type)

Create the GSL or BLAS function name for data from the base name and the CL type.

Package

gsll.

Source

defmfun-array.lisp.

Function: after-llk (arglist)

The portion of the arglist from the first llk on.

Package

gsll.

Source

forms.lisp.

Function: all-io (direction &optional arrays)

Create a function that returns dimensions for argspecs that are arrays for the specified direction.

Package

gsll.

Source

funcallable.lisp.

Function: arglist-plain-and-categories (arglist &optional include-llk)

Get arglist without classes and a list of categories.

Package

gsll.

Source

forms.lisp.

Function: array-default (spec &optional no-init)

Make an array of the current type and initialize from the pool.

Package

gsll.

Source

generate-examples.lisp.

Function: array-element-refs (names argspecs dimension-values)

A list of forms reference each array element in succession.
If there is no argspec for the argument, just reference the variable itself.

Package

gsll.

Source

funcallable.lisp.

Function: bin-samples (count edge number-of-samples distribution &rest distribution-parameters)

Update the fixnum vectors count and edge with sample random values from the distribution, and return the mean.

Package

gsll.

Source

tests.lisp.

Function: body-expand (name arglist gsl-name c-arguments key-args)

Expand the body (computational part) of the defmfun.

Package

gsll.

Source

body-expand.lisp.

Function: body-no-optional-arg (name arglist gsl-name c-arguments key-args)

Wrap necessary array-handling forms around the expanded unswitched body form.

Package

gsll.

Source

defmfun-single.lisp.

Function: body-optional-arg (name arglist gsl-name c-arguments key-args)

Create the body of a defmfun with &optional in its arglist, where the presence or absence of the optional argument(s) selects one of two GSL functions.

Package

gsll.

Source

defmfun.lisp.

Function: bspline-example (&optional ncoeffs)
Package

gsll.

Source

basis-splines.lisp.

Function: callback-args (argspec)

The arguments passed by GSL to the callback function.

Package

gsll.

Source

callback.lisp.

Function: callback-remove-arg (list cbinfo &optional key)

Remove from the list the symbol representing the foreign callback argument.

Package

gsll.

Source

callback.lisp.

Function: callback-replace-arg (replacement list cbinfo)

Replace in the list the symbol representing the foreign callback argument.

Package

gsll.

Source

callback.lisp.

Function: callback-set-dynamic (callback-object &optional arglist)

Make a form to set the dynamic variable defining callbacks.

Package

gsll.

Source

callback-included.lisp.

Function: callback-set-mvb (argument-names form fnspec dimension-values)

Create the multiple-value-bind form in the callback to set the return C arrays.

Package

gsll.

Source

funcallable.lisp.

Function: callback-set-slots (cbinfo dynamic-variables callback-dynamic)

Set the slots in the foreign callback struct.

Package

gsll.

Source

callback.lisp.

Function: callback-symbol-set (callback-dynamic cbinfo symbols)

Generate the form to set each of the dynamic (special) variables to (function scalarsp dimensions...) in the body of the demfun for each of the callback functions.

Package

gsll.

Source

callback.lisp.

Function: category-for-argument (arglist symbol)

Find the category (class) for the given argument.

Package

gsll.

Source

forms.lisp.

Function: cbd-dimensions (callback-dynamic)
Package

gsll.

Source

callback.lisp.

Function: cbd-functions (callback-dynamic)
Package

gsll.

Source

callback.lisp.

Function: chebyshev-point-example (x)
Package

gsll.

Source

chebyshev.lisp.

Function: chebyshev-step (x)
Package

gsll.

Source

chebyshev.lisp.

Function: chebyshev-table-example ()
Package

gsll.

Source

chebyshev.lisp.

Function: check-gsl-status (status-code context)

Check the return status code from a GSL function and signal a warning if it is not :SUCCESS.

Package

gsll.

Source

interface.lisp.

Function: check-null-pointer (pointer error-code reason)
Package

gsll.

Source

interface.lisp.

Function: cl-argument-types (cl-arguments c-arguments-types)

Create CL argument and types from the C arguments.

Package

gsll.

Source

interface.lisp.

Function: cl-convert-form (decl)

Generate a form that calls the appropriate converter from C/GSL to CL.

Package

gsll.

Source

body-expand.lisp.

Function: cl-gsl (cl-type &optional prepend-underscore blas)

The GSL splice string from the CL type.

Package

gsll.

Source

types.lisp.

Function: cl-symbols (arglist)

The symbols in the arglist.

Package

gsll.

Source

interface.lisp.

Function: comb-copy (source destination)

Copy the elements of the combination source into the
combination destination. The two combinations must have the same size.

Package

gsll.

Source

combination.lisp.

Function: complete-definition (defn name arglist gsl-name c-arguments key-args &optional body-maker mapdown)

A complete definition form, starting with defun, :method, or defmethod.

Package

gsll.

Source

defmfun-single.lisp.

Function: complex-with-error (real-sfr imaginary-sfr)

Return two complex numbers, the value and the error.

Package

gsll.

Source

return-structures.lisp.

Function: constant-matrix (constant dim0 &optional dim1 element-type)
Package

gsll.

Source

matrix-generation.lisp.

Function: copy-exponent-fit-data (instance)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: copy-sa-state (source destination)
Package

gsll.

Source

simulated-annealing.lisp.

Function: copy-with-stride (vector &key stride init-offset)

Copy a vector and initialize it.

Package

gsll.

Source

example.lisp.

Function: create-complex-matrix (dim)
Package

gsll.

Source

matrix-generation.lisp.

Function: create-general-matrix (dim0 dim1)
Package

gsll.

Source

matrix-generation.lisp.

Function: create-hilbert-matrix (dim)

Make Hilbert matrix used to test linear algebra functions.

Package

gsll.

Source

matrix-generation.lisp.

Function: create-matrix (function dim0 &optional dim1 element-type)

Make a matrix or vector of the specified dimensions, with contents based on a function of the element indices i, j.

Package

gsll.

Source

matrix-generation.lisp.

Function: create-moler-matrix (dim)
Package

gsll.

Source

matrix-generation.lisp.

Function: create-rhs-vector (dim &optional element-type)
Package

gsll.

Source

matrix-generation.lisp.

Function: create-row-matrix (dim0 dim1)
Package

gsll.

Source

matrix-generation.lisp.

Function: create-singular-matrix (dim0 dim1)
Package

gsll.

Source

matrix-generation.lisp.

Function: create-vandermonde-matrix (dim)

Make Van der Monde matrix used to test linear algebra functions.

Package

gsll.

Source

matrix-generation.lisp.

Function: creturn-st (c-return)

The symbol-type of the return from the C function.

Package

gsll.

Source

body-expand.lisp.

Function: declaration-form (cl-argument-types &optional ignores specials)
Package

gsll.

Source

interface.lisp.

Function: decode-ieee754 (float)

The significand (mantissa), exponent, and sign of the IEEE 754 representation of a floating point number, given as integers. It does not matter whether the actual representation follows IEEE.
Values returned are significand, exponent, sign, bits in significand, bits in exponent.

Package

gsll.

Source

floating-point.lisp.

Function: default-covariance (parameters-or-size)
Package

gsll.

Source

linear-least-squares.lisp.

Function: default-lls-workspace (observations parameters-or-size)
Package

gsll.

Source

linear-least-squares.lisp.

Function: defgeneric-method-p (name)

When defining :method in a defgeneric, (nil foo) is used for the name, and foo will be returned from this function.

Package

gsll.

Source

defmfun-single.lisp.

Function: defmfun-return (c-return cret-name clret allocated return return-supplied-p enumeration outputs)

Generate the return computation expression for defmfun.

Package

gsll.

Source

body-expand.lisp.

Function: delete-test-definition (name)
Package

gsll.

Source

generate-examples.lisp.

Function: deriv-f1-d (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f2 (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f2-d (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f3 (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f3-d (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f4 (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f4-d (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f5 (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f5-d (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: deriv-f6-d (x)
Package

gsll.

Source

numerical-differentiation.lisp.

Function: distribution-bin-integral (pdf)

Compute the CDF for a bin from the PDF.

Package

gsll.

Source

tests.lisp.

Function: eigenvalue-eigenvectors-example ()
Package

gsll.

Source

symmetric-hermitian.lisp.

Function: element-type-select (form element-type)

Find the actual form to use as the default based on the list in form.

Package

gsll.

Source

defmfun-array.lisp.

Function: eql-specializer (arg)

If this argument has an eql specializer, return the specialization category; otherwise nil.

Package

gsll.

Source

forms.lisp.

Function: establish-handler ()
Package

gsll.

Source

conditions.lisp.

Function: evaluate-integral-example (&optional intervals)

Evaluate integral of sin(x) in interval 0-pi. sin(x) is tabulated over a 0-2pi interval and interpolated with +periodic-cubic-spline-interpolation+

Package

gsll.

Source

spline-example.lisp.

Function: expand-defmfun-arrays (defn name arglist gsl-name c-arguments categories key-args)
Package

gsll.

Source

defmfun-array.lisp.

Function: expand-defmfun-defmethods (name arglist gsl-name c-arguments key-args)

Define methods for all kinds of arrays.

Package

gsll.

Source

defmfun-array.lisp.

Function: expand-defmfun-generic (name arglist gsl-name c-arguments key-args)

Define a generic function and methods for all kinds of arrays.

Package

gsll.

Source

defmfun-array.lisp.

Function: expand-defmfun-method (name arglist gsl-name c-arguments key-args)

Create a specific method for a previously-defined generic function.

Package

gsll.

Source

defmfun.lisp.

Function: expand-defmfun-optional (name arglist gsl-name c-arguments key-args)

Expand defmfun where there is an optional argument
present, giving the choice between two different GSL functions.

Package

gsll.

Source

defmfun.lisp.

Function: expand-defmfun-wrap (name arglist gsl-name c-arguments key-args)
Package

gsll.

Source

defmfun.lisp.

Reader: exponent-fit-data-n (instance)
Writer: (setf exponent-fit-data-n) (instance)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Target Slot

n.

Function: exponent-fit-data-p (object)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Reader: exponent-fit-data-sigma (instance)
Writer: (setf exponent-fit-data-sigma) (instance)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Target Slot

sigma.

Reader: exponent-fit-data-y (instance)
Writer: (setf exponent-fit-data-y) (instance)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Target Slot

y.

Function: exponential-residual (x f)

Compute the negative of the residuals with the exponential model for the nonlinear least squares example.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: exponential-residual-derivative (x jacobian)

Compute the partial derivatives of the negative of the residuals with the exponential model
for the nonlinear least squares example.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: exponential-residual-fdf (x f jacobian)

Compute the function and partial derivatives of the negative of the residuals with the exponential model
for the nonlinear least squares example.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: faify-form (ptr argspec dimension-values)

Make the form that turns the mpointer into a foreign-array.

Package

gsll.

Source

funcallable.lisp.

Function: fft-complex-off-stride-check (vector stride offset)
Package

gsll.

Source

fast-fourier-transform.lisp.

Function: fft-frequency-split (size)

Return the index where the highest frequency component is located in a vector of the given size, after applying an FFT. The second value that is returned, is the most negative frequency divided by the sample frequency step.

Package

gsll.

Source

extras.lisp.

Function: fft-frequency-step (size &optional sample-spacing)

Return the frequency step for the FFT of a vector with the given size and assuming the given sample spacing.

Package

gsll.

Source

extras.lisp.

Function: fft-highest-frequency (size &optional sample-spacing)

Return the highest frequency for the FFT of a vector with the given size and assuming the given sample spacing.

Package

gsll.

Source

extras.lisp.

Function: fft-pulse-test (element-type dimension)
Package

gsll.

Source

example.lisp.

Function: fft-test-forms (size stride)
Package

gsll.

Source

fast-fourier-transform.lisp.

Function: forward-backward (symb)
Package

gsll.

Source

wavelet.lisp.

Function: generate-all-array-tests-body (element-types test)
Package

gsll.

Source

generate-examples.lisp.

Function: generate-all-permutations (n)

Generate all the permutations of n objects.

Package

gsll.

Source

permutation.lisp.

Function: generate-all-permutations-backwards (n)

Generate all the permutations of n objects.

Package

gsll.

Source

permutation.lisp.

Function: generate-methods (defn category name arglist gsl-name c-arguments key-args &optional replace-both)

Create all the methods for a generic function.

Package

gsll.

Source

defmfun-array.lisp.

Function: generate-nlls-data (&optional number-of-observations)

Create the data used in the nonlinear least squares fit example.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: get-callbacks-for-class (class)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: get-mcm-parameters (object)

Get all parameters, as a foreign struct, for the MISER method.

Package

gsll.

Source

monte-carlo.lisp.

Function: get-mcv-parameters (object)

Get all parameters, as a foreign struct, for the VEGAS method.

Package

gsll.

Source

monte-carlo.lisp.

Function: gsl-config-pathname (pn)
Package

gsll.

Source

init.lisp.

Function: have-at-least-gsl-version (version-wanted)

The GSL version currently running is at least the version wanted, specified as (major minor).

Package

gsll.

Source

gsl-version.lisp.

Function: histo-clone (source)
Package

gsll.

Source

histogram.lisp.

Function: histo-copy (source destination)

Copy the histogram source into the pre-existing histogram destination, making the latter into an exact copy of the former.
The two histograms must be of the same size.

Package

gsll.

Source

histogram.lisp.

Function: histo2d-clone (source)
Package

gsll.

Source

histogram.lisp.

Function: histo2d-copy (source destination)

Copy the histogram source into the pre-existing histogram destination, making the latter into an exact copy of the former.
The two histograms must be of the same size.

Package

gsll.

Source

histogram.lisp.

Function: ieee754-sign-bit (float-type)

The bytespec to access the sign bit in the IEEE754 specification.

Package

gsll.

Source

floating-point.lisp.

Function: initialize-suffix-switched-foreign (initialize-suffix)

The specified initialize-suffix indicates that there are two foreign functions that can be called; which one is called is dependent on the presence or absense of certain arguments.

Package

gsll.

Source

mobject.lisp.

Function: integrate-vanderpol (max-time &optional step-size stepper print-steps)

Integrate the van der Pol oscillator as given in Section 25.5 of the GSL manual. To reproduce that example, (integrate-vanderpol 100.0d0).

Package

gsll.

Source

ode-example.lisp.

Function: integration-test-f1 (alpha)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f11 (alpha)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f15 (alpha)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f16 (alpha)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f3 (alpha)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f454 (x)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f455 (x)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-f456 (x)
Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: integration-test-f457 (x)
Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: integration-test-f458 (x)
Package

gsll.

Source

numerical-integration-with-tables.lisp.

Function: integration-test-f459 (x)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-myfn1 (x)
Package

gsll.

Source

numerical-integration.lisp.

Function: integration-test-myfn2 (alpha)
Package

gsll.

Source

numerical-integration.lisp.

Function: levin-value (levin slot)
Package

gsll.

Source

series-acceleration.lisp.

Function: limits-check (count number-of-samples cdf retry)

Returns nil if finite and within limits.

Package

gsll.

Source

tests.lisp.

Function: linear-least-squares-multivariate-example (data &optional print-details)

Second example in Section 36.5 of the GSL manual. Returns the coefficients of x^0, x^1, x^2 for the best fit, and the chi squared.

Package

gsll.

Source

linear-least-squares.lisp.

Function: linear-least-squares-univariate-example (&optional print-steps)

First example in Section 36.5 of the GSL manual.

Package

gsll.

Source

linear-least-squares.lisp.

Function: linear-mfit-nosvd (model observations parameters-or-size &optional weight covariance workspace)

Compute the best-fit parameters c of the weighted or unweighted model y = X c for the observations y and optional weights
and the model matrix X. The covariance matrix of
the model parameters is computed with the given weights. The weighted sum of squares of the residuals from the best-fit, chi^2, is returned as the last value.

The best-fit is found by singular value decomposition of the matrix model using the preallocated workspace provided. The modified Golub-Reinsch SVD algorithm is used for the unweighted solution, with column scaling to improve the accuracy of the singular values. Any components which have zero singular value (to machine precision) are discarded from the fit.

Package

gsll.

Source

linear-least-squares.lisp.

Function: linear-mfit-svd (model observations parameters-or-size tolerance &optional weight covariance workspace)

Compute the best-fit parameters c of the weighted or unweighted model y = X c for the observations y and weights and the model matrix X. The covariance matrix of the model parameters is computed with the given weights. The weighted or unweighted sum of squares of the residuals from the best-fit, chi^2, is returned as the first value.

The best-fit is found by singular value decomposition of the matrix model using the preallocated workspace provided. The modified Golub-Reinsch SVD algorithm is used, with column scaling to improve the accuracy of the singular values (unweighted). Any components which have zero singular value (to machine precision) are discarded from the fit. In the second form of the function the components are discarded if the ratio of singular values s_i/s_0 falls below the user-specified tolerance, and the effective rank is returned as the second value.

Package

gsll.

Source

linear-least-squares.lisp.

Function: lookup-condition (number)
Package

gsll.

Source

conditions.lisp.

Function: make-and-init-vector (element-type size &key init-offset)

Make a vector of the given element type and size. If init-offset is given, it is assumed to be a valid number, with which the vector is initialised; each element is set to a unique, predetermined value. See also test.c in GSL’s fft directory.

Package

gsll.

Source

example.lisp.

Function: make-cbstruct (struct slots-values &rest function-slotnames)

Make the callback structure.

Package

gsll.

Source

callback.lisp.

Function: make-cbstruct-object (class)

Make the callback structure based on the mobject definition.

Package

gsll.

Source

callback-compile-defs.lisp.

Function: make-compiled-funcallable (function fnspec scalarsp dimensions)
Package

gsll.

Source

funcallable.lisp.

Function: make-defmcallbacks (cbinfo callback-names function-names)
Package

gsll.

Source

callback.lisp.

Function: make-exponent-fit-data (&key n y sigma)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: make-fft-complex-wavetable-double-float (n)

Create the GSL object representing a structure that holds the factorization and trigonometric lookup tables for the mixed radix complex fft algorithm (class FFT-COMPLEX-WAVETABLE-DOUBLE-FLOAT).
This function prepares a trigonometric lookup table for a complex FFT of
length n. The function returns a pointer to the newly allocated
gsl_fft_complex_wavetable if no errors were detected, and a null pointer in
the case of error. The length n is factorized into a product of
subtransforms, and the factors and their trigonometric coefficients are
stored in the wavetable. The trigonometric coefficients are computed using
direct calls to sin and cos, for accuracy. Recursion relations could be used
to compute the lookup table faster, but if an application performs many FFTs
of the same length then this computation is a one-off overhead which does
not affect the final throughput.

The wavetable structure can be used repeatedly for any transform of the same
length. The table is not modified by calls to any of the other FFT
functions. The same wavetable can be used for both forward and backward (or
inverse) transforms of a given length.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-complex-wavetable-single-float (n)

Create the GSL object representing a structure that holds the factorization and trigonometric lookup tables for the mixed radix complex float fft algorithm (class FFT-COMPLEX-WAVETABLE-SINGLE-FLOAT).
This function prepares a trigonometric lookup table for a complex float FFT
of length n. The function returns a pointer to the newly allocated
gsl_fft_complex_wavetable if no errors were detected, and a null pointer in
the case of error. The length n is factorized into a product of
subtransforms, and the factors and their trigonometric coefficients are
stored in the wavetable. The trigonometric coefficients are computed using
direct calls to sin and cos, for accuracy. Recursion relations could be used
to compute the lookup table faster, but if an application performs many FFTs
of the same length then this computation is a one-off overhead which does
not affect the final throughput.

The wavetable structure can be used repeatedly for any transform of the same
length. The table is not modified by calls to any of the other FFT
functions. The same wavetable can be used for both forward and backward (or
inverse) transforms of a given length.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-complex-workspace-double-float (n)

Create the GSL object representing a Structure that holds the additional working space required for the intermediate steps of the mixed radix complex fft algoritms (class FFT-COMPLEX-WORKSPACE-DOUBLE-FLOAT). This function allocates a workspace for a complex transform of length n.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-complex-workspace-single-float (n)

Create the GSL object representing a Structure that holds the additional working space required for the intermediate steps of the mixed radix complex float fft algoritms (class FFT-COMPLEX-WORKSPACE-SINGLE-FLOAT). This function allocates a workspace for a complex float transform of length
n.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-half-complex-wavetable-double-float (n)

Create the GSL object representing a structure that holds the factorization and trigonometric lookup tables for the mixed radix halfcomplex fft algorithm (class FFT-HALF-COMPLEX-WAVETABLE-DOUBLE-FLOAT).
These functions prepare trigonometric lookup tables for an FFT of size n
real elements. The functions return a pointer to the newly allocated struct
if no errors were detected, and a null pointer in the case of error. The
length n is factorized into a product of subtransforms, and the factors and
their trigonometric coefficients are stored in the wavetable. The
trigonometric coefficients are computed using direct calls to sin and cos,
for accuracy. Recursion relations could be used to compute the lookup table
faster, but if an application performs many FFTs of the same length then
computing the wavetable is a one-off overhead which does not affect the
final throughput.

The wavetable structure can be used repeatedly for any transform of the same
length. The table is not modified by calls to any of the other FFT
functions. The appropriate type of wavetable must be used for forward real
or inverse half-complex transforms.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-half-complex-wavetable-single-float (n)

Create the GSL object representing a structure that holds the factorization and trigonometric lookup tables for the mixed radix real float fft algorithm (class FFT-HALF-COMPLEX-WAVETABLE-SINGLE-FLOAT).
These functions prepare trigonometric lookup tables for an FFT of size n
real float elements. The functions return a pointer to the newly allocated
struct if no errors were detected, and a null pointer in the case of error.
The length n is factorized into a product of subtransforms, and the factors
and their trigonometric coefficients are stored in the wavetable. The
trigonometric coefficients are computed using direct calls to sin and cos,
for accuracy. Recursion relations could be used to compute the lookup table
faster, but if an application performs many FFTs of the same length then
computing the wavetable is a one-off overhead which does not affect the
final throughput.

The wavetable structure can be used repeatedly for any transform of the same
length. The table is not modified by calls to any of the other FFT
functions. The appropriate type of wavetable must be used for forward real
or inverse half-complex transforms.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-real-wavetable-double-float (n)

Create the GSL object representing a structure that holds the factorization and trigonometric lookup tables for the mixed radix real fft algorithm (class FFT-REAL-WAVETABLE-DOUBLE-FLOAT).
These functions prepare trigonometric lookup tables for an FFT of size n
real elements. The functions return a pointer to the newly allocated struct
if no errors were detected, and a null pointer in the case of error. The
length n is factorized into a product of subtransforms, and the factors and
their trigonometric coefficients are stored in the wavetable. The
trigonometric coefficients are computed using direct calls to sin and cos,
for accuracy. Recursion relations could be used to compute the lookup table
faster, but if an application performs many FFTs of the same length then
computing the wavetable is a one-off overhead which does not affect the
final throughput.

The wavetable structure can be used repeatedly for any transform of the same
length. The table is not modified by calls to any of the other FFT
functions. The appropriate type of wavetable must be used for forward real
or inverse half-complex transforms.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-real-wavetable-single-float (n)

Create the GSL object representing a structure that holds the factorization and trigonometric lookup tables for the mixed radix real float fft algorithm (class FFT-REAL-WAVETABLE-SINGLE-FLOAT).
These functions prepare trigonometric lookup tables for an FFT of size n
real float elements. The functions return a pointer to the newly allocated
struct if no errors were detected, and a null pointer in the case of error.
The length n is factorized into a product of subtransforms, and the factors
and their trigonometric coefficients are stored in the wavetable. The
trigonometric coefficients are computed using direct calls to sin and cos,
for accuracy. Recursion relations could be used to compute the lookup table
faster, but if an application performs many FFTs of the same length then
computing the wavetable is a one-off overhead which does not affect the
final throughput.

The wavetable structure can be used repeatedly for any transform of the same
length. The table is not modified by calls to any of the other FFT
functions. The appropriate type of wavetable must be used for forward real
or inverse half-complex transforms.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-real-workspace-double-float (n)

Create the GSL object representing a Structure that holds the additional working space required for the intermediate steps of the mixed radix real fft algoritms (class FFT-REAL-WORKSPACE-DOUBLE-FLOAT). This function allocates a workspace for a real transform of length n.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-fft-real-workspace-single-float (n)

Create the GSL object representing a Structure that holds the additional working space required for the intermediate steps of the mixed radix real float fft algoritms (class FFT-REAL-WORKSPACE-SINGLE-FLOAT). This function allocates a workspace for a real float transform of length
n.

Package

gsll.

Source

wavetable-workspace.lisp.

Function: make-foreign-array-from-mpointer (mpointer &optional element-type category-or-rank finalize)

Make the foreign array when a GSL pointer to a gsl-vector-c or gsl-matrix-c is given.

Package

gsll.

Source

foreign-array.lisp.

Function: make-funcallable-form (user-function fnspec scalarsp dimension-values)

Define a wrapper function to interface GSL with the user’s function. scalarsp will be either T or NIL, depending on whether the user function expects and returns scalars, and dimension-values should be a list of number(s), (dim0) or (dim0 dim1), or NIL.

Package

gsll.

Source

funcallable.lisp.

Function: make-funcallables-for-object (object)

Make compiled functions for the object that can be funcalled in the callback.

Package

gsll.

Source

funcallable.lisp.

Function: make-gsl-metadata (object)

Make the necessary GSL metadata (mpointer and block-pointer) for the given foreign array, and return the mpointer. This should only be called by #’mpointer the first time it is called on a particular foreign-array.

Package

gsll.

Source

foreign-array.lisp.

Function: make-initialize-instance (class cl-alloc-args cl-initialize-args prefix freer)
Package

gsll.

Source

mobject.lisp.

Function: make-list-from-pool (type length &optional starting)

Make a list for :initial-contents of the specified element type and length using the pool data for the type and starting at the specified point in the pool.

Package

gsll.

Source

generate-examples.lisp.

Function: make-mobject-defmcallbacks (cbinfo class)

Make the defmcallback forms needed to define the callbacks associated with mobject that includes callback functions.

Package

gsll.

Source

callback-compile-defs.lisp.

Function: make-new-sa-state (&rest arguments)

Make a new simulated annealing state.
Pass any arguments to user-state-maker-function.

Package

gsll.

Source

simulated-annealing.lisp.

Function: make-ntuple-example-data (&optional filename)
Package

gsll.

Source

ntuple.lisp.

Function: make-reinitialize-instance (class cl-initialize-args initialize-name prefix initialize-suffix initialize-args inputs cbinfo superclasses switch ri-c-return)

Expand the reinitialize-instance form.

Package

gsll.

Source

mobject.lisp.

Function: make-sa-states (length)
Package

gsll.

Source

simulated-annealing.lisp.

Function: make-symbol-cardinal (name i &optional intern-package)
Package

gsll.

Source

utility.lisp.

Function: make-symbol-cardinals (name max-count &optional intern-package)
Package

gsll.

Source

utility.lisp.

Function: make-urand-vector (element-type dimension &key stride init-offset)

Make a vector with random elements.

Package

gsll.

Source

example.lisp.

Function: map-name (cl-name gsl-name)
Package

gsll.

Source

interface.lisp.

Function: mappend (fn &rest lsts)

maps elements in list and finally appends all resulted lists.

Package

gsll.

Source

utility.lisp.

Function: matrix-product-dimensions (a b &key transa transb)
Package

gsll.

Source

blas2.lisp.

Function: mcrw (x y z)

Example function for Monte Carlo used in random walk studies.

Package

gsll.

Source

monte-carlo.lisp.

Function: mean-2x (histogram)

The mean of the histogrammed x variable, where the histogram is regarded as a probability distribution. Negative bin values are ignored for the purposes of this calculation.

Package

gsll.

Source

statistics.lisp.

Function: mean-2y (histogram)

The mean of the histogrammed y variable, where the histogram is regarded as a probability distribution. Negative bin values are ignored for the purposes of this calculation.

Package

gsll.

Source

statistics.lisp.

Function: minimization-one-example (&optional minimizer-type print-steps with-values)

Solving a minimum, the example given in Sec. 33.8 of the GSL manual.

Package

gsll.

Source

minimization-one.lisp.

Function: mobject-cbvname (class-name &optional count)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: mobject-cbvnames (class-name &optional count)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: mobject-fnvname (class-name &optional count)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: mobject-fnvnames (class-name &optional count)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: mobject-maker (maker arglists class cl-alloc-args initialize-when-making cl-initialize-args description documentation initialize-args initializerp settingp singular cbinfo)

Make the defun form that makes the mobject.

Package

gsll.

Source

mobject.lisp.

Function: mobject-variable-name (class-name suffix &optional count)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: multimin-example-derivative (&optional method print-steps)

This is an example solving the multidimensional minimization problem of a paraboloid using the derivative. The callback functions paraboloid-vector and paraboloid-derivative expect vectors. Contrast this with multimin-example-derivative-scalars, which expects and returns the scalar components.

Package

gsll.

Source

minimization-multi.lisp.

Function: multimin-example-derivative-scalars (&optional method print-steps)

This is an example solving the multidimensional minimization problem of a paraboloid using the derivative. The callback functions paraboloid-scalar and paraboloid-derivative-scalar expect scalars. Contrast this with multimin-example-derivative, which
expects and returns vectors.

Package

gsll.

Source

minimization-multi.lisp.

Function: multimin-example-no-derivative (&optional method print-steps)
Package

gsll.

Source

minimization-multi.lisp.

Function: multiroot-slot (solver slot)
Package

gsll.

Source

roots-multi.lisp.

Function: mv-linear-least-squares-data ()

Generate data for second example in Section 36.5 of the GSL manual.

Package

gsll.

Source

linear-least-squares.lisp.

Function: next-float (float &optional increment)
Package

gsll.

Source

floating-point.lisp.

Function: nonlinear-least-squares-example (&optional number-of-observations method print-steps)
Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: norm-f (fit)

Find the norm of the fit function f.

Package

gsll.

Source

nonlinear-least-squares.lisp.

Function: ntuple-example-histogramming (&optional filename)
Package

gsll.

Source

ntuple.lisp.

Function: ntuple-example-make-read ()

Create an ntuple historgram example data file, and read it.

Package

gsll.

Source

ntuple.lisp.

Function: ntuple-example-read (&optional filename)
Package

gsll.

Source

ntuple.lisp.

Function: ntuple-example-sel-func (ntuple-data)
Package

gsll.

Source

ntuple.lisp.

Function: ntuple-example-val-func (ntuple-data)
Package

gsll.

Source

ntuple.lisp.

Function: ntuple-example-values (i)
Package

gsll.

Source

ntuple.lisp.

Function: number-of-callbacks (cbinfo)
Package

gsll.

Source

callback.lisp.

Function: optional-args-to-switch-gsl-functions (arglist gsl-name)

The presence/absence of optional arguments will switch between the first and second listed GSL function names.

Package

gsll.

Source

defmfun.lisp.

Function: paraboloid-and-derivative (arguments-gv-pointer value-pointer derivative-gv-pointer)
Package

gsll.

Source

minimization-multi.lisp.

Function: paraboloid-and-derivative-scalar (x y)
Package

gsll.

Source

minimization-multi.lisp.

Function: paraboloid-derivative (xy output)
Package

gsll.

Source

minimization-multi.lisp.

Function: paraboloid-derivative-scalar (x y)
Package

gsll.

Source

minimization-multi.lisp.

Function: paraboloid-scalar (x y)

A paraboloid function of two arguments, given in GSL manual Sec. 35.4. This version takes scalar arguments.

Package

gsll.

Source

minimization-multi.lisp.

Function: paraboloid-vector (xy)

A paraboloid function of two arguments, given in GSL manual Sec. 35.4. This version takes a vector-double-float argument.

Package

gsll.

Source

minimization-multi.lisp.

Function: parse-callback-argspec (argspec component)

From the :callbacks argument, parse a single argument of a single function specification.

Package

gsll.

Source

callback.lisp.

Function: parse-callback-fnspec (fnspec component)

From the :callbacks argument, parse a single function specification.

Package

gsll.

Source

callback.lisp.

Function: parse-callback-static (cbinfo component)

Get the information component from the callbacks list.

Package

gsll.

Source

callback.lisp.

Function: perm-copy (source destination)

Copy the elements of the permutation source into the
permutation destination. The two permutations must have the same size.

Package

gsll.

Source

permutation.lisp.

Function: plural-symbol (symbol)

Make the plural form of this symbol.

Package

gsll.

Source

mobject.lisp.

Function: powell (arg0 arg1)

Powell’s test function.

Package

gsll.

Source

roots-multi.lisp.

Function: power-of-2-p (num)

The integer is a power of 2.

Package

gsll.

Source

forward.lisp.

Function: quadratic (x)
Package

gsll.

Source

roots-one.lisp.

Function: quadratic-and-derivative (x)
Package

gsll.

Source

roots-one.lisp.

Function: quadratic-derivative (x)
Package

gsll.

Source

roots-one.lisp.

Function: quasi-clone (instance)
Package

gsll.

Source

quasi.lisp.

Function: quasi-copy (source destination)

Copy the quasi-random sequence generator src into the pre-existing generator dest, making dest into an exact copy of src. The two generators must be of the same type.

Package

gsll.

Source

quasi.lisp.

Function: random-walk-miser-example (&optional nsamples)
Package

gsll.

Source

monte-carlo.lisp.

Function: random-walk-plain-example (&optional nsamples)
Package

gsll.

Source

monte-carlo.lisp.

Function: random-walk-vegas-example (&optional nsamples)
Package

gsll.

Source

monte-carlo.lisp.

Function: realpart-vector (complex-vector &key stride init-offset)

The real vector consisting of the real part of the complex vector.

Package

gsll.

Source

example.lisp.

Function: record-callbacks-for-class (class cbinfo)
Package

gsll.

Source

callback-compile-defs.lisp.

Function: reference-foreign-element (foreign-pointer-name linear-index argspec dimension-values)

Create the form to reference the element of a foreign array, or a scalar, for getting or setting.

Package

gsll.

Source

funcallable.lisp.

Function: reset-urand ()
Package

gsll.

Source

example.lisp.

Function: rng-clone (source)
Package

gsll.

Source

generators.lisp.

Function: rng-copy (source destination)

Copy the random number generator source into the pre-existing generator destination,
making destination into an exact copy
of source. The two generators must be of the same type.

Package

gsll.

Source

generators.lisp.

Function: rng-types-setup ()

A pointer to an array of all the available generator types, terminated by a null pointer. The function should be called once at the start of the program, if needed. Users should call all-random-number-generators.

Package

gsll.

Source

rng-types.lisp.

Function: roots-multi-example-derivative (&optional method print-steps)

Solving Rosenbrock with derivatives, the example given in Sec. 34.8 of the GSL manual.

Package

gsll.

Source

roots-multi.lisp.

Function: roots-multi-example-no-derivative (&optional method print-steps)

Solving Rosenbrock, the example given in Sec. 34.8 of the GSL manual.

Package

gsll.

Source

roots-multi.lisp.

Function: roots-one-example-derivative (&optional method print-steps)

Solving a quadratic, the example given in Sec. 32.10 of the GSL manual.

Package

gsll.

Source

roots-one.lisp.

Function: roots-one-example-no-derivative (&optional method print-steps)

Solving a quadratic, the example given in Sec. 32.10 of the GSL manual.

Package

gsll.

Source

roots-one.lisp.

Function: rosenbrock (arg0 arg1)

Rosenbrock test function.

Package

gsll.

Source

roots-multi.lisp.

Function: rosenbrock-df (arg0 arg1)

The partial derivatives of the Rosenbrock functions.

Package

gsll.

Source

roots-multi.lisp.

Function: rosenbrock-fdf (arg0 arg1)
Package

gsll.

Source

roots-multi.lisp.

Function: sa-state-value (foreign-pointer)
Package

gsll.

Source

simulated-annealing.lisp.

Function: scalar-default (&optional float-type)

Make a scalar of the current type from the pool. For complex types, setting float-type will select a real of the corresponding component float type.

Package

gsll.

Source

generate-examples.lisp.

Function: set-cbstruct (cbstruct structure-name slots-values function-slotnames)

Make the slots in the foreign callback structure.

Package

gsll.

Source

callback.lisp.

Function: set-mcm-parameters (object params)

Set the parameter for the MISER method.

Package

gsll.

Source

monte-carlo.lisp.

Function: set-mcv-parameters (object params)
Package

gsll.

Source

monte-carlo.lisp.

Function: set-parameters (foreign-structure structure-name)

Set the parameters slot to null.

Package

gsll.

Source

callback.lisp.

Function: set-parameters-gen (ws &optional compute-shur-form-s compute-shur-form-t balance)
Package

gsll.

Source

nonsymmetric-generalized.lisp.

Function: set-parameters-nonsymmetric (ws &optional compute-shur-form balance)
Package

gsll.

Source

nonsymmetric.lisp.

Function: set-slot-function (foreign-structure structure-name slot-name gsl-function)

Set the slot in the cbstruct to the callback corresponding to gsl-function. If gsl-function is nil, set to the null-pointer.

Package

gsll.

Source

callback.lisp.

Function: set-structure-slot (foreign-structure structure-name slot-name value)
Package

gsll.

Source

callback.lisp.

Function: sf-check-results (result-list expected-value tolerance)

Check the results of multiple returns where each value may have an error estimate returned as well.

Package

gsll.

Source

augment.lisp.

Function: sf-check-single (result expected-value tolerance &optional error-estimate)

Check the result of a single value as in test_sf_check_result in specfunc/test_sf.c.

Package

gsll.

Source

augment.lisp.

Function: sf-frac-diff (x1 x2)
Package

gsll.

Source

augment.lisp.

Function: sigma-2x (histogram)
Package

gsll.

Source

statistics.lisp.

Function: sigma-2y (histogram)
Package

gsll.

Source

statistics.lisp.

Function: signal-gsl-error (number explanation &optional file line)

Signal an error from the GSL library.

Package

gsll.

Source

conditions.lisp.

Function: signal-gsl-warning (number explanation &optional file line)

Signal a warning from the GSL library.

Package

gsll.

Source

conditions.lisp.

Function: simulated-annealing-example ()
Package

gsll.

Source

simulated-annealing.lisp.

Function: simulated-annealing-int (parameters generator x0-p energy-function step-function metric-function)
Package

gsll.

Source

simulated-annealing.lisp.

Function: simulated-annealing-test (initial-value)
Package

gsll.

Source

simulated-annealing.lisp.

Function: singular-symbol (symbol)

Make the singular form of this symbol.

Package

gsll.

Source

mobject.lisp.

Function: singularize (symbols form)

In the form, replace the plural symbol with the singular symbol given.

Package

gsll.

Source

mobject.lisp.

Function: size-array (array-or-size)
Package

gsll.

Source

linear-least-squares.lisp.

Function: size-vector-scalar (vector &key stride)

Return the size of a vector while taking the stride into account.

Package

gsll.

Source

example.lisp.

Function: solve-tridiagonal-example (&optional n)

Solution differential equation
y=1 with boundary conditions y(0)=(n-1)^2, y(n-1)=0.

The solution is the sequence: (n-1)^2, (n-2)^2, ... 9, 4, 2, 1, 0

Desicretization of y leads to a tridiagonal system of equations (y_(i-1)-2_i+y_(i+1))/2 = 1 for 1 < i < (n - 2)

The boundary conditions are implemented as
y(0)=(n-1)^2
y(n-1)=0

Package

gsll.

Source

diagonal.lisp.

Function: spline-example (&optional step)

The first example in Sec. 26.7 of the GSL manual.

Package

gsll.

Source

spline-example.lisp.

Function: state-pointer (foreign-pointer)
Package

gsll.

Source

simulated-annealing.lisp.

Function: stupid-code-walk-eval-some (form eval-list)

Walk the form and if the first symbol of the list is a member of eval-list, evaluate it and use the result. Otherwise use the result as-is.

Package

gsll.

Source

generate-examples.lisp.

Function: stupid-code-walk-find-variables (sexp)

This will work with the simplest s-expression forms only to find variables used.

Package

gsll.

Source

defmfun-single.lisp.

Function: success-continue (value)

If status is +success+, return T, otherwise return NIL.

Package

gsll.

Source

interface.lisp.

Function: success-failure (value)

If status is either +success+ or +continue+, return T; otherwise, return NIL.

Package

gsll.

Source

interface.lisp.

Function: symbol-keyword-symbol (symbol &optional singular)

Make a list of key symbol, listifying if singular.

Package

gsll.

Source

mobject.lisp.

Function: test-cholesky-decomp-dim (matrix)

Decompose using Cholesky and then multiply.

Package

gsll.

Source

cholesky.lisp.

Function: test-cholesky-invert-dim (matrix)

Invert using Cholesky decomposition

Package

gsll.

Source

cholesky.lisp.

Function: test-cholesky-solve-dim (matrix)

Solve the linear equation using Cholesky with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

cholesky.lisp.

Function: test-complex-fft-noise (vector &key stride non-radix-2)

Test forward, inverse and backward FFT for a complex vector and return all three results.

Package

gsll.

Source

example.lisp.

Function: test-fft-noise (element-type size &key stride non-radix-2)

A test of real forward and complex forward, reverse, and inverse FFT
on random noise. Returns the result of the DFT forward Fourier transformation and the forward FFT, which should be the same, and the original vector and the inverse FFT, which should also be the same. In addition,
the backward Fourier transform is returned for complex vectors, which should be the same as the last two.

Package

gsll.

Source

example.lisp.

Function: test-hh-solve-dim (matrix)

Solve the linear equation using Householder with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

householder.lisp.

Function: test-lu-solve-dim (matrix &optional vector)

Solve the linear equation using LU with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

lu.lisp.

Function: test-qr-decomp-dim (matrix)

Solve the QR decomposition with the supplied
matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

qr.lisp.

Function: test-qr-lssolve-dim (matrix)

Solve the linear equation using QR least squares with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index. Returns the solution and the residual.

Package

gsll.

Source

qr.lisp.

Function: test-qr-qrsolve-dim (matrix)

Solve the linear equation using QR with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

qr.lisp.

Function: test-qr-solve-dim (matrix)

Solve the linear equation using QR with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

qr.lisp.

Function: test-qr-update-dim (matrix)

Test QR rank-1 update; this should return a matrix with all elements near zero.

Package

gsll.

Source

qr.lisp.

Function: test-qrpt-decomp-dim (matrix)

Solve the QRPT decomposition with the supplied
matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

qrpt.lisp.

Function: test-qrpt-qrsolve-dim (matrix)

Solve the linear equation using QRPT with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

qrpt.lisp.

Function: test-qrpt-solve-dim (matrix)

Solve the linear equation using QRPT with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

qrpt.lisp.

Function: test-real-fft-noise (vector &key stride non-radix-2)

Test forward and inverse FFT for a real vector, and return both results in unpacked form.

Package

gsll.

Source

example.lisp.

Function: test-sv-solve-dim (matrix)

Solve the linear equation using SVD with the supplied matrix and a right-hand side vector which is the reciprocal of one more than the index.

Package

gsll.

Source

svd.lisp.

Function: testpdf (pdf-function &rest distribution)

Test the probability density function in the same way that GSL does. If everything is functioning correctly, this will return T.

Package

gsll.

Source

tests.lisp.

Function: trivial-example-energy (state)
Package

gsll.

Source

simulated-annealing.lisp.

Function: trivial-example-metric (state1 state2)
Package

gsll.

Source

simulated-annealing.lisp.

Function: trivial-example-step (rng-mpointer state step-size)
Package

gsll.

Source

simulated-annealing.lisp.

Function: trivial-test-energy (state)
Package

gsll.

Source

simulated-annealing.lisp.

Function: urand ()

Generate a random number. See fft/urand.c.

Package

gsll.

Source

example.lisp.

Function: value-from-dimensions (argspec dimension-values &optional total)

Return argspec ’dimensions with numerical sizes for dimensions substituted for dim0, dim1. If total = T, then return the product of those dimensions. The list dimensions-values is a list of one or two numerical values, (dim0-value dim1-value) or (dim0-value).

Package

gsll.

Source

funcallable.lisp.

Function: values-unless-singleton (forms)
Package

gsll.

Source

body-expand.lisp.

Function: values-with-errors (&rest values-sfr)

Return numbers as values and errors.

Package

gsll.

Source

return-structures.lisp.

Function: vanderpol (time y0 y1)
Package

gsll.

Source

ode-example.lisp.

Function: vanderpol-jacobian (time y0 y1)
Package

gsll.

Source

ode-example.lisp.

Function: variables-used-in-c-arguments (c-arguments)

Find the arguments passed to the C function. This is a poor quality code walker, but is sufficient for actual usage of defmfun.

Package

gsll.

Source

defmfun-single.lisp.

Function: vdf (size-or-array &optional type)

Make or take a vector.

Package

gsll.

Source

return-structures.lisp.

Function: vdf-size (size-or-array)

Size of vector made with vfd.

Package

gsll.

Source

return-structures.lisp.

Function: vector/length (vector &key stride)
Package

gsll.

Source

example.lisp.

Function: view-bin-as-foreign-array (histogram)

A view of the histogram bin counts as a foreign array. The two objects point to the same foreign data.

Package

gsll.

Source

histogram.lisp.

Function: view-range-as-foreign-array (histogram)

A view of the histogram range as a foreign array. This vector has one more element than the number of bins; the first element is the lower bound of the first bin, and the last element is the upper bound of the last bin. The two objects point to the same foreign data.

Package

gsll.

Source

histogram.lisp.

Function: vspecs-direction (argspecs direction &optional array-only)

Find the specs for all variables, or all array variables, with the specified direction.

Package

gsll.

Source

funcallable.lisp.

Function: wavelet-example (&optional cl-data)

Demonstrates the use of the one-dimensional wavelet transform functions. It computes an approximation to an input signal (of length 256) using the 20 largest components of the wavelet transform, while setting the others to zero. See GSL manual Section 30.4.

Package

gsll.

Source

wavelet.lisp.

Function: wavelet-forward-example (&optional cl-data)

Simpler example, with only a Daubechies wavelet forward transformation.

Package

gsll.

Source

wavelet.lisp.

Function: wfo-declare (d cbinfo)
Package

gsll.

Source

interface.lisp.

Function: wrap-index-export (expanded-body name gsl-name key-args)

Wrap the expanded-body with index and export if requested. Use a progn if needed.

Package

gsll.

Source

defmfun.lisp.

Function: wrap-letlike (when binding wrapping body)
Package

gsll.

Source

defmfun-single.lisp.

Function: wrap-progn (args)

Wrap the arguments in a progn.

Package

gsll.

Source

defmfun.lisp.


5.2.5 Generic functions

Generic Function: alloc-from-block (object blockptr)

Allocate memory for the GSL struct given a block pointer.

Package

gsll.

Source

both.lisp.

Methods
Method: alloc-from-block ((object matrix-unsigned-byte-64) blockptr)
Method: alloc-from-block ((object matrix-signed-byte-64) blockptr)
Method: alloc-from-block ((object matrix-unsigned-byte-32) blockptr)
Method: alloc-from-block ((object matrix-signed-byte-32) blockptr)
Method: alloc-from-block ((object matrix-unsigned-byte-16) blockptr)
Method: alloc-from-block ((object matrix-signed-byte-16) blockptr)
Method: alloc-from-block ((object matrix-unsigned-byte-8) blockptr)
Method: alloc-from-block ((object matrix-signed-byte-8) blockptr)
Method: alloc-from-block ((object matrix-complex-double-float) blockptr)
Method: alloc-from-block ((object matrix-complex-single-float) blockptr)
Method: alloc-from-block ((object matrix-double-float) blockptr)
Method: alloc-from-block ((object matrix-single-float) blockptr)
Method: alloc-from-block ((object vector-single-float) blockptr)
Method: alloc-from-block ((object vector-double-float) blockptr)
Method: alloc-from-block ((object vector-complex-single-float) blockptr)
Method: alloc-from-block ((object vector-complex-double-float) blockptr)
Method: alloc-from-block ((object vector-signed-byte-8) blockptr)
Method: alloc-from-block ((object vector-unsigned-byte-8) blockptr)
Method: alloc-from-block ((object vector-signed-byte-16) blockptr)
Method: alloc-from-block ((object vector-unsigned-byte-16) blockptr)
Method: alloc-from-block ((object vector-signed-byte-32) blockptr)
Method: alloc-from-block ((object vector-unsigned-byte-32) blockptr)
Method: alloc-from-block ((object vector-signed-byte-64) blockptr)
Method: alloc-from-block ((object vector-unsigned-byte-64) blockptr)
Generic Function: allocate (object &key order number-of-breakpoints solver-type dimensions number-of-observations number-of-parameters type size member absolute-error relative-error y-scaling dydt-scaling absolute-scale dimension dim omega l trig n alpha beta mu nu number-of-bins-x number-of-bins-y number-of-bins probabilities rng-type qmax &allow-other-keys)

Use GSL to allocate memory. Returns pointer but does not bind mpointer slot.

Package

gsll.

Source

mobject.lisp.

Methods
Method: allocate ((object basis-spline) &key order number-of-breakpoints)
Source

basis-splines.lisp.

Method: allocate ((object nonlinear-fdffit) &key solver-type dimensions)
Source

nonlinear-least-squares.lisp.

Method: allocate ((object nonlinear-ffit) &key solver-type dimensions)
Source

nonlinear-least-squares.lisp.

Method: allocate ((object fit-workspace) &key number-of-observations number-of-parameters)
Source

linear-least-squares.lisp.

Method: allocate ((object multi-dimensional-minimizer-fdf) &key type dimensions)
Source

minimization-multi.lisp.

Method: allocate ((object multi-dimensional-minimizer-f) &key type dimensions)
Source

minimization-multi.lisp.

Method: allocate ((object multi-dimensional-root-solver-fdf) &key type dimensions)
Source

roots-multi.lisp.

Method: allocate ((object multi-dimensional-root-solver-f) &key type dimensions)
Source

roots-multi.lisp.

Method: allocate ((object one-dimensional-minimizer) &key type)
Source

minimization-one.lisp.

Method: allocate ((object one-dimensional-root-solver-fdf) &key type)
Source

roots-one.lisp.

Method: allocate ((object one-dimensional-root-solver-f) &key type)
Source

roots-one.lisp.

Method: allocate ((object hankel) &key size)
Source

hankel.lisp.

Method: allocate ((object wavelet-workspace) &key size)
Source

wavelet.lisp.

Method: allocate ((object wavelet) &key type member)
Source

wavelet.lisp.

Method: allocate ((object levin-truncated) &key order)
Source

series-acceleration.lisp.

Method: allocate ((object levin) &key order)
Source

series-acceleration.lisp.

Method: allocate ((object chebyshev) &key order)
Source

chebyshev.lisp.

Method: allocate ((object acceleration) &key)
Source

lookup.lisp.

Method: allocate ((object spline) &key type size)
Source

interpolation.lisp.

Method: allocate ((object interpolation) &key type size)
Source

interpolation.lisp.

Method: allocate ((object ode-evolution) &key dimensions)
Source

evolution.lisp.

Method: allocate ((object scaled-control) &key absolute-error relative-error y-scaling dydt-scaling absolute-scale dimension)
Source

control.lisp.

Method: allocate ((object yp-control) &key absolute-error relative-error)
Source

control.lisp.

Method: allocate ((object y-control) &key absolute-error relative-error)
Source

control.lisp.

Method: allocate ((object standard-control) &key absolute-error relative-error y-scaling dydt-scaling)
Source

control.lisp.

Method: allocate ((object ode-stepper) &key type dimensions)
Source

stepping.lisp.

Method: allocate ((object monte-carlo-vegas) &key dim)
Source

monte-carlo.lisp.

Method: allocate ((object monte-carlo-miser) &key dim)
Source

monte-carlo.lisp.

Method: allocate ((object monte-carlo-plain) &key dim)
Source

monte-carlo.lisp.

Method: allocate ((object qawo-table) &key omega l trig n)
Source

numerical-integration-with-tables.lisp.

Method: allocate ((object qaws-table) &key alpha beta mu nu)
Source

numerical-integration-with-tables.lisp.

Method: allocate ((object integration-workspace) &key size)
Source

numerical-integration.lisp.

Method: allocate ((object histogram2d-pdf) &key number-of-bins-x number-of-bins-y)
Source

probability-distribution.lisp.

Method: allocate ((object histogram-pdf) &key number-of-bins)
Source

probability-distribution.lisp.

Method: allocate ((object histogram2d) &key number-of-bins-x number-of-bins-y)
Source

histogram.lisp.

Method: allocate ((object histogram) &key number-of-bins)
Source

histogram.lisp.

Method: allocate ((object discrete-random) &key probabilities)
Source

discrete.lisp.

Method: allocate ((object quasi-random-number-generator) &key rng-type dimension)
Source

quasi.lisp.

Method: allocate ((object random-number-generator) &key rng-type)
Source

generators.lisp.

Method: allocate ((object fft-half-complex-wavetable-single-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-half-complex-wavetable-double-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-complex-workspace-single-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-complex-workspace-double-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-complex-wavetable-single-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-complex-wavetable-double-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-real-workspace-single-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-real-workspace-double-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-real-wavetable-single-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object fft-real-wavetable-double-float) &key n)
Source

wavetable-workspace.lisp.

Method: allocate ((object eigen-genv) &key n)
Source

nonsymmetric-generalized.lisp.

Method: allocate ((object eigen-gen) &key n)
Source

nonsymmetric-generalized.lisp.

Method: allocate ((object eigen-genhermv) &key n)
Source

generalized.lisp.

Method: allocate ((object eigen-genherm) &key n)
Source

generalized.lisp.

Method: allocate ((object eigen-gensymmv) &key n)
Source

generalized.lisp.

Method: allocate ((object eigen-gensymm) &key n)
Source

generalized.lisp.

Method: allocate ((object eigen-nonsymmv) &key n)
Source

nonsymmetric.lisp.

Method: allocate ((object eigen-nonsymm) &key n)
Source

nonsymmetric.lisp.

Method: allocate ((object eigen-hermv) &key n)
Source

symmetric-hermitian.lisp.

Method: allocate ((object eigen-herm) &key n)
Source

symmetric-hermitian.lisp.

Method: allocate ((object eigen-symmv) &key n)
Source

symmetric-hermitian.lisp.

Method: allocate ((object eigen-symm) &key n)
Source

symmetric-hermitian.lisp.

Method: allocate ((object mathieu) &key n qmax)
Source

mathieu.lisp.

Method: allocate ((object polynomial-complex-workspace) &key n)
Source

polynomial.lisp.

Method: allocate ((object permutation) &key size)
Source

permutation.lisp.

Generic Function: backward-fourier-transform-dif-radix2 (vector &key stride)

Backward decimation-in-frequency FFT on a vector for which (floor length stride) is a power of 2.

Package

gsll.

Source

backward.lisp.

Methods
Method: backward-fourier-transform-dif-radix2 ((vector vector-complex-single-float) &key stride)
Method: backward-fourier-transform-dif-radix2 ((vector vector-complex-double-float) &key stride)
Generic Function: backward-fourier-transform-halfcomplex-nonradix2 (vector &key stride wavetable workspace)

Backward FFT on a vector for which (floor length stride) is not a power of 2, in half complex form.

Package

gsll.

Source

backward.lisp.

Methods
Method: backward-fourier-transform-halfcomplex-nonradix2 ((vector vector-single-float) &key stride wavetable workspace)
Method: backward-fourier-transform-halfcomplex-nonradix2 ((vector vector-double-float) &key stride wavetable workspace)
Generic Function: backward-fourier-transform-halfcomplex-radix2 (vector &key stride)

Backward FFT on a vector for which (floor length stride) is a power of 2, in half complex form.

Package

gsll.

Source

backward.lisp.

Methods
Method: backward-fourier-transform-halfcomplex-radix2 ((vector vector-single-float) &key stride)
Method: backward-fourier-transform-halfcomplex-radix2 ((vector vector-double-float) &key stride)
Generic Function: backward-fourier-transform-nonradix2 (vector &key stride wavetable workspace)

Backward FFT on a complex vector for which (floor length stride) is not a power of 2.

Package

gsll.

Source

backward.lisp.

Methods
Method: backward-fourier-transform-nonradix2 ((vector vector-complex-single-float) &key stride wavetable workspace)
Method: backward-fourier-transform-nonradix2 ((vector vector-complex-double-float) &key stride wavetable workspace)
Generic Function: backward-fourier-transform-radix2 (vector &key stride)

Backward FFT on a vector for which (floor length stride) is a power of 2.

Package

gsll.

Source

backward.lisp.

Methods
Method: backward-fourier-transform-radix2 ((vector vector-complex-single-float) &key stride)
Method: backward-fourier-transform-radix2 ((vector vector-complex-double-float) &key stride)
Generic Reader: callback-struct (object)
Package

gsll.

Methods
Reader Method: callback-struct ((callback-included-cl callback-included-cl))

automatically generated reader method

Source

callback-included.lisp.

Target Slot

callback.

Generic Reader: cbinfo (object)
Package

gsll.

Methods
Reader Method: cbinfo ((callback-included callback-included))

The specification form for static callback information.

Source

callback-included.lisp.

Target Slot

cbinfo.

Generic Reader: dimension-names (object)
Package

gsll.

Methods
Reader Method: dimension-names ((callback-included callback-included))

The names in the GSL struct for dimensions.

Source

callback-included.lisp.

Target Slot

dimension-names.

Generic Reader: error-number (condition)
Package

gsll.

Methods
Reader Method: error-number ((condition gsl-eof))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition failure-to-reach-tolerance-g))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition failure-to-reach-tolerance-x))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition failure-to-reach-tolerance-f))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition jacobian-not-improving))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition no-progress))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition table-limit-exceeded))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition cache-limit-exceeded))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition unimplemented-feature))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition unsupported-feature))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition divergence))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition singularity))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition nonsquare-matrix))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition nonconformant-dimensions))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition roundoff-failure))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition loss-of-accuracy))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition overflow))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition underflow))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition failure-to-reach-tolerance))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition invalid-tolerance))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition gsl-division-by-zero))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition exceeded-maximum-iterations))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition runaway-iteration))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition bad-function-supplied))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition memory-allocation-failure))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition sanity-check-failure))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition factorization-failure))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition generic-failure-2))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition generic-failure-1))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition invalid-argument))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition invalid-pointer))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition input-range))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition input-domain))
Source

conditions.lisp.

Target Slot

error-number.

Reader Method: error-number ((condition gsl-condition))
Source

conditions.lisp.

Target Slot

error-number.

Generic Reader: error-text (condition)
Package

gsll.

Methods
Reader Method: error-text ((condition gsl-eof))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition failure-to-reach-tolerance-g))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition failure-to-reach-tolerance-x))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition failure-to-reach-tolerance-f))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition jacobian-not-improving))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition no-progress))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition table-limit-exceeded))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition cache-limit-exceeded))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition unimplemented-feature))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition unsupported-feature))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition divergence))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition singularity))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition nonsquare-matrix))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition nonconformant-dimensions))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition roundoff-failure))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition loss-of-accuracy))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition overflow))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition underflow))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition failure-to-reach-tolerance))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition invalid-tolerance))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition gsl-division-by-zero))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition exceeded-maximum-iterations))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition runaway-iteration))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition bad-function-supplied))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition memory-allocation-failure))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition sanity-check-failure))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition factorization-failure))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition generic-failure-2))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition generic-failure-1))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition invalid-argument))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition invalid-pointer))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition input-range))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition input-domain))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition unspecified-errno))
Source

conditions.lisp.

Target Slot

error-text.

Reader Method: error-text ((condition gsl-condition))
Source

conditions.lisp.

Target Slot

error-text.

Generic Reader: explanation (condition)
Package

gsll.

Methods
Reader Method: explanation ((condition gsl-condition))
Source

conditions.lisp.

Target Slot

explanation.

Generic Function: fft-half-complex-radix2-unpack (vector &key stride output)

Convert an array of half-complex coefficients as returned by real-fft-radix2-transform, into an ordinary complex array.

Package

gsll.

Source

unpack.lisp.

Methods
Method: fft-half-complex-radix2-unpack ((vector vector-single-float) &key stride output)
Method: fft-half-complex-radix2-unpack ((vector vector-double-float) &key stride output)
Generic Function: fft-half-complex-unpack (vector &key stride output)

This function converts an array of half-complex coefficients as returned by fft-real-transform, into an ordinary complex array. It fills in the complex array using the symmetry z_k = z_{n-k}^* to reconstruct the redundant elements.

Package

gsll.

Source

unpack.lisp.

Methods
Method: fft-half-complex-unpack ((vector vector-single-float) &key stride output)
Method: fft-half-complex-unpack ((vector vector-double-float) &key stride output)
Generic Function: fft-real-unpack (vector &key stride output)

This function converts a single real array into an equivalent complex array (with imaginary part set to zero), suitable for fft-complex routines.

Package

gsll.

Source

unpack.lisp.

Methods
Method: fft-real-unpack ((vector vector-single-float) &key stride output)
Method: fft-real-unpack ((vector vector-double-float) &key stride output)
Generic Function: forward-fourier-transform-dif-radix2 (vector &key stride)

Forward decimation-in-frequency FFT on a vector for which (floor length stride) is a power of 2.

Package

gsll.

Source

forward.lisp.

Methods
Method: forward-fourier-transform-dif-radix2 ((vector vector-complex-single-float) &key stride)
Method: forward-fourier-transform-dif-radix2 ((vector vector-complex-double-float) &key stride)
Generic Function: forward-fourier-transform-halfcomplex-nonradix2 (vector &key stride wavetable workspace)

Forward FFT on a vector for which (floor length stride) is not a power of 2, in half complex form.

Package

gsll.

Source

forward.lisp.

Methods
Method: forward-fourier-transform-halfcomplex-nonradix2 ((vector vector-single-float) &key stride wavetable workspace)
Method: forward-fourier-transform-halfcomplex-nonradix2 ((vector vector-double-float) &key stride wavetable workspace)
Generic Function: forward-fourier-transform-halfcomplex-radix2 (vector &key stride)

Forward FFT on a vector for which (floor length stride) is a power of 2, in half complex form.

Package

gsll.

Source

forward.lisp.

Methods
Method: forward-fourier-transform-halfcomplex-radix2 ((vector vector-single-float) &key stride)
Method: forward-fourier-transform-halfcomplex-radix2 ((vector vector-double-float) &key stride)
Generic Function: forward-fourier-transform-nonradix2 (vector &key stride wavetable workspace)

Forward FFT on a vector for which (floor length stride) is not a power of 2.

Package

gsll.

Source

forward.lisp.

Methods
Method: forward-fourier-transform-nonradix2 ((vector vector-single-float) &key stride wavetable workspace)
Method: forward-fourier-transform-nonradix2 ((vector vector-double-float) &key stride wavetable workspace)
Method: forward-fourier-transform-nonradix2 ((vector vector-complex-single-float) &key stride wavetable workspace)
Method: forward-fourier-transform-nonradix2 ((vector vector-complex-double-float) &key stride wavetable workspace)
Generic Function: forward-fourier-transform-radix2 (vector &key stride)

Forward FFT on a vector for which (floor length stride) is a power of 2.

Package

gsll.

Source

forward.lisp.

Methods
Method: forward-fourier-transform-radix2 ((vector vector-single-float) &key stride)
Method: forward-fourier-transform-radix2 ((vector vector-double-float) &key stride)
Method: forward-fourier-transform-radix2 ((vector vector-complex-single-float) &key stride)
Method: forward-fourier-transform-radix2 ((vector vector-complex-double-float) &key stride)
Generic Function: fourier-transform-dif-radix2 (vector direction &key stride n)

Decimation-in-frequency version of the FFT in the given direction for a complex radix-2 vector

Package

gsll.

Source

select-direction.lisp.

Methods
Method: fourier-transform-dif-radix2 ((vector vector-complex-single-float) direction &key stride n)
Method: fourier-transform-dif-radix2 ((vector vector-complex-double-float) direction &key stride n)
Generic Function: fourier-transform-radix2 (vector direction &key stride n)

FFT in the given direction for a complex radix-2 vector

Package

gsll.

Source

select-direction.lisp.

Methods
Method: fourier-transform-radix2 ((vector vector-complex-single-float) direction &key stride n)
Method: fourier-transform-radix2 ((vector vector-complex-double-float) direction &key stride n)
Generic Reader: funcallables (object)
Package

gsll.

Methods
Reader Method: funcallables ((callback-included callback-included))

The function objects that will be called by the callbacks.

Source

callback-included.lisp.

Target Slot

funcallables.

Generic Reader: functions (object)
Package

gsll.

Methods
Reader Method: functions ((callback-included callback-included))

The user functions as function designators.
These should correspond in order to the structure-slot-name list.

Source

callback-included.lisp.

Target Slot

functions.

Generic Reader: gsl-name (condition)
Package

gsll.

Methods
Reader Method: gsl-name ((condition obsolete-gsl-version))
Source

defmfun-single.lisp.

Target Slot

gsl-name.

Generic Reader: gsl-version (condition)
Package

gsll.

Methods
Reader Method: gsl-version ((condition obsolete-gsl-version))
Source

defmfun-single.lisp.

Target Slot

gsl-version.

Generic Function: inverse-fourier-transform-dif-radix2 (vector &key stride)

Inverse decimation-in-frequency FFT on a vector for which (floor length stride) is a power of 2.

Package

gsll.

Source

inverse.lisp.

Methods
Method: inverse-fourier-transform-dif-radix2 ((vector vector-complex-single-float) &key stride)
Method: inverse-fourier-transform-dif-radix2 ((vector vector-complex-double-float) &key stride)
Generic Function: inverse-fourier-transform-halfcomplex-nonradix2 (vector &key stride wavetable workspace)

Inverse FFT on a vector for which (floor length stride) is not a power of 2, in half complex form.

Package

gsll.

Source

inverse.lisp.

Methods
Method: inverse-fourier-transform-halfcomplex-nonradix2 ((vector vector-single-float) &key stride wavetable workspace)
Method: inverse-fourier-transform-halfcomplex-nonradix2 ((vector vector-double-float) &key stride wavetable workspace)
Generic Function: inverse-fourier-transform-halfcomplex-radix2 (vector &key stride)

Inverse FFT on a vector for which (floor length stride) is a power of 2, in half complex form.

Package

gsll.

Source

inverse.lisp.

Methods
Method: inverse-fourier-transform-halfcomplex-radix2 ((vector vector-single-float) &key stride)
Method: inverse-fourier-transform-halfcomplex-radix2 ((vector vector-double-float) &key stride)
Generic Function: inverse-fourier-transform-nonradix2 (vector &key stride wavetable workspace)

Inverse FFT on a complex vector for which (floor length stride) is not a power of 2.

Package

gsll.

Source

inverse.lisp.

Methods
Method: inverse-fourier-transform-nonradix2 ((vector vector-complex-single-float) &key stride wavetable workspace)
Method: inverse-fourier-transform-nonradix2 ((vector vector-complex-double-float) &key stride wavetable workspace)
Generic Function: inverse-fourier-transform-radix2 (vector &key stride)

Inverse FFT on a vector for which (floor length stride) is a power of 2.

Package

gsll.

Source

inverse.lisp.

Methods
Method: inverse-fourier-transform-radix2 ((vector vector-complex-single-float) &key stride)
Method: inverse-fourier-transform-radix2 ((vector vector-complex-double-float) &key stride)
Generic Reader: line-number (condition)
Package

gsll.

Methods
Reader Method: line-number ((condition gsl-condition))
Source

conditions.lisp.

Target Slot

line-number.

Generic Function: mpointer (object)
Package

gsll.

Methods
Method: mpointer ((object foreign-array))
Source

foreign-array.lisp.

Method: mpointer ((object system-area-pointer))
Source

mobject.lisp.

Reader Method: mpointer ((mobject mobject))

A pointer to the GSL representation of the object.

Source

mobject.lisp.

Target Slot

mpointer.

Generic Reader: scalarsp (object)
Package

gsll.

Methods
Reader Method: scalarsp ((callback-included callback-included))

Whether the function expect to be passed and return scalars or arrays.

Source

callback-included.lisp.

Target Slot

scalarsp.

Generic Reader: source-file (condition)
Package

gsll.

Methods
Reader Method: source-file ((condition gsl-condition))
Source

conditions.lisp.

Target Slot

source-file.


5.2.6 Conditions

Condition: obsolete-gsl-version

An error indicating that the currently loaded version of the GSL libary does not have the function defined.

Package

gsll.

Source

defmfun-single.lisp.

Direct superclasses

error.

Direct methods
Direct slots
Slot: name
Initargs

:name

Readers

name.

Writers

This slot is read-only.

Slot: gsl-name
Initargs

:gsl-name

Readers

gsl-name.

Writers

This slot is read-only.

Slot: gsl-version
Initargs

:gsl-version

Readers

gsl-version.

Writers

This slot is read-only.

Condition: unspecified-errno

Errno value from GNU Scientific Library not recognized.

Package

gsll.

Source

conditions.lisp.

Direct superclasses

gsl-condition.

Direct methods

error-text.

Direct slots
Slot: error-text
Allocation

:class

Initform

(quote "returned errno code not recognized")

Initargs

:error-text

Readers

error-text.

Writers

This slot is read-only.


5.2.7 Structures

Structure: exponent-fit-data
Package

gsll.

Source

nonlinear-least-squares.lisp.

Direct superclasses

structure-object.

Direct slots
Slot: n
Readers

exponent-fit-data-n.

Writers

(setf exponent-fit-data-n).

Slot: y
Readers

exponent-fit-data-y.

Writers

(setf exponent-fit-data-y).

Slot: sigma
Readers

exponent-fit-data-sigma.

Writers

(setf exponent-fit-data-sigma).


5.2.8 Classes

Class: callback-included

A mobject that includes a callback function or functions to GSL.

Package

gsll.

Source

callback-included.lisp.

Direct superclasses

mobject.

Direct subclasses
Direct methods
Direct slots
Slot: cbinfo

The specification form for static callback information.

Initargs

:cbinfo

Readers

cbinfo.

Writers

This slot is read-only.

Slot: dimension-names

The names in the GSL struct for dimensions.

Initargs

:dimension-names

Readers

dimension-names.

Writers

This slot is read-only.

Slot: functions

The user functions as function designators.
These should correspond in order to the structure-slot-name list.

Initargs

:functions

Readers

functions.

Writers

This slot is read-only.

Slot: funcallables

The function objects that will be called by the callbacks.

Initargs

:funcallables

Readers

funcallables.

Writers

This slot is read-only.

Slot: scalarsp

Whether the function expect to be passed and return scalars or arrays.

Initform

t

Initargs

:scalarsp

Readers

scalarsp.

Writers

This slot is read-only.

Slot: dimensions
Package

grid.

Initargs

:dimensions

Readers

dimensions.

Writers

This slot is read-only.

Class: callback-included-cl

A mobject that includes a callback function or functions, in which the pointer to the callback structure is stored in a CL class slot.

Package

gsll.

Source

callback-included.lisp.

Direct superclasses

callback-included.

Direct subclasses

ode-stepper.

Direct methods

callback-struct.

Direct slots
Slot: callback
Package

cffi.

Initargs

:callback

Readers

callback-struct.

Writers

This slot is read-only.

Class: combination

GSL combinations.

Package

gsll.

Source

combination.lisp.

Direct superclasses

vector-unsigned-byte-64.

Direct methods
Class: fft-complex-wavetable-double-float

The GSL representation of the structure that holds the factorization and trigonometric lookup tables for the mixed radix complex fft algorithm.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-complex-wavetable-single-float

The GSL representation of the structure that holds the factorization and trigonometric lookup tables for the mixed radix complex float fft algorithm.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-complex-workspace-double-float

The GSL representation of the Structure that holds the additional working space required for the intermediate steps of the mixed radix complex fft algoritms.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-complex-workspace-single-float

The GSL representation of the Structure that holds the additional working space required for the intermediate steps of the mixed radix complex float fft algoritms.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-half-complex-wavetable-double-float

The GSL representation of the structure that holds the factorization and trigonometric lookup tables for the mixed radix halfcomplex fft algorithm.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-half-complex-wavetable-single-float

The GSL representation of the structure that holds the factorization and trigonometric lookup tables for the mixed radix real float fft algorithm.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-real-wavetable-double-float

The GSL representation of the structure that holds the factorization and trigonometric lookup tables for the mixed radix real fft algorithm.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-real-wavetable-single-float

The GSL representation of the structure that holds the factorization and trigonometric lookup tables for the mixed radix real float fft algorithm.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-real-workspace-double-float

The GSL representation of the Structure that holds the additional working space required for the intermediate steps of the mixed radix real fft algoritms.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: fft-real-workspace-single-float

The GSL representation of the Structure that holds the additional working space required for the intermediate steps of the mixed radix real float fft algoritms.

Package

gsll.

Source

wavetable-workspace.lisp.

Direct superclasses

mobject.

Direct methods
Class: histogram-c-tclass
Package

gsll.

Source

histogram.lisp.

Direct superclasses
  • foreign-struct-type.
  • translatable-foreign-type.
Class: mobject
Package

gsll.

Source

mobject.lisp.

Direct subclasses
Direct methods

mpointer.

Direct slots
Slot: mpointer

A pointer to the GSL representation of the object.

Initargs

:mpointer

Readers

mpointer.

Writers

This slot is read-only.

Class: ntuple-data-tclass
Package

gsll.

Source

ntuple.lisp.

Direct superclasses
  • foreign-struct-type.
  • translatable-foreign-type.
Class: ode-control

Objects used for control of ordinary differential equation integration.

Package

gsll.

Source

control.lisp.

Direct superclasses

mobject.

Direct subclasses
Direct methods

name.

Class: simulated-annealing-parameters-tclass
Package

gsll.

Source

simulated-annealing.lisp.

Direct superclasses
  • foreign-struct-type.
  • translatable-foreign-type.

Appendix A Indexes


A.1 Concepts


A.2 Functions

Jump to:   %   (   1  
A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V   W   Z  
Index Entry  Section

%
%var-accessor-*gsl-version*: Private ordinary functions
%var-accessor-+akima-interpolation+: Private ordinary functions
%var-accessor-+bisection-fsolver+: Private ordinary functions
%var-accessor-+borosh13+: Private ordinary functions
%var-accessor-+brent-fminimizer+: Private ordinary functions
%var-accessor-+brent-fsolver+: Private ordinary functions
%var-accessor-+broyden+: Private ordinary functions
%var-accessor-+bspline-wavelet+: Private ordinary functions
%var-accessor-+bspline-wavelet-centered+: Private ordinary functions
%var-accessor-+cmrg+: Private ordinary functions
%var-accessor-+conjugate-fletcher-reeves+: Private ordinary functions
%var-accessor-+conjugate-polak-ribiere+: Private ordinary functions
%var-accessor-+coveyou+: Private ordinary functions
%var-accessor-+cubic-spline-interpolation+: Private ordinary functions
%var-accessor-+daubechies-wavelet+: Private ordinary functions
%var-accessor-+daubechies-wavelet-centered+: Private ordinary functions
%var-accessor-+default-seed+: Private ordinary functions
%var-accessor-+default-type+: Private ordinary functions
%var-accessor-+discrete-newton+: Private ordinary functions
%var-accessor-+false-position-fsolver+: Private ordinary functions
%var-accessor-+fishman18+: Private ordinary functions
%var-accessor-+fishman20+: Private ordinary functions
%var-accessor-+fishman2x+: Private ordinary functions
%var-accessor-+gfsr4+: Private ordinary functions
%var-accessor-+gnewton-mfdfsolver+: Private ordinary functions
%var-accessor-+golden-section-fminimizer+: Private ordinary functions
%var-accessor-+haar-wavelet+: Private ordinary functions
%var-accessor-+haar-wavelet-centered+: Private ordinary functions
%var-accessor-+halton+: Private ordinary functions
%var-accessor-+hybrid-scaled+: Private ordinary functions
%var-accessor-+hybrid-unscaled+: Private ordinary functions
%var-accessor-+knuthran+: Private ordinary functions
%var-accessor-+knuthran2+: Private ordinary functions
%var-accessor-+knuthran2002+: Private ordinary functions
%var-accessor-+lecuyer21+: Private ordinary functions
%var-accessor-+levenberg-marquardt+: Private ordinary functions
%var-accessor-+levenberg-marquardt-unscaled+: Private ordinary functions
%var-accessor-+linear-interpolation+: Private ordinary functions
%var-accessor-+minstd+: Private ordinary functions
%var-accessor-+mrg+: Private ordinary functions
%var-accessor-+mt19937+: Private ordinary functions
%var-accessor-+mt19937-1998+: Private ordinary functions
%var-accessor-+mt19937-1999+: Private ordinary functions
%var-accessor-+newton-fdfsolver+: Private ordinary functions
%var-accessor-+newton-mfdfsolver+: Private ordinary functions
%var-accessor-+niederreiter2+: Private ordinary functions
%var-accessor-+periodic-akima-interpolation+: Private ordinary functions
%var-accessor-+periodic-cubic-spline-interpolation+: Private ordinary functions
%var-accessor-+polynomial-interpolation+: Private ordinary functions
%var-accessor-+powells-hybrid+: Private ordinary functions
%var-accessor-+powells-hybrid-unscaled+: Private ordinary functions
%var-accessor-+quad-golden-fminimizer+: Private ordinary functions
%var-accessor-+r250+: Private ordinary functions
%var-accessor-+ran0+: Private ordinary functions
%var-accessor-+ran1+: Private ordinary functions
%var-accessor-+ran2+: Private ordinary functions
%var-accessor-+ran3+: Private ordinary functions
%var-accessor-+rand+: Private ordinary functions
%var-accessor-+rand48+: Private ordinary functions
%var-accessor-+random128_bsd+: Private ordinary functions
%var-accessor-+random128_glibc2+: Private ordinary functions
%var-accessor-+random128_libc5+: Private ordinary functions
%var-accessor-+random256_bsd+: Private ordinary functions
%var-accessor-+random256_glibc2+: Private ordinary functions
%var-accessor-+random256_libc5+: Private ordinary functions
%var-accessor-+random32_bsd+: Private ordinary functions
%var-accessor-+random32_glibc2+: Private ordinary functions
%var-accessor-+random32_libc5+: Private ordinary functions
%var-accessor-+random64_bsd+: Private ordinary functions
%var-accessor-+random64_glibc2+: Private ordinary functions
%var-accessor-+random64_libc5+: Private ordinary functions
%var-accessor-+random8_bsd+: Private ordinary functions
%var-accessor-+random8_glibc2+: Private ordinary functions
%var-accessor-+random8_libc5+: Private ordinary functions
%var-accessor-+random_bsd+: Private ordinary functions
%var-accessor-+random_glibc2+: Private ordinary functions
%var-accessor-+random_libc5+: Private ordinary functions
%var-accessor-+randu+: Private ordinary functions
%var-accessor-+ranf+: Private ordinary functions
%var-accessor-+ranlux+: Private ordinary functions
%var-accessor-+ranlux389+: Private ordinary functions
%var-accessor-+ranlxd1+: Private ordinary functions
%var-accessor-+ranlxd2+: Private ordinary functions
%var-accessor-+ranlxs0+: Private ordinary functions
%var-accessor-+ranlxs1+: Private ordinary functions
%var-accessor-+ranlxs2+: Private ordinary functions
%var-accessor-+ranmar+: Private ordinary functions
%var-accessor-+reverse-halton+: Private ordinary functions
%var-accessor-+secant-fdfsolver+: Private ordinary functions
%var-accessor-+simplex-nelder-mead+: Private ordinary functions
%var-accessor-+simplex-nelder-mead-on2+: Private ordinary functions
%var-accessor-+simplex-nelder-mead-random+: Private ordinary functions
%var-accessor-+slatec+: Private ordinary functions
%var-accessor-+sobol+: Private ordinary functions
%var-accessor-+steffenson-fdfsolver+: Private ordinary functions
%var-accessor-+step-bsimp+: Private ordinary functions
%var-accessor-+step-gear1+: Private ordinary functions
%var-accessor-+step-gear2+: Private ordinary functions
%var-accessor-+step-rk2+: Private ordinary functions
%var-accessor-+step-rk2imp+: Private ordinary functions
%var-accessor-+step-rk4+: Private ordinary functions
%var-accessor-+step-rk4imp+: Private ordinary functions
%var-accessor-+step-rk8pd+: Private ordinary functions
%var-accessor-+step-rkck+: Private ordinary functions
%var-accessor-+step-rkf45+: Private ordinary functions
%var-accessor-+taus+: Private ordinary functions
%var-accessor-+taus113+: Private ordinary functions
%var-accessor-+taus2+: Private ordinary functions
%var-accessor-+transputer+: Private ordinary functions
%var-accessor-+tt800+: Private ordinary functions
%var-accessor-+uni+: Private ordinary functions
%var-accessor-+uni32+: Private ordinary functions
%var-accessor-+vax+: Private ordinary functions
%var-accessor-+vector-bfgs+: Private ordinary functions
%var-accessor-+vector-bfgs2+: Private ordinary functions
%var-accessor-+waterman14+: Private ordinary functions
%var-accessor-+zuf+: Private ordinary functions

(
(setf %var-accessor-*gsl-version*): Private ordinary functions
(setf %var-accessor-+akima-interpolation+): Private ordinary functions
(setf %var-accessor-+bisection-fsolver+): Private ordinary functions
(setf %var-accessor-+borosh13+): Private ordinary functions
(setf %var-accessor-+brent-fminimizer+): Private ordinary functions
(setf %var-accessor-+brent-fsolver+): Private ordinary functions
(setf %var-accessor-+broyden+): Private ordinary functions
(setf %var-accessor-+bspline-wavelet+): Private ordinary functions
(setf %var-accessor-+bspline-wavelet-centered+): Private ordinary functions
(setf %var-accessor-+cmrg+): Private ordinary functions
(setf %var-accessor-+conjugate-fletcher-reeves+): Private ordinary functions
(setf %var-accessor-+conjugate-polak-ribiere+): Private ordinary functions
(setf %var-accessor-+coveyou+): Private ordinary functions
(setf %var-accessor-+cubic-spline-interpolation+): Private ordinary functions
(setf %var-accessor-+daubechies-wavelet+): Private ordinary functions
(setf %var-accessor-+daubechies-wavelet-centered+): Private ordinary functions
(setf %var-accessor-+default-seed+): Private ordinary functions
(setf %var-accessor-+default-type+): Private ordinary functions
(setf %var-accessor-+discrete-newton+): Private ordinary functions
(setf %var-accessor-+false-position-fsolver+): Private ordinary functions
(setf %var-accessor-+fishman18+): Private ordinary functions
(setf %var-accessor-+fishman20+): Private ordinary functions
(setf %var-accessor-+fishman2x+): Private ordinary functions
(setf %var-accessor-+gfsr4+): Private ordinary functions
(setf %var-accessor-+gnewton-mfdfsolver+): Private ordinary functions
(setf %var-accessor-+golden-section-fminimizer+): Private ordinary functions
(setf %var-accessor-+haar-wavelet+): Private ordinary functions
(setf %var-accessor-+haar-wavelet-centered+): Private ordinary functions
(setf %var-accessor-+halton+): Private ordinary functions
(setf %var-accessor-+hybrid-scaled+): Private ordinary functions
(setf %var-accessor-+hybrid-unscaled+): Private ordinary functions
(setf %var-accessor-+knuthran+): Private ordinary functions
(setf %var-accessor-+knuthran2+): Private ordinary functions
(setf %var-accessor-+knuthran2002+): Private ordinary functions
(setf %var-accessor-+lecuyer21+): Private ordinary functions
(setf %var-accessor-+levenberg-marquardt+): Private ordinary functions
(setf %var-accessor-+levenberg-marquardt-unscaled+): Private ordinary functions
(setf %var-accessor-+linear-interpolation+): Private ordinary functions
(setf %var-accessor-+minstd+): Private ordinary functions
(setf %var-accessor-+mrg+): Private ordinary functions
(setf %var-accessor-+mt19937+): Private ordinary functions
(setf %var-accessor-+mt19937-1998+): Private ordinary functions
(setf %var-accessor-+mt19937-1999+): Private ordinary functions
(setf %var-accessor-+newton-fdfsolver+): Private ordinary functions
(setf %var-accessor-+newton-mfdfsolver+): Private ordinary functions
(setf %var-accessor-+niederreiter2+): Private ordinary functions
(setf %var-accessor-+periodic-akima-interpolation+): Private ordinary functions
(setf %var-accessor-+periodic-cubic-spline-interpolation+): Private ordinary functions
(setf %var-accessor-+polynomial-interpolation+): Private ordinary functions
(setf %var-accessor-+powells-hybrid+): Private ordinary functions
(setf %var-accessor-+powells-hybrid-unscaled+): Private ordinary functions
(setf %var-accessor-+quad-golden-fminimizer+): Private ordinary functions
(setf %var-accessor-+r250+): Private ordinary functions
(setf %var-accessor-+ran0+): Private ordinary functions
(setf %var-accessor-+ran1+): Private ordinary functions
(setf %var-accessor-+ran2+): Private ordinary functions
(setf %var-accessor-+ran3+): Private ordinary functions
(setf %var-accessor-+rand+): Private ordinary functions
(setf %var-accessor-+rand48+): Private ordinary functions
(setf %var-accessor-+random128_bsd+): Private ordinary functions
(setf %var-accessor-+random128_glibc2+): Private ordinary functions
(setf %var-accessor-+random128_libc5+): Private ordinary functions
(setf %var-accessor-+random256_bsd+): Private ordinary functions
(setf %var-accessor-+random256_glibc2+): Private ordinary functions
(setf %var-accessor-+random256_libc5+): Private ordinary functions
(setf %var-accessor-+random32_bsd+): Private ordinary functions
(setf %var-accessor-+random32_glibc2+): Private ordinary functions
(setf %var-accessor-+random32_libc5+): Private ordinary functions
(setf %var-accessor-+random64_bsd+): Private ordinary functions
(setf %var-accessor-+random64_glibc2+): Private ordinary functions
(setf %var-accessor-+random64_libc5+): Private ordinary functions
(setf %var-accessor-+random8_bsd+): Private ordinary functions
(setf %var-accessor-+random8_glibc2+): Private ordinary functions
(setf %var-accessor-+random8_libc5+): Private ordinary functions
(setf %var-accessor-+random_bsd+): Private ordinary functions
(setf %var-accessor-+random_glibc2+): Private ordinary functions
(setf %var-accessor-+random_libc5+): Private ordinary functions
(setf %var-accessor-+randu+): Private ordinary functions
(setf %var-accessor-+ranf+): Private ordinary functions
(setf %var-accessor-+ranlux+): Private ordinary functions
(setf %var-accessor-+ranlux389+): Private ordinary functions
(setf %var-accessor-+ranlxd1+): Private ordinary functions
(setf %var-accessor-+ranlxd2+): Private ordinary functions
(setf %var-accessor-+ranlxs0+): Private ordinary functions
(setf %var-accessor-+ranlxs1+): Private ordinary functions
(setf %var-accessor-+ranlxs2+): Private ordinary functions
(setf %var-accessor-+ranmar+): Private ordinary functions
(setf %var-accessor-+reverse-halton+): Private ordinary functions
(setf %var-accessor-+secant-fdfsolver+): Private ordinary functions
(setf %var-accessor-+simplex-nelder-mead+): Private ordinary functions
(setf %var-accessor-+simplex-nelder-mead-on2+): Private ordinary functions
(setf %var-accessor-+simplex-nelder-mead-random+): Private ordinary functions
(setf %var-accessor-+slatec+): Private ordinary functions
(setf %var-accessor-+sobol+): Private ordinary functions
(setf %var-accessor-+steffenson-fdfsolver+): Private ordinary functions
(setf %var-accessor-+step-bsimp+): Private ordinary functions
(setf %var-accessor-+step-gear1+): Private ordinary functions
(setf %var-accessor-+step-gear2+): Private ordinary functions
(setf %var-accessor-+step-rk2+): Private ordinary functions
(setf %var-accessor-+step-rk2imp+): Private ordinary functions
(setf %var-accessor-+step-rk4+): Private ordinary functions
(setf %var-accessor-+step-rk4imp+): Private ordinary functions
(setf %var-accessor-+step-rk8pd+): Private ordinary functions
(setf %var-accessor-+step-rkck+): Private ordinary functions
(setf %var-accessor-+step-rkf45+): Private ordinary functions
(setf %var-accessor-+taus+): Private ordinary functions
(setf %var-accessor-+taus113+): Private ordinary functions
(setf %var-accessor-+taus2+): Private ordinary functions
(setf %var-accessor-+transputer+): Private ordinary functions
(setf %var-accessor-+tt800+): Private ordinary functions
(setf %var-accessor-+uni+): Private ordinary functions
(setf %var-accessor-+uni32+): Private ordinary functions
(setf %var-accessor-+vax+): Private ordinary functions
(setf %var-accessor-+vector-bfgs+): Private ordinary functions
(setf %var-accessor-+vector-bfgs2+): Private ordinary functions
(setf %var-accessor-+waterman14+): Private ordinary functions
(setf %var-accessor-+zuf+): Private ordinary functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf column): Public generic functions
(setf exponent-fit-data-n): Private ordinary functions
(setf exponent-fit-data-sigma): Private ordinary functions
(setf exponent-fit-data-y): Private ordinary functions
(setf maref): Public setf expanders
(setf parameter): Public generic functions
(setf parameter): Public generic functions
(setf parameter): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions
(setf row): Public generic functions

1
1/gamma: Public ordinary functions

A
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-deviation: Public generic functions
absolute-sum: Public generic functions
absolute-sum: Public generic functions
absolute-sum: Public generic functions
absolute-sum: Public generic functions
absolute-sum: Public generic functions
accelerate: Public ordinary functions
accelerate-truncated: Public ordinary functions
accelerated-interpolation-search: Public ordinary functions
acceleration-example: Private ordinary functions
access-value-int: Private ordinary functions
actual-array-c-type: Private ordinary functions
actual-array-class: Private ordinary functions
actual-class-arglist: Private ordinary functions
actual-element-c-type: Private ordinary functions
actual-gsl-function-name: Private ordinary functions
adjust-stepsize: Public ordinary functions
after-llk: Private ordinary functions
airy-ai: Public ordinary functions
airy-ai-deriv: Public ordinary functions
airy-ai-deriv-scaled: Public ordinary functions
airy-ai-scaled: Public ordinary functions
airy-bi: Public ordinary functions
airy-bi-deriv: Public ordinary functions
airy-bi-deriv-scaled: Public ordinary functions
airy-bi-scaled: Public ordinary functions
airy-zero-ai: Public ordinary functions
airy-zero-ai-deriv: Public ordinary functions
airy-zero-bi: Public ordinary functions
airy-zero-bi-deriv: Public ordinary functions
all-fft-test-forms: Private macros
all-io: Private ordinary functions
all-random-number-generators: Public ordinary functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
alloc-from-block: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
allocate: Private generic functions
apply-evolution: Public ordinary functions
apply-hankel: Public ordinary functions
apply-step: Public ordinary functions
aref: Public standalone methods
aref: Public standalone methods
aref: Public standalone methods
arglist-plain-and-categories: Private ordinary functions
argument: Public ordinary functions
array-default: Private ordinary functions
array-element-refs: Private ordinary functions
assert-neginf: Private macros
assert-posinf: Private macros
assert-sf-scale: Private macros
assert-to-tolerance: Private macros
atanint: Public ordinary functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
autocorrelation: Public generic functions
axpy: Public generic functions
axpy: Public generic functions
axpy: Public generic functions
axpy: Public generic functions
axpy: Public generic functions

B
backward-derivative: Public ordinary functions
backward-discrete-fourier-transform: Public generic functions
backward-discrete-fourier-transform: Public generic functions
backward-discrete-fourier-transform: Public generic functions
backward-fourier-transform: Public ordinary functions
backward-fourier-transform-dif-radix2: Private generic functions
backward-fourier-transform-dif-radix2: Private generic functions
backward-fourier-transform-dif-radix2: Private generic functions
backward-fourier-transform-halfcomplex-nonradix2: Private generic functions
backward-fourier-transform-halfcomplex-nonradix2: Private generic functions
backward-fourier-transform-halfcomplex-nonradix2: Private generic functions
backward-fourier-transform-halfcomplex-radix2: Private generic functions
backward-fourier-transform-halfcomplex-radix2: Private generic functions
backward-fourier-transform-halfcomplex-radix2: Private generic functions
backward-fourier-transform-nonradix2: Private generic functions
backward-fourier-transform-nonradix2: Private generic functions
backward-fourier-transform-nonradix2: Private generic functions
backward-fourier-transform-radix2: Private generic functions
backward-fourier-transform-radix2: Private generic functions
backward-fourier-transform-radix2: Private generic functions
bernoulli-pdf: Public ordinary functions
bessel-lnknu: Public ordinary functions
bessel-zero-j0: Public ordinary functions
bessel-zero-j1: Public ordinary functions
bessel-zero-jnu: Public ordinary functions
beta: Public ordinary functions
beta-p: Public ordinary functions
beta-pdf: Public ordinary functions
beta-pinv: Public ordinary functions
beta-q: Public ordinary functions
beta-qinv: Public ordinary functions
bidiagonal-decomposition: Public ordinary functions
bidiagonal-unpack: Public ordinary functions
bidiagonal-unpack-diagonal-superdiagonal: Public ordinary functions
bidiagonal-unpack2: Public ordinary functions
bin-samples: Private ordinary functions
binomial: Public ordinary functions
binomial-p: Public ordinary functions
binomial-pdf: Public ordinary functions
binomial-q: Public ordinary functions
bivariate-gaussian-pdf: Public ordinary functions
blas-copy: Public generic functions
blas-copy: Public generic functions
blas-copy: Public generic functions
blas-copy: Public generic functions
blas-copy: Public generic functions
blas-swap: Public generic functions
blas-swap: Public generic functions
blas-swap: Public generic functions
blas-swap: Public generic functions
blas-swap: Public generic functions
body-expand: Private ordinary functions
body-no-optional-arg: Private ordinary functions
body-optional-arg: Private ordinary functions
bookdata-ntuple: Public ordinary functions
breakpoint: Public ordinary functions
bspline-example: Private ordinary functions

C
callback-args: Private ordinary functions
callback-remove-arg: Private ordinary functions
callback-replace-arg: Private ordinary functions
callback-set-dynamic: Private ordinary functions
callback-set-mvb: Private ordinary functions
callback-set-slots: Private ordinary functions
callback-struct: Private generic functions
callback-struct: Private generic functions
callback-symbol-set: Private ordinary functions
canonical-cycles: Public ordinary functions
canonical-to-linear: Public ordinary functions
category-for-argument: Private ordinary functions
cauchy-p: Public ordinary functions
cauchy-pdf: Public ordinary functions
cauchy-pinv: Public ordinary functions
cauchy-q: Public ordinary functions
cauchy-qinv: Public ordinary functions
cbd-dimensions: Private ordinary functions
cbd-functions: Private ordinary functions
cbinfo: Private generic functions
cbinfo: Private generic functions
cdot: Public generic functions
cdot: Public generic functions
cdot: Public generic functions
central-derivative: Public ordinary functions
chebyshev-point-example: Private ordinary functions
chebyshev-step: Private ordinary functions
chebyshev-table-example: Private ordinary functions
check-gsl-status: Private ordinary functions
check-null-pointer: Private ordinary functions
chi: Public ordinary functions
chi-squared-p: Public ordinary functions
chi-squared-pdf: Public ordinary functions
chi-squared-pinv: Public ordinary functions
chi-squared-q: Public ordinary functions
chi-squared-qinv: Public ordinary functions
cholesky-decomposition: Public generic functions
cholesky-decomposition: Public generic functions
cholesky-decomposition: Public generic functions
cholesky-invert: Public ordinary functions
cholesky-solve: Public generic functions
cholesky-solve: Public generic functions
cholesky-solve: Public generic functions
choose: Public ordinary functions
ci: Public ordinary functions
cl-argument-types: Private ordinary functions
cl-convert-form: Private ordinary functions
cl-gsl: Private ordinary functions
cl-symbols: Private ordinary functions
clausen: Public ordinary functions
close-ntuple: Public ordinary functions
coefficients: Public ordinary functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
column: Public generic functions
comb-copy: Private ordinary functions
combination-next: Public ordinary functions
combination-previous: Public ordinary functions
combination-range: Public ordinary functions
complementary-incomplete-gamma: Public ordinary functions
complete-definition: Private ordinary functions
complex-with-error: Private ordinary functions
conjugate-rank-1-update: Public generic functions
conjugate-rank-1-update: Public generic functions
conjugate-rank-1-update: Public generic functions
constant-matrix: Private ordinary functions
control-alloc: Public ordinary functions
copy: Public standalone methods
copy: Public standalone methods
copy: Public standalone methods
copy: Public standalone methods
copy: Public standalone methods
copy: Public standalone methods
copy-exponent-fit-data: Private ordinary functions
copy-sa-state: Private ordinary functions
copy-with-stride: Private ordinary functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
correlation: Public generic functions
cos-err: Public ordinary functions
coulomb-cl: Public ordinary functions
coulomb-cl-array: Public ordinary functions
coulomb-wave-f-array: Public ordinary functions
coulomb-wave-fg: Public ordinary functions
coulomb-wave-fg-array: Public ordinary functions
coulomb-wave-fgp-array: Public ordinary functions
coulomb-wave-sphf-array: Public ordinary functions
coupling-3j: Public ordinary functions
coupling-6j: Public ordinary functions
coupling-9j: Public ordinary functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
covariance: Public generic functions
create-complex-matrix: Private ordinary functions
create-general-matrix: Private ordinary functions
create-hilbert-matrix: Private ordinary functions
create-matrix: Private ordinary functions
create-moler-matrix: Private ordinary functions
create-ntuple: Public ordinary functions
create-rhs-vector: Private ordinary functions
create-row-matrix: Private ordinary functions
create-singular-matrix: Private ordinary functions
create-vandermonde-matrix: Private ordinary functions
creturn-st: Private ordinary functions
cx-add: Public ordinary functions
cx-add-imag: Public ordinary functions
cx-add-real: Public ordinary functions
cx-arccos: Public ordinary functions
cx-arccos-real: Public ordinary functions
cx-arccosh: Public ordinary functions
cx-arccosh-real: Public ordinary functions
cx-arccot: Public ordinary functions
cx-arccoth: Public ordinary functions
cx-arccsc: Public ordinary functions
cx-arccsc-real: Public ordinary functions
cx-arccsch: Public ordinary functions
cx-arcsec: Public ordinary functions
cx-arcsec-real: Public ordinary functions
cx-arcsech: Public ordinary functions
cx-arcsin: Public ordinary functions
cx-arcsin-real: Public ordinary functions
cx-arcsinh: Public ordinary functions
cx-arctan: Public ordinary functions
cx-arctanh: Public ordinary functions
cx-arctanh-real: Public ordinary functions
cx-conjugate: Public ordinary functions
cx-cos: Public ordinary functions
cx-cosh: Public ordinary functions
cx-cot: Public ordinary functions
cx-coth: Public ordinary functions
cx-csc: Public ordinary functions
cx-csch: Public ordinary functions
cx-div: Public ordinary functions
cx-div-imag: Public ordinary functions
cx-div-real: Public ordinary functions
cx-exp: Public ordinary functions
cx-expt: Public ordinary functions
cx-expt-real: Public ordinary functions
cx-inverse: Public ordinary functions
cx-log: Public ordinary functions
cx-log10: Public ordinary functions
cx-logb: Public ordinary functions
cx-mul: Public ordinary functions
cx-mul-imag: Public ordinary functions
cx-mul-real: Public ordinary functions
cx-negative: Public ordinary functions
cx-sec: Public ordinary functions
cx-sech: Public ordinary functions
cx-sin: Public ordinary functions
cx-sinh: Public ordinary functions
cx-sqrt: Public ordinary functions
cx-sqrt-real: Public ordinary functions
cx-sub: Public ordinary functions
cx-sub-imag: Public ordinary functions
cx-sub-real: Public ordinary functions
cx-tan: Public ordinary functions
cx-tanh: Public ordinary functions
cylindrical-bessel-i: Public generic functions
cylindrical-bessel-i: Public generic functions
cylindrical-bessel-i: Public generic functions
cylindrical-bessel-i-scaled: Public generic functions
cylindrical-bessel-i-scaled: Public generic functions
cylindrical-bessel-i-scaled: Public generic functions
cylindrical-bessel-i0: Public ordinary functions
cylindrical-bessel-i0-scaled: Public ordinary functions
cylindrical-bessel-i1: Public ordinary functions
cylindrical-bessel-i1-scaled: Public ordinary functions
cylindrical-bessel-in-array: Public ordinary functions
cylindrical-bessel-in-scaled-array: Public ordinary functions
cylindrical-bessel-j: Public generic functions
cylindrical-bessel-j: Public generic functions
cylindrical-bessel-j: Public generic functions
cylindrical-bessel-j-array-order: Public ordinary functions
cylindrical-bessel-j-array-x: Public ordinary functions
cylindrical-bessel-j0: Public ordinary functions
cylindrical-bessel-j1: Public ordinary functions
cylindrical-bessel-k: Public generic functions
cylindrical-bessel-k: Public generic functions
cylindrical-bessel-k: Public generic functions
cylindrical-bessel-k-scaled: Public generic functions
cylindrical-bessel-k-scaled: Public generic functions
cylindrical-bessel-k-scaled: Public generic functions
cylindrical-bessel-k0: Public ordinary functions
cylindrical-bessel-k0-scaled: Public ordinary functions
cylindrical-bessel-k1: Public ordinary functions
cylindrical-bessel-k1-scaled: Public ordinary functions
cylindrical-bessel-kn-array: Public ordinary functions
cylindrical-bessel-kn-scaled-array: Public ordinary functions
cylindrical-bessel-y: Public generic functions
cylindrical-bessel-y: Public generic functions
cylindrical-bessel-y: Public generic functions
cylindrical-bessel-y0: Public ordinary functions
cylindrical-bessel-y1: Public ordinary functions
cylindrical-bessel-yn-array: Public ordinary functions

D
dawson: Public ordinary functions
debye-1: Public ordinary functions
debye-2: Public ordinary functions
debye-3: Public ordinary functions
debye-4: Public ordinary functions
declaration-form: Private ordinary functions
decode-ieee754: Private ordinary functions
def-ci-subclass: Private macros
def-ci-subclass-1d: Private macros
def-rng-type: Private macros
default-covariance: Private ordinary functions
default-lls-workspace: Private ordinary functions
defcomparison: Private macros
defgeneric-method-p: Private ordinary functions
define-gsl-condition: Private macros
defmcallback: Private macros
defmfun: Private macros
defmfun-return: Private ordinary functions
defmobject: Private macros
defmpar: Private macros
delete-test-definition: Private ordinary functions
deriv-f1-d: Private ordinary functions
deriv-f2: Private ordinary functions
deriv-f2-d: Private ordinary functions
deriv-f3: Private ordinary functions
deriv-f3-d: Private ordinary functions
deriv-f4: Private ordinary functions
deriv-f4-d: Private ordinary functions
deriv-f5: Private ordinary functions
deriv-f5-d: Private ordinary functions
deriv-f6-d: Private ordinary functions
derivative-chebyshev: Public ordinary functions
dilogarithm: Public generic functions
dilogarithm: Public generic functions
dilogarithm: Public generic functions
dimension-names: Private generic functions
dimension-names: Private generic functions
dimensions: Public standalone methods
dimensions: Public standalone methods
dimensions: Public standalone methods
dimensions: Public standalone methods
dirichlet-log-pdf: Public ordinary functions
dirichlet-pdf: Public ordinary functions
discrete-fourier-transform: Public generic functions
discrete-fourier-transform: Public generic functions
discrete-fourier-transform: Public generic functions
discrete-pdf: Public ordinary functions
distribution-bin-integral: Private ordinary functions
divided-difference: Public ordinary functions
double-factorial: Public ordinary functions
double-float-unequal: Public ordinary functions

E
eigenvalue-eigenvectors-example: Private ordinary functions
eigenvalues: Public generic functions
eigenvalues: Public generic functions
eigenvalues: Public generic functions
eigenvalues-eigenvectors: Public generic functions
eigenvalues-eigenvectors: Public generic functions
eigenvalues-eigenvectors: Public generic functions
eigenvalues-eigenvectors-gen: Public ordinary functions
eigenvalues-eigenvectors-gensymm: Public generic functions
eigenvalues-eigenvectors-gensymm: Public generic functions
eigenvalues-eigenvectors-gensymm: Public generic functions
eigenvalues-eigenvectors-nonsymm: Public ordinary functions
eigenvalues-gen: Public ordinary functions
eigenvalues-gensymm: Public generic functions
eigenvalues-gensymm: Public generic functions
eigenvalues-gensymm: Public generic functions
eigenvalues-nonsymm: Public ordinary functions
element-type-select: Private ordinary functions
elliptic-integral-d: Public ordinary functions
elliptic-integral-e: Public ordinary functions
elliptic-integral-e-complete: Public ordinary functions
elliptic-integral-f: Public ordinary functions
elliptic-integral-k-complete: Public ordinary functions
elliptic-integral-p: Public ordinary functions
elliptic-integral-rc: Public ordinary functions
elliptic-integral-rd: Public ordinary functions
elliptic-integral-rf: Public ordinary functions
elliptic-integral-rj: Public ordinary functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt*: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt+: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt-: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
elt/: Public generic functions
eql-specializer: Private ordinary functions
equal-bins-p: Public generic functions
equal-bins-p: Public generic functions
equal-bins-p: Public generic functions
erf: Public ordinary functions
erf-q: Public ordinary functions
erf-z: Public ordinary functions
erfc: Public ordinary functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-number: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
error-text: Private generic functions
establish-handler: Private ordinary functions
eta: Public ordinary functions
euclidean-norm: Public generic functions
euclidean-norm: Public generic functions
euclidean-norm: Public generic functions
euclidean-norm: Public generic functions
euclidean-norm: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate: Public generic functions
evaluate-chebyshev-error: Public ordinary functions
evaluate-derivative: Public generic functions
evaluate-derivative: Public generic functions
evaluate-derivative: Public generic functions
evaluate-integral: Public generic functions
evaluate-integral: Public generic functions
evaluate-integral: Public generic functions
evaluate-integral-example: Private ordinary functions
evaluate-second-derivative: Public generic functions
evaluate-second-derivative: Public generic functions
evaluate-second-derivative: Public generic functions
evaluate-with-derivatives: Public ordinary functions
examples: Public ordinary functions
exp-1: Public ordinary functions
exp-err: Public ordinary functions
exp-err-scaled: Public ordinary functions
exp-mult: Public ordinary functions
exp-mult-err: Public ordinary functions
exp-mult-err-scaled: Public ordinary functions
exp-mult-scaled: Public ordinary functions
exp-scaled: Public ordinary functions
expand-defmfun-arrays: Private ordinary functions
expand-defmfun-defmethods: Private ordinary functions
expand-defmfun-generic: Private ordinary functions
expand-defmfun-method: Private ordinary functions
expand-defmfun-optional: Private ordinary functions
expand-defmfun-wrap: Private ordinary functions
explanation: Private generic functions
explanation: Private generic functions
expm1: Public ordinary functions
exponent-fit-data-n: Private ordinary functions
exponent-fit-data-p: Private ordinary functions
exponent-fit-data-sigma: Private ordinary functions
exponent-fit-data-y: Private ordinary functions
exponential-integral-3: Public ordinary functions
exponential-integral-e1: Public ordinary functions
exponential-integral-e2: Public ordinary functions
exponential-integral-ei: Public ordinary functions
exponential-integral-en: Public ordinary functions
exponential-p: Public ordinary functions
exponential-pdf: Public ordinary functions
exponential-pinv: Public ordinary functions
exponential-power-p: Public ordinary functions
exponential-power-pdf: Public ordinary functions
exponential-power-q: Public ordinary functions
exponential-q: Public ordinary functions
exponential-qinv: Public ordinary functions
exponential-residual: Private ordinary functions
exponential-residual-derivative: Private ordinary functions
exponential-residual-fdf: Private ordinary functions
exprel: Public ordinary functions
exprel-2: Public ordinary functions
exprel-n: Public ordinary functions

F
factorial: Public ordinary functions
faify-form: Private ordinary functions
fdist-p: Public ordinary functions
fdist-pdf: Public ordinary functions
fdist-pinv: Public ordinary functions
fdist-q: Public ordinary functions
fdist-qinv: Public ordinary functions
fermi-dirac-0: Public ordinary functions
fermi-dirac-1: Public ordinary functions
fermi-dirac-1/2: Public ordinary functions
fermi-dirac-2: Public ordinary functions
fermi-dirac-3/2: Public ordinary functions
fermi-dirac-inc-0: Public ordinary functions
fermi-dirac-integral: Public ordinary functions
fermi-dirac-m1: Public ordinary functions
fermi-dirac-m1/2: Public ordinary functions
fft-complex-off-stride-check: Private ordinary functions
fft-complex-result-check: Private macros
fft-frequency-split: Private ordinary functions
fft-frequency-step: Private ordinary functions
fft-frequency-vector: Public ordinary functions
fft-half-complex-radix2-unpack: Private generic functions
fft-half-complex-radix2-unpack: Private generic functions
fft-half-complex-radix2-unpack: Private generic functions
fft-half-complex-unpack: Private generic functions
fft-half-complex-unpack: Private generic functions
fft-half-complex-unpack: Private generic functions
fft-highest-frequency: Private ordinary functions
fft-inverse-shift: Public ordinary functions
fft-pulse-test: Private ordinary functions
fft-real-result-check: Private macros
fft-real-unpack: Private generic functions
fft-real-unpack: Private generic functions
fft-real-unpack: Private generic functions
fft-shift: Public ordinary functions
fft-test-forms: Private ordinary functions
finitep: Public ordinary functions
fit-gradient: Public ordinary functions
fit-test-delta: Public ordinary functions
fit-test-gradient: Public ordinary functions
flat-p: Public ordinary functions
flat-pdf: Public ordinary functions
flat-pinv: Public ordinary functions
flat-q: Public ordinary functions
flat-qinv: Public ordinary functions
float-as-integer: Public ordinary functions
fminimizer-f-lower: Public ordinary functions
fminimizer-f-upper: Public ordinary functions
fminimizer-x-lower: Public ordinary functions
fminimizer-x-upper: Public ordinary functions
foreign-pointer-method: Private macros
format-ieee754-bits: Public ordinary functions
forward-backward: Private ordinary functions
forward-derivative: Public ordinary functions
forward-discrete-fourier-transform: Public generic functions
forward-discrete-fourier-transform: Public generic functions
forward-discrete-fourier-transform: Public generic functions
forward-fourier-transform: Public ordinary functions
forward-fourier-transform-dif-radix2: Private generic functions
forward-fourier-transform-dif-radix2: Private generic functions
forward-fourier-transform-dif-radix2: Private generic functions
forward-fourier-transform-halfcomplex-nonradix2: Private generic functions
forward-fourier-transform-halfcomplex-nonradix2: Private generic functions
forward-fourier-transform-halfcomplex-nonradix2: Private generic functions
forward-fourier-transform-halfcomplex-radix2: Private generic functions
forward-fourier-transform-halfcomplex-radix2: Private generic functions
forward-fourier-transform-halfcomplex-radix2: Private generic functions
forward-fourier-transform-nonradix2: Private generic functions
forward-fourier-transform-nonradix2: Private generic functions
forward-fourier-transform-nonradix2: Private generic functions
forward-fourier-transform-nonradix2: Private generic functions
forward-fourier-transform-nonradix2: Private generic functions
forward-fourier-transform-radix2: Private generic functions
forward-fourier-transform-radix2: Private generic functions
forward-fourier-transform-radix2: Private generic functions
forward-fourier-transform-radix2: Private generic functions
forward-fourier-transform-radix2: Private generic functions
fourier-transform: Public ordinary functions
fourier-transform-dif-radix2: Private generic functions
fourier-transform-dif-radix2: Private generic functions
fourier-transform-dif-radix2: Private generic functions
fourier-transform-radix2: Private generic functions
fourier-transform-radix2: Private generic functions
fourier-transform-radix2: Private generic functions
fsolver-lower: Public ordinary functions
fsolver-upper: Public ordinary functions
funcallables: Private generic functions
funcallables: Private generic functions
Function, %var-accessor-*gsl-version*: Private ordinary functions
Function, %var-accessor-+akima-interpolation+: Private ordinary functions
Function, %var-accessor-+bisection-fsolver+: Private ordinary functions
Function, %var-accessor-+borosh13+: Private ordinary functions
Function, %var-accessor-+brent-fminimizer+: Private ordinary functions
Function, %var-accessor-+brent-fsolver+: Private ordinary functions
Function, %var-accessor-+broyden+: Private ordinary functions
Function, %var-accessor-+bspline-wavelet+: Private ordinary functions
Function, %var-accessor-+bspline-wavelet-centered+: Private ordinary functions
Function, %var-accessor-+cmrg+: Private ordinary functions
Function, %var-accessor-+conjugate-fletcher-reeves+: Private ordinary functions
Function, %var-accessor-+conjugate-polak-ribiere+: Private ordinary functions
Function, %var-accessor-+coveyou+: Private ordinary functions
Function, %var-accessor-+cubic-spline-interpolation+: Private ordinary functions
Function, %var-accessor-+daubechies-wavelet+: Private ordinary functions
Function, %var-accessor-+daubechies-wavelet-centered+: Private ordinary functions
Function, %var-accessor-+default-seed+: Private ordinary functions
Function, %var-accessor-+default-type+: Private ordinary functions
Function, %var-accessor-+discrete-newton+: Private ordinary functions
Function, %var-accessor-+false-position-fsolver+: Private ordinary functions
Function, %var-accessor-+fishman18+: Private ordinary functions
Function, %var-accessor-+fishman20+: Private ordinary functions
Function, %var-accessor-+fishman2x+: Private ordinary functions
Function, %var-accessor-+gfsr4+: Private ordinary functions
Function, %var-accessor-+gnewton-mfdfsolver+: Private ordinary functions
Function, %var-accessor-+golden-section-fminimizer+: Private ordinary functions
Function, %var-accessor-+haar-wavelet+: Private ordinary functions
Function, %var-accessor-+haar-wavelet-centered+: Private ordinary functions
Function, %var-accessor-+halton+: Private ordinary functions
Function, %var-accessor-+hybrid-scaled+: Private ordinary functions
Function, %var-accessor-+hybrid-unscaled+: Private ordinary functions
Function, %var-accessor-+knuthran+: Private ordinary functions
Function, %var-accessor-+knuthran2+: Private ordinary functions
Function, %var-accessor-+knuthran2002+: Private ordinary functions
Function, %var-accessor-+lecuyer21+: Private ordinary functions
Function, %var-accessor-+levenberg-marquardt+: Private ordinary functions
Function, %var-accessor-+levenberg-marquardt-unscaled+: Private ordinary functions
Function, %var-accessor-+linear-interpolation+: Private ordinary functions
Function, %var-accessor-+minstd+: Private ordinary functions
Function, %var-accessor-+mrg+: Private ordinary functions
Function, %var-accessor-+mt19937+: Private ordinary functions
Function, %var-accessor-+mt19937-1998+: Private ordinary functions
Function, %var-accessor-+mt19937-1999+: Private ordinary functions
Function, %var-accessor-+newton-fdfsolver+: Private ordinary functions
Function, %var-accessor-+newton-mfdfsolver+: Private ordinary functions
Function, %var-accessor-+niederreiter2+: Private ordinary functions
Function, %var-accessor-+periodic-akima-interpolation+: Private ordinary functions
Function, %var-accessor-+periodic-cubic-spline-interpolation+: Private ordinary functions
Function, %var-accessor-+polynomial-interpolation+: Private ordinary functions
Function, %var-accessor-+powells-hybrid+: Private ordinary functions
Function, %var-accessor-+powells-hybrid-unscaled+: Private ordinary functions
Function, %var-accessor-+quad-golden-fminimizer+: Private ordinary functions
Function, %var-accessor-+r250+: Private ordinary functions
Function, %var-accessor-+ran0+: Private ordinary functions
Function, %var-accessor-+ran1+: Private ordinary functions
Function, %var-accessor-+ran2+: Private ordinary functions
Function, %var-accessor-+ran3+: Private ordinary functions
Function, %var-accessor-+rand+: Private ordinary functions
Function, %var-accessor-+rand48+: Private ordinary functions
Function, %var-accessor-+random128_bsd+: Private ordinary functions
Function, %var-accessor-+random128_glibc2+: Private ordinary functions
Function, %var-accessor-+random128_libc5+: Private ordinary functions
Function, %var-accessor-+random256_bsd+: Private ordinary functions
Function, %var-accessor-+random256_glibc2+: Private ordinary functions
Function, %var-accessor-+random256_libc5+: Private ordinary functions
Function, %var-accessor-+random32_bsd+: Private ordinary functions
Function, %var-accessor-+random32_glibc2+: Private ordinary functions
Function, %var-accessor-+random32_libc5+: Private ordinary functions
Function, %var-accessor-+random64_bsd+: Private ordinary functions
Function, %var-accessor-+random64_glibc2+: Private ordinary functions
Function, %var-accessor-+random64_libc5+: Private ordinary functions
Function, %var-accessor-+random8_bsd+: Private ordinary functions
Function, %var-accessor-+random8_glibc2+: Private ordinary functions
Function, %var-accessor-+random8_libc5+: Private ordinary functions
Function, %var-accessor-+random_bsd+: Private ordinary functions
Function, %var-accessor-+random_glibc2+: Private ordinary functions
Function, %var-accessor-+random_libc5+: Private ordinary functions
Function, %var-accessor-+randu+: Private ordinary functions
Function, %var-accessor-+ranf+: Private ordinary functions
Function, %var-accessor-+ranlux+: Private ordinary functions
Function, %var-accessor-+ranlux389+: Private ordinary functions
Function, %var-accessor-+ranlxd1+: Private ordinary functions
Function, %var-accessor-+ranlxd2+: Private ordinary functions
Function, %var-accessor-+ranlxs0+: Private ordinary functions
Function, %var-accessor-+ranlxs1+: Private ordinary functions
Function, %var-accessor-+ranlxs2+: Private ordinary functions
Function, %var-accessor-+ranmar+: Private ordinary functions
Function, %var-accessor-+reverse-halton+: Private ordinary functions
Function, %var-accessor-+secant-fdfsolver+: Private ordinary functions
Function, %var-accessor-+simplex-nelder-mead+: Private ordinary functions
Function, %var-accessor-+simplex-nelder-mead-on2+: Private ordinary functions
Function, %var-accessor-+simplex-nelder-mead-random+: Private ordinary functions
Function, %var-accessor-+slatec+: Private ordinary functions
Function, %var-accessor-+sobol+: Private ordinary functions
Function, %var-accessor-+steffenson-fdfsolver+: Private ordinary functions
Function, %var-accessor-+step-bsimp+: Private ordinary functions
Function, %var-accessor-+step-gear1+: Private ordinary functions
Function, %var-accessor-+step-gear2+: Private ordinary functions
Function, %var-accessor-+step-rk2+: Private ordinary functions
Function, %var-accessor-+step-rk2imp+: Private ordinary functions
Function, %var-accessor-+step-rk4+: Private ordinary functions
Function, %var-accessor-+step-rk4imp+: Private ordinary functions
Function, %var-accessor-+step-rk8pd+: Private ordinary functions
Function, %var-accessor-+step-rkck+: Private ordinary functions
Function, %var-accessor-+step-rkf45+: Private ordinary functions
Function, %var-accessor-+taus+: Private ordinary functions
Function, %var-accessor-+taus113+: Private ordinary functions
Function, %var-accessor-+taus2+: Private ordinary functions
Function, %var-accessor-+transputer+: Private ordinary functions
Function, %var-accessor-+tt800+: Private ordinary functions
Function, %var-accessor-+uni+: Private ordinary functions
Function, %var-accessor-+uni32+: Private ordinary functions
Function, %var-accessor-+vax+: Private ordinary functions
Function, %var-accessor-+vector-bfgs+: Private ordinary functions
Function, %var-accessor-+vector-bfgs2+: Private ordinary functions
Function, %var-accessor-+waterman14+: Private ordinary functions
Function, %var-accessor-+zuf+: Private ordinary functions
Function, (setf %var-accessor-*gsl-version*): Private ordinary functions
Function, (setf %var-accessor-+akima-interpolation+): Private ordinary functions
Function, (setf %var-accessor-+bisection-fsolver+): Private ordinary functions
Function, (setf %var-accessor-+borosh13+): Private ordinary functions
Function, (setf %var-accessor-+brent-fminimizer+): Private ordinary functions
Function, (setf %var-accessor-+brent-fsolver+): Private ordinary functions
Function, (setf %var-accessor-+broyden+): Private ordinary functions
Function, (setf %var-accessor-+bspline-wavelet+): Private ordinary functions
Function, (setf %var-accessor-+bspline-wavelet-centered+): Private ordinary functions
Function, (setf %var-accessor-+cmrg+): Private ordinary functions
Function, (setf %var-accessor-+conjugate-fletcher-reeves+): Private ordinary functions
Function, (setf %var-accessor-+conjugate-polak-ribiere+): Private ordinary functions
Function, (setf %var-accessor-+coveyou+): Private ordinary functions
Function, (setf %var-accessor-+cubic-spline-interpolation+): Private ordinary functions
Function, (setf %var-accessor-+daubechies-wavelet+): Private ordinary functions
Function, (setf %var-accessor-+daubechies-wavelet-centered+): Private ordinary functions
Function, (setf %var-accessor-+default-seed+): Private ordinary functions
Function, (setf %var-accessor-+default-type+): Private ordinary functions
Function, (setf %var-accessor-+discrete-newton+): Private ordinary functions
Function, (setf %var-accessor-+false-position-fsolver+): Private ordinary functions
Function, (setf %var-accessor-+fishman18+): Private ordinary functions
Function, (setf %var-accessor-+fishman20+): Private ordinary functions
Function, (setf %var-accessor-+fishman2x+): Private ordinary functions
Function, (setf %var-accessor-+gfsr4+): Private ordinary functions
Function, (setf %var-accessor-+gnewton-mfdfsolver+): Private ordinary functions
Function, (setf %var-accessor-+golden-section-fminimizer+): Private ordinary functions
Function, (setf %var-accessor-+haar-wavelet+): Private ordinary functions
Function, (setf %var-accessor-+haar-wavelet-centered+): Private ordinary functions
Function, (setf %var-accessor-+halton+): Private ordinary functions
Function, (setf %var-accessor-+hybrid-scaled+): Private ordinary functions
Function, (setf %var-accessor-+hybrid-unscaled+): Private ordinary functions
Function, (setf %var-accessor-+knuthran+): Private ordinary functions
Function, (setf %var-accessor-+knuthran2+): Private ordinary functions
Function, (setf %var-accessor-+knuthran2002+): Private ordinary functions
Function, (setf %var-accessor-+lecuyer21+): Private ordinary functions
Function, (setf %var-accessor-+levenberg-marquardt+): Private ordinary functions
Function, (setf %var-accessor-+levenberg-marquardt-unscaled+): Private ordinary functions
Function, (setf %var-accessor-+linear-interpolation+): Private ordinary functions
Function, (setf %var-accessor-+minstd+): Private ordinary functions
Function, (setf %var-accessor-+mrg+): Private ordinary functions
Function, (setf %var-accessor-+mt19937+): Private ordinary functions
Function, (setf %var-accessor-+mt19937-1998+): Private ordinary functions
Function, (setf %var-accessor-+mt19937-1999+): Private ordinary functions
Function, (setf %var-accessor-+newton-fdfsolver+): Private ordinary functions
Function, (setf %var-accessor-+newton-mfdfsolver+): Private ordinary functions
Function, (setf %var-accessor-+niederreiter2+): Private ordinary functions
Function, (setf %var-accessor-+periodic-akima-interpolation+): Private ordinary functions
Function, (setf %var-accessor-+periodic-cubic-spline-interpolation+): Private ordinary functions
Function, (setf %var-accessor-+polynomial-interpolation+): Private ordinary functions
Function, (setf %var-accessor-+powells-hybrid+): Private ordinary functions
Function, (setf %var-accessor-+powells-hybrid-unscaled+): Private ordinary functions
Function, (setf %var-accessor-+quad-golden-fminimizer+): Private ordinary functions
Function, (setf %var-accessor-+r250+): Private ordinary functions
Function, (setf %var-accessor-+ran0+): Private ordinary functions
Function, (setf %var-accessor-+ran1+): Private ordinary functions
Function, (setf %var-accessor-+ran2+): Private ordinary functions
Function, (setf %var-accessor-+ran3+): Private ordinary functions
Function, (setf %var-accessor-+rand+): Private ordinary functions
Function, (setf %var-accessor-+rand48+): Private ordinary functions
Function, (setf %var-accessor-+random128_bsd+): Private ordinary functions
Function, (setf %var-accessor-+random128_glibc2+): Private ordinary functions
Function, (setf %var-accessor-+random128_libc5+): Private ordinary functions
Function, (setf %var-accessor-+random256_bsd+): Private ordinary functions
Function, (setf %var-accessor-+random256_glibc2+): Private ordinary functions
Function, (setf %var-accessor-+random256_libc5+): Private ordinary functions
Function, (setf %var-accessor-+random32_bsd+): Private ordinary functions
Function, (setf %var-accessor-+random32_glibc2+): Private ordinary functions
Function, (setf %var-accessor-+random32_libc5+): Private ordinary functions
Function, (setf %var-accessor-+random64_bsd+): Private ordinary functions
Function, (setf %var-accessor-+random64_glibc2+): Private ordinary functions
Function, (setf %var-accessor-+random64_libc5+): Private ordinary functions
Function, (setf %var-accessor-+random8_bsd+): Private ordinary functions
Function, (setf %var-accessor-+random8_glibc2+): Private ordinary functions
Function, (setf %var-accessor-+random8_libc5+): Private ordinary functions
Function, (setf %var-accessor-+random_bsd+): Private ordinary functions
Function, (setf %var-accessor-+random_glibc2+): Private ordinary functions
Function, (setf %var-accessor-+random_libc5+): Private ordinary functions
Function, (setf %var-accessor-+randu+): Private ordinary functions
Function, (setf %var-accessor-+ranf+): Private ordinary functions
Function, (setf %var-accessor-+ranlux+): Private ordinary functions
Function, (setf %var-accessor-+ranlux389+): Private ordinary functions
Function, (setf %var-accessor-+ranlxd1+): Private ordinary functions
Function, (setf %var-accessor-+ranlxd2+): Private ordinary functions
Function, (setf %var-accessor-+ranlxs0+): Private ordinary functions
Function, (setf %var-accessor-+ranlxs1+): Private ordinary functions
Function, (setf %var-accessor-+ranlxs2+): Private ordinary functions
Function, (setf %var-accessor-+ranmar+): Private ordinary functions
Function, (setf %var-accessor-+reverse-halton+): Private ordinary functions
Function, (setf %var-accessor-+secant-fdfsolver+): Private ordinary functions
Function, (setf %var-accessor-+simplex-nelder-mead+): Private ordinary functions
Function, (setf %var-accessor-+simplex-nelder-mead-on2+): Private ordinary functions
Function, (setf %var-accessor-+simplex-nelder-mead-random+): Private ordinary functions
Function, (setf %var-accessor-+slatec+): Private ordinary functions
Function, (setf %var-accessor-+sobol+): Private ordinary functions
Function, (setf %var-accessor-+steffenson-fdfsolver+): Private ordinary functions
Function, (setf %var-accessor-+step-bsimp+): Private ordinary functions
Function, (setf %var-accessor-+step-gear1+): Private ordinary functions
Function, (setf %var-accessor-+step-gear2+): Private ordinary functions
Function, (setf %var-accessor-+step-rk2+): Private ordinary functions
Function, (setf %var-accessor-+step-rk2imp+): Private ordinary functions
Function, (setf %var-accessor-+step-rk4+): Private ordinary functions
Function, (setf %var-accessor-+step-rk4imp+): Private ordinary functions
Function, (setf %var-accessor-+step-rk8pd+): Private ordinary functions
Function, (setf %var-accessor-+step-rkck+): Private ordinary functions
Function, (setf %var-accessor-+step-rkf45+): Private ordinary functions
Function, (setf %var-accessor-+taus+): Private ordinary functions
Function, (setf %var-accessor-+taus113+): Private ordinary functions
Function, (setf %var-accessor-+taus2+): Private ordinary functions
Function, (setf %var-accessor-+transputer+): Private ordinary functions
Function, (setf %var-accessor-+tt800+): Private ordinary functions
Function, (setf %var-accessor-+uni+): Private ordinary functions
Function, (setf %var-accessor-+uni32+): Private ordinary functions
Function, (setf %var-accessor-+vax+): Private ordinary functions
Function, (setf %var-accessor-+vector-bfgs+): Private ordinary functions
Function, (setf %var-accessor-+vector-bfgs2+): Private ordinary functions
Function, (setf %var-accessor-+waterman14+): Private ordinary functions
Function, (setf %var-accessor-+zuf+): Private ordinary functions
Function, (setf exponent-fit-data-n): Private ordinary functions
Function, (setf exponent-fit-data-sigma): Private ordinary functions
Function, (setf exponent-fit-data-y): Private ordinary functions
Function, 1/gamma: Public ordinary functions
Function, accelerate: Public ordinary functions
Function, accelerate-truncated: Public ordinary functions
Function, accelerated-interpolation-search: Public ordinary functions
Function, acceleration-example: Private ordinary functions
Function, access-value-int: Private ordinary functions
Function, actual-array-c-type: Private ordinary functions
Function, actual-array-class: Private ordinary functions
Function, actual-class-arglist: Private ordinary functions
Function, actual-element-c-type: Private ordinary functions
Function, actual-gsl-function-name: Private ordinary functions
Function, adjust-stepsize: Public ordinary functions
Function, after-llk: Private ordinary functions
Function, airy-ai: Public ordinary functions
Function, airy-ai-deriv: Public ordinary functions
Function, airy-ai-deriv-scaled: Public ordinary functions
Function, airy-ai-scaled: Public ordinary functions
Function, airy-bi: Public ordinary functions
Function, airy-bi-deriv: Public ordinary functions
Function, airy-bi-deriv-scaled: Public ordinary functions
Function, airy-bi-scaled: Public ordinary functions
Function, airy-zero-ai: Public ordinary functions
Function, airy-zero-ai-deriv: Public ordinary functions
Function, airy-zero-bi: Public ordinary functions
Function, airy-zero-bi-deriv: Public ordinary functions
Function, all-io: Private ordinary functions
Function, all-random-number-generators: Public ordinary functions
Function, apply-evolution: Public ordinary functions
Function, apply-hankel: Public ordinary functions
Function, apply-step: Public ordinary functions
Function, arglist-plain-and-categories: Private ordinary functions
Function, argument: Public ordinary functions
Function, array-default: Private ordinary functions
Function, array-element-refs: Private ordinary functions
Function, atanint: Public ordinary functions
Function, backward-derivative: Public ordinary functions
Function, backward-fourier-transform: Public ordinary functions
Function, bernoulli-pdf: Public ordinary functions
Function, bessel-lnknu: Public ordinary functions
Function, bessel-zero-j0: Public ordinary functions
Function, bessel-zero-j1: Public ordinary functions
Function, bessel-zero-jnu: Public ordinary functions
Function, beta: Public ordinary functions
Function, beta-p: Public ordinary functions
Function, beta-pdf: Public ordinary functions
Function, beta-pinv: Public ordinary functions
Function, beta-q: Public ordinary functions
Function, beta-qinv: Public ordinary functions
Function, bidiagonal-decomposition: Public ordinary functions
Function, bidiagonal-unpack: Public ordinary functions
Function, bidiagonal-unpack-diagonal-superdiagonal: Public ordinary functions
Function, bidiagonal-unpack2: Public ordinary functions
Function, bin-samples: Private ordinary functions
Function, binomial: Public ordinary functions
Function, binomial-p: Public ordinary functions
Function, binomial-pdf: Public ordinary functions
Function, binomial-q: Public ordinary functions
Function, bivariate-gaussian-pdf: Public ordinary functions
Function, body-expand: Private ordinary functions
Function, body-no-optional-arg: Private ordinary functions
Function, body-optional-arg: Private ordinary functions
Function, bookdata-ntuple: Public ordinary functions
Function, breakpoint: Public ordinary functions
Function, bspline-example: Private ordinary functions
Function, callback-args: Private ordinary functions
Function, callback-remove-arg: Private ordinary functions
Function, callback-replace-arg: Private ordinary functions
Function, callback-set-dynamic: Private ordinary functions
Function, callback-set-mvb: Private ordinary functions
Function, callback-set-slots: Private ordinary functions
Function, callback-symbol-set: Private ordinary functions
Function, canonical-cycles: Public ordinary functions
Function, canonical-to-linear: Public ordinary functions
Function, category-for-argument: Private ordinary functions
Function, cauchy-p: Public ordinary functions
Function, cauchy-pdf: Public ordinary functions
Function, cauchy-pinv: Public ordinary functions
Function, cauchy-q: Public ordinary functions
Function, cauchy-qinv: Public ordinary functions
Function, cbd-dimensions: Private ordinary functions
Function, cbd-functions: Private ordinary functions
Function, central-derivative: Public ordinary functions
Function, chebyshev-point-example: Private ordinary functions
Function, chebyshev-step: Private ordinary functions
Function, chebyshev-table-example: Private ordinary functions
Function, check-gsl-status: Private ordinary functions
Function, check-null-pointer: Private ordinary functions
Function, chi: Public ordinary functions
Function, chi-squared-p: Public ordinary functions
Function, chi-squared-pdf: Public ordinary functions
Function, chi-squared-pinv: Public ordinary functions
Function, chi-squared-q: Public ordinary functions
Function, chi-squared-qinv: Public ordinary functions
Function, cholesky-invert: Public ordinary functions
Function, choose: Public ordinary functions
Function, ci: Public ordinary functions
Function, cl-argument-types: Private ordinary functions
Function, cl-convert-form: Private ordinary functions
Function, cl-gsl: Private ordinary functions
Function, cl-symbols: Private ordinary functions
Function, clausen: Public ordinary functions
Function, close-ntuple: Public ordinary functions
Function, coefficients: Public ordinary functions
Function, comb-copy: Private ordinary functions
Function, combination-next: Public ordinary functions
Function, combination-previous: Public ordinary functions
Function, combination-range: Public ordinary functions
Function, complementary-incomplete-gamma: Public ordinary functions
Function, complete-definition: Private ordinary functions
Function, complex-with-error: Private ordinary functions
Function, constant-matrix: Private ordinary functions
Function, control-alloc: Public ordinary functions
Function, copy-exponent-fit-data: Private ordinary functions
Function, copy-sa-state: Private ordinary functions
Function, copy-with-stride: Private ordinary functions
Function, cos-err: Public ordinary functions
Function, coulomb-cl: Public ordinary functions
Function, coulomb-cl-array: Public ordinary functions
Function, coulomb-wave-f-array: Public ordinary functions
Function, coulomb-wave-fg: Public ordinary functions
Function, coulomb-wave-fg-array: Public ordinary functions
Function, coulomb-wave-fgp-array: Public ordinary functions
Function, coulomb-wave-sphf-array: Public ordinary functions
Function, coupling-3j: Public ordinary functions
Function, coupling-6j: Public ordinary functions
Function, coupling-9j: Public ordinary functions
Function, create-complex-matrix: Private ordinary functions
Function, create-general-matrix: Private ordinary functions
Function, create-hilbert-matrix: Private ordinary functions
Function, create-matrix: Private ordinary functions
Function, create-moler-matrix: Private ordinary functions
Function, create-ntuple: Public ordinary functions
Function, create-rhs-vector: Private ordinary functions
Function, create-row-matrix: Private ordinary functions
Function, create-singular-matrix: Private ordinary functions
Function, create-vandermonde-matrix: Private ordinary functions
Function, creturn-st: Private ordinary functions
Function, cx-add: Public ordinary functions
Function, cx-add-imag: Public ordinary functions
Function, cx-add-real: Public ordinary functions
Function, cx-arccos: Public ordinary functions
Function, cx-arccos-real: Public ordinary functions
Function, cx-arccosh: Public ordinary functions
Function, cx-arccosh-real: Public ordinary functions
Function, cx-arccot: Public ordinary functions
Function, cx-arccoth: Public ordinary functions
Function, cx-arccsc: Public ordinary functions
Function, cx-arccsc-real: Public ordinary functions
Function, cx-arccsch: Public ordinary functions
Function, cx-arcsec: Public ordinary functions
Function, cx-arcsec-real: Public ordinary functions
Function, cx-arcsech: Public ordinary functions
Function, cx-arcsin: Public ordinary functions
Function, cx-arcsin-real: Public ordinary functions
Function, cx-arcsinh: Public ordinary functions
Function, cx-arctan: Public ordinary functions
Function, cx-arctanh: Public ordinary functions
Function, cx-arctanh-real: Public ordinary functions
Function, cx-conjugate: Public ordinary functions
Function, cx-cos: Public ordinary functions
Function, cx-cosh: Public ordinary functions
Function, cx-cot: Public ordinary functions
Function, cx-coth: Public ordinary functions
Function, cx-csc: Public ordinary functions
Function, cx-csch: Public ordinary functions
Function, cx-div: Public ordinary functions
Function, cx-div-imag: Public ordinary functions
Function, cx-div-real: Public ordinary functions
Function, cx-exp: Public ordinary functions
Function, cx-expt: Public ordinary functions
Function, cx-expt-real: Public ordinary functions
Function, cx-inverse: Public ordinary functions
Function, cx-log: Public ordinary functions
Function, cx-log10: Public ordinary functions
Function, cx-logb: Public ordinary functions
Function, cx-mul: Public ordinary functions
Function, cx-mul-imag: Public ordinary functions
Function, cx-mul-real: Public ordinary functions
Function, cx-negative: Public ordinary functions
Function, cx-sec: Public ordinary functions
Function, cx-sech: Public ordinary functions
Function, cx-sin: Public ordinary functions
Function, cx-sinh: Public ordinary functions
Function, cx-sqrt: Public ordinary functions
Function, cx-sqrt-real: Public ordinary functions
Function, cx-sub: Public ordinary functions
Function, cx-sub-imag: Public ordinary functions
Function, cx-sub-real: Public ordinary functions
Function, cx-tan: Public ordinary functions
Function, cx-tanh: Public ordinary functions
Function, cylindrical-bessel-i0: Public ordinary functions
Function, cylindrical-bessel-i0-scaled: Public ordinary functions
Function, cylindrical-bessel-i1: Public ordinary functions
Function, cylindrical-bessel-i1-scaled: Public ordinary functions
Function, cylindrical-bessel-in-array: Public ordinary functions
Function, cylindrical-bessel-in-scaled-array: Public ordinary functions
Function, cylindrical-bessel-j-array-order: Public ordinary functions
Function, cylindrical-bessel-j-array-x: Public ordinary functions
Function, cylindrical-bessel-j0: Public ordinary functions
Function, cylindrical-bessel-j1: Public ordinary functions
Function, cylindrical-bessel-k0: Public ordinary functions
Function, cylindrical-bessel-k0-scaled: Public ordinary functions
Function, cylindrical-bessel-k1: Public ordinary functions
Function, cylindrical-bessel-k1-scaled: Public ordinary functions
Function, cylindrical-bessel-kn-array: Public ordinary functions
Function, cylindrical-bessel-kn-scaled-array: Public ordinary functions
Function, cylindrical-bessel-y0: Public ordinary functions
Function, cylindrical-bessel-y1: Public ordinary functions
Function, cylindrical-bessel-yn-array: Public ordinary functions
Function, dawson: Public ordinary functions
Function, debye-1: Public ordinary functions
Function, debye-2: Public ordinary functions
Function, debye-3: Public ordinary functions
Function, debye-4: Public ordinary functions
Function, declaration-form: Private ordinary functions
Function, decode-ieee754: Private ordinary functions
Function, default-covariance: Private ordinary functions
Function, default-lls-workspace: Private ordinary functions
Function, defgeneric-method-p: Private ordinary functions
Function, defmfun-return: Private ordinary functions
Function, delete-test-definition: Private ordinary functions
Function, deriv-f1-d: Private ordinary functions
Function, deriv-f2: Private ordinary functions
Function, deriv-f2-d: Private ordinary functions
Function, deriv-f3: Private ordinary functions
Function, deriv-f3-d: Private ordinary functions
Function, deriv-f4: Private ordinary functions
Function, deriv-f4-d: Private ordinary functions
Function, deriv-f5: Private ordinary functions
Function, deriv-f5-d: Private ordinary functions
Function, deriv-f6-d: Private ordinary functions
Function, derivative-chebyshev: Public ordinary functions
Function, dirichlet-log-pdf: Public ordinary functions
Function, dirichlet-pdf: Public ordinary functions
Function, discrete-pdf: Public ordinary functions
Function, distribution-bin-integral: Private ordinary functions
Function, divided-difference: Public ordinary functions
Function, double-factorial: Public ordinary functions
Function, double-float-unequal: Public ordinary functions
Function, eigenvalue-eigenvectors-example: Private ordinary functions
Function, eigenvalues-eigenvectors-gen: Public ordinary functions
Function, eigenvalues-eigenvectors-nonsymm: Public ordinary functions
Function, eigenvalues-gen: Public ordinary functions
Function, eigenvalues-nonsymm: Public ordinary functions
Function, element-type-select: Private ordinary functions
Function, elliptic-integral-d: Public ordinary functions
Function, elliptic-integral-e: Public ordinary functions
Function, elliptic-integral-e-complete: Public ordinary functions
Function, elliptic-integral-f: Public ordinary functions
Function, elliptic-integral-k-complete: Public ordinary functions
Function, elliptic-integral-p: Public ordinary functions
Function, elliptic-integral-rc: Public ordinary functions
Function, elliptic-integral-rd: Public ordinary functions
Function, elliptic-integral-rf: Public ordinary functions
Function, elliptic-integral-rj: Public ordinary functions
Function, eql-specializer: Private ordinary functions
Function, erf: Public ordinary functions
Function, erf-q: Public ordinary functions
Function, erf-z: Public ordinary functions
Function, erfc: Public ordinary functions
Function, establish-handler: Private ordinary functions
Function, eta: Public ordinary functions
Function, evaluate-chebyshev-error: Public ordinary functions
Function, evaluate-integral-example: Private ordinary functions
Function, evaluate-with-derivatives: Public ordinary functions
Function, examples: Public ordinary functions
Function, exp-1: Public ordinary functions
Function, exp-err: Public ordinary functions
Function, exp-err-scaled: Public ordinary functions
Function, exp-mult: Public ordinary functions
Function, exp-mult-err: Public ordinary functions
Function, exp-mult-err-scaled: Public ordinary functions
Function, exp-mult-scaled: Public ordinary functions
Function, exp-scaled: Public ordinary functions
Function, expand-defmfun-arrays: Private ordinary functions
Function, expand-defmfun-defmethods: Private ordinary functions
Function, expand-defmfun-generic: Private ordinary functions
Function, expand-defmfun-method: Private ordinary functions
Function, expand-defmfun-optional: Private ordinary functions
Function, expand-defmfun-wrap: Private ordinary functions
Function, expm1: Public ordinary functions
Function, exponent-fit-data-n: Private ordinary functions
Function, exponent-fit-data-p: Private ordinary functions
Function, exponent-fit-data-sigma: Private ordinary functions
Function, exponent-fit-data-y: Private ordinary functions
Function, exponential-integral-3: Public ordinary functions
Function, exponential-integral-e1: Public ordinary functions
Function, exponential-integral-e2: Public ordinary functions
Function, exponential-integral-ei: Public ordinary functions
Function, exponential-integral-en: Public ordinary functions
Function, exponential-p: Public ordinary functions
Function, exponential-pdf: Public ordinary functions
Function, exponential-pinv: Public ordinary functions
Function, exponential-power-p: Public ordinary functions
Function, exponential-power-pdf: Public ordinary functions
Function, exponential-power-q: Public ordinary functions
Function, exponential-q: Public ordinary functions
Function, exponential-qinv: Public ordinary functions
Function, exponential-residual: Private ordinary functions
Function, exponential-residual-derivative: Private ordinary functions
Function, exponential-residual-fdf: Private ordinary functions
Function, exprel: Public ordinary functions
Function, exprel-2: Public ordinary functions
Function, exprel-n: Public ordinary functions
Function, factorial: Public ordinary functions
Function, faify-form: Private ordinary functions
Function, fdist-p: Public ordinary functions
Function, fdist-pdf: Public ordinary functions
Function, fdist-pinv: Public ordinary functions
Function, fdist-q: Public ordinary functions
Function, fdist-qinv: Public ordinary functions
Function, fermi-dirac-0: Public ordinary functions
Function, fermi-dirac-1: Public ordinary functions
Function, fermi-dirac-1/2: Public ordinary functions
Function, fermi-dirac-2: Public ordinary functions
Function, fermi-dirac-3/2: Public ordinary functions
Function, fermi-dirac-inc-0: Public ordinary functions
Function, fermi-dirac-integral: Public ordinary functions
Function, fermi-dirac-m1: Public ordinary functions
Function, fermi-dirac-m1/2: Public ordinary functions
Function, fft-complex-off-stride-check: Private ordinary functions
Function, fft-frequency-split: Private ordinary functions
Function, fft-frequency-step: Private ordinary functions
Function, fft-frequency-vector: Public ordinary functions
Function, fft-highest-frequency: Private ordinary functions
Function, fft-inverse-shift: Public ordinary functions
Function, fft-pulse-test: Private ordinary functions
Function, fft-shift: Public ordinary functions
Function, fft-test-forms: Private ordinary functions
Function, finitep: Public ordinary functions
Function, fit-gradient: Public ordinary functions
Function, fit-test-delta: Public ordinary functions
Function, fit-test-gradient: Public ordinary functions
Function, flat-p: Public ordinary functions
Function, flat-pdf: Public ordinary functions
Function, flat-pinv: Public ordinary functions
Function, flat-q: Public ordinary functions
Function, flat-qinv: Public ordinary functions
Function, float-as-integer: Public ordinary functions
Function, fminimizer-f-lower: Public ordinary functions
Function, fminimizer-f-upper: Public ordinary functions
Function, fminimizer-x-lower: Public ordinary functions
Function, fminimizer-x-upper: Public ordinary functions
Function, format-ieee754-bits: Public ordinary functions
Function, forward-backward: Private ordinary functions
Function, forward-derivative: Public ordinary functions
Function, forward-fourier-transform: Public ordinary functions
Function, fourier-transform: Public ordinary functions
Function, fsolver-lower: Public ordinary functions
Function, fsolver-upper: Public ordinary functions
Function, gamma: Public ordinary functions
Function, gamma*: Public ordinary functions
Function, gamma-p: Public ordinary functions
Function, gamma-pdf: Public ordinary functions
Function, gamma-pinv: Public ordinary functions
Function, gamma-q: Public ordinary functions
Function, gamma-qinv: Public ordinary functions
Function, gaussian-p: Public ordinary functions
Function, gaussian-pdf: Public ordinary functions
Function, gaussian-pinv: Public ordinary functions
Function, gaussian-q: Public ordinary functions
Function, gaussian-qinv: Public ordinary functions
Function, gaussian-tail-pdf: Public ordinary functions
Function, gegenbauer: Public ordinary functions
Function, gegenbauer-1: Public ordinary functions
Function, gegenbauer-2: Public ordinary functions
Function, gegenbauer-3: Public ordinary functions
Function, gegenbauer-array: Public ordinary functions
Function, generate-all-array-tests-body: Private ordinary functions
Function, generate-all-permutations: Private ordinary functions
Function, generate-all-permutations-backwards: Private ordinary functions
Function, generate-methods: Private ordinary functions
Function, generate-nlls-data: Private ordinary functions
Function, geometric-p: Public ordinary functions
Function, geometric-pdf: Public ordinary functions
Function, geometric-q: Public ordinary functions
Function, get-callbacks-for-class: Private ordinary functions
Function, get-mcm-parameters: Private ordinary functions
Function, get-mcv-parameters: Private ordinary functions
Function, get-random-number: Public ordinary functions
Function, greville-abscissa: Public ordinary functions
Function, gsl-asinh: Public ordinary functions
Function, gsl-atanh: Public ordinary functions
Function, gsl-config-pathname: Private ordinary functions
Function, gsl-exp: Public ordinary functions
Function, gsl-lookup: Public ordinary functions
Function, gsl-random-state: Public ordinary functions
Function, gumbel1-p: Public ordinary functions
Function, gumbel1-pdf: Public ordinary functions
Function, gumbel1-pinv: Public ordinary functions
Function, gumbel1-q: Public ordinary functions
Function, gumbel1-qinv: Public ordinary functions
Function, gumbel2-p: Public ordinary functions
Function, gumbel2-pdf: Public ordinary functions
Function, gumbel2-pinv: Public ordinary functions
Function, gumbel2-q: Public ordinary functions
Function, gumbel2-qinv: Public ordinary functions
Function, have-at-least-gsl-version: Private ordinary functions
Function, hazard: Public ordinary functions
Function, heapsort: Public ordinary functions
Function, heapsort-index: Public ordinary functions
Function, histo-clone: Private ordinary functions
Function, histo-copy: Private ordinary functions
Function, histo2d-clone: Private ordinary functions
Function, histo2d-copy: Private ordinary functions
Function, histogram-covariance: Public ordinary functions
Function, histogram-find: Public ordinary functions
Function, householder-hm: Public ordinary functions
Function, householder-hv: Public ordinary functions
Function, householder-mh: Public ordinary functions
Function, householder-solve: Public ordinary functions
Function, householder-transform: Public ordinary functions
Function, hurwitz-zeta: Public ordinary functions
Function, hydrogenicr: Public ordinary functions
Function, hydrogenicr-1: Public ordinary functions
Function, hypergeometric-0f1: Public ordinary functions
Function, hypergeometric-2f0: Public ordinary functions
Function, hypergeometric-2f1: Public ordinary functions
Function, hypergeometric-2f1-conj: Public ordinary functions
Function, hypergeometric-2f1-conj-renorm: Public ordinary functions
Function, hypergeometric-2f1-renorm: Public ordinary functions
Function, hypergeometric-p: Public ordinary functions
Function, hypergeometric-pdf: Public ordinary functions
Function, hypergeometric-q: Public ordinary functions
Function, hypotenuse: Public ordinary functions
Function, hypotenuse*: Public ordinary functions
Function, ieee754-sign-bit: Private ordinary functions
Function, incomplete-beta: Public ordinary functions
Function, incomplete-gamma: Public ordinary functions
Function, infinityp: Public ordinary functions
Function, init-first: Public ordinary functions
Function, init-last: Public ordinary functions
Function, initialize-suffix-switched-foreign: Private ordinary functions
Function, integer-as-float: Public ordinary functions
Function, integral-chebyshev: Public ordinary functions
Function, integrate-vanderpol: Private ordinary functions
Function, integration-qag: Public ordinary functions
Function, integration-qagi: Public ordinary functions
Function, integration-qagil: Public ordinary functions
Function, integration-qagiu: Public ordinary functions
Function, integration-qagp: Public ordinary functions
Function, integration-qags: Public ordinary functions
Function, integration-qawc: Public ordinary functions
Function, integration-qawf: Public ordinary functions
Function, integration-qawo: Public ordinary functions
Function, integration-qaws: Public ordinary functions
Function, integration-qng: Public ordinary functions
Function, integration-test-f1: Private ordinary functions
Function, integration-test-f11: Private ordinary functions
Function, integration-test-f15: Private ordinary functions
Function, integration-test-f16: Private ordinary functions
Function, integration-test-f3: Private ordinary functions
Function, integration-test-f454: Private ordinary functions
Function, integration-test-f455: Private ordinary functions
Function, integration-test-f456: Private ordinary functions
Function, integration-test-f457: Private ordinary functions
Function, integration-test-f458: Private ordinary functions
Function, integration-test-f459: Private ordinary functions
Function, integration-test-myfn1: Private ordinary functions
Function, integration-test-myfn2: Private ordinary functions
Function, interpolation-search: Public ordinary functions
Function, inverse-fourier-transform: Public ordinary functions
Function, inversions: Public ordinary functions
Function, jacobian: Public ordinary functions
Function, jacobian-elliptic-functions: Public ordinary functions
Function, knots: Public ordinary functions
Function, laguerre: Public ordinary functions
Function, laguerre-1: Public ordinary functions
Function, laguerre-2: Public ordinary functions
Function, laguerre-3: Public ordinary functions
Function, lambert-w0: Public ordinary functions
Function, lambert-wm1: Public ordinary functions
Function, landau-pdf: Public ordinary functions
Function, laplace-p: Public ordinary functions
Function, laplace-pdf: Public ordinary functions
Function, laplace-pinv: Public ordinary functions
Function, laplace-q: Public ordinary functions
Function, laplace-qinv: Public ordinary functions
Function, legendre-conicalp-0: Public ordinary functions
Function, legendre-conicalp-1: Public ordinary functions
Function, legendre-conicalp-half: Public ordinary functions
Function, legendre-conicalp-mhalf: Public ordinary functions
Function, legendre-h3d: Public ordinary functions
Function, legendre-h3d-0: Public ordinary functions
Function, legendre-h3d-1: Public ordinary functions
Function, legendre-h3d-array: Public ordinary functions
Function, legendre-p1: Public ordinary functions
Function, legendre-p2: Public ordinary functions
Function, legendre-p3: Public ordinary functions
Function, legendre-pl: Public ordinary functions
Function, legendre-pl-array: Public ordinary functions
Function, legendre-pl-deriv-array: Public ordinary functions
Function, legendre-plm: Public ordinary functions
Function, legendre-q0: Public ordinary functions
Function, legendre-q1: Public ordinary functions
Function, legendre-ql: Public ordinary functions
Function, legendre-regular-cylindrical-conical: Public ordinary functions
Function, legendre-regular-spherical-conical: Public ordinary functions
Function, legendre-sphplm: Public ordinary functions
Function, levin-value: Private ordinary functions
Function, limits-check: Private ordinary functions
Function, linear-cycles: Public ordinary functions
Function, linear-estimate: Public ordinary functions
Function, linear-fit: Public ordinary functions
Function, linear-least-squares-multivariate-example: Private ordinary functions
Function, linear-least-squares-univariate-example: Private ordinary functions
Function, linear-mfit: Public ordinary functions
Function, linear-mfit-nosvd: Private ordinary functions
Function, linear-mfit-svd: Private ordinary functions
Function, linear-to-canonical: Public ordinary functions
Function, log+1: Public ordinary functions
Function, log-1+x: Public ordinary functions
Function, log-1+x-m1: Public ordinary functions
Function, log-abs: Public ordinary functions
Function, log-beta: Public ordinary functions
Function, log-choose: Public ordinary functions
Function, log-cosh: Public ordinary functions
Function, log-double-factorial: Public ordinary functions
Function, log-erfc: Public ordinary functions
Function, log-factorial: Public ordinary functions
Function, log-gamma: Public ordinary functions
Function, log-gamma-complex: Public ordinary functions
Function, log-gamma-sign: Public ordinary functions
Function, log-modulus: Public ordinary functions
Function, log-pochammer: Public ordinary functions
Function, log-pochammer-sign: Public ordinary functions
Function, log-sin: Public ordinary functions
Function, log-sinh: Public ordinary functions
Function, logarithmic-pdf: Public ordinary functions
Function, logistic-p: Public ordinary functions
Function, logistic-pdf: Public ordinary functions
Function, logistic-pinv: Public ordinary functions
Function, logistic-q: Public ordinary functions
Function, logistic-qinv: Public ordinary functions
Function, lognormal-p: Public ordinary functions
Function, lognormal-pdf: Public ordinary functions
Function, lognormal-pinv: Public ordinary functions
Function, lognormal-q: Public ordinary functions
Function, lognormal-qinv: Public ordinary functions
Function, lookup-condition: Private ordinary functions
Function, ls-covariance: Public ordinary functions
Function, make-acceleration: Public ordinary functions
Function, make-and-init-vector: Private ordinary functions
Function, make-basis-spline: Public ordinary functions
Function, make-cbstruct: Private ordinary functions
Function, make-cbstruct-object: Private ordinary functions
Function, make-chebyshev: Public ordinary functions
Function, make-combination: Public ordinary functions
Function, make-compiled-funcallable: Private ordinary functions
Function, make-defmcallbacks: Private ordinary functions
Function, make-discrete-random: Public ordinary functions
Function, make-eigen-gen: Public ordinary functions
Function, make-eigen-genherm: Public ordinary functions
Function, make-eigen-genhermv: Public ordinary functions
Function, make-eigen-gensymm: Public ordinary functions
Function, make-eigen-gensymmv: Public ordinary functions
Function, make-eigen-genv: Public ordinary functions
Function, make-eigen-herm: Public ordinary functions
Function, make-eigen-hermv: Public ordinary functions
Function, make-eigen-nonsymm: Public ordinary functions
Function, make-eigen-nonsymmv: Public ordinary functions
Function, make-eigen-symm: Public ordinary functions
Function, make-eigen-symmv: Public ordinary functions
Function, make-exponent-fit-data: Private ordinary functions
Function, make-fft-complex-wavetable-double-float: Private ordinary functions
Function, make-fft-complex-wavetable-single-float: Private ordinary functions
Function, make-fft-complex-workspace-double-float: Private ordinary functions
Function, make-fft-complex-workspace-single-float: Private ordinary functions
Function, make-fft-half-complex-wavetable-double-float: Private ordinary functions
Function, make-fft-half-complex-wavetable-single-float: Private ordinary functions
Function, make-fft-real-wavetable-double-float: Private ordinary functions
Function, make-fft-real-wavetable-single-float: Private ordinary functions
Function, make-fft-real-workspace-double-float: Private ordinary functions
Function, make-fft-real-workspace-single-float: Private ordinary functions
Function, make-fft-wavetable: Public ordinary functions
Function, make-fft-workspace: Public ordinary functions
Function, make-fit-workspace: Public ordinary functions
Function, make-foreign-array-from-mpointer: Private ordinary functions
Function, make-funcallable-form: Private ordinary functions
Function, make-funcallables-for-object: Private ordinary functions
Function, make-gsl-metadata: Private ordinary functions
Function, make-hankel: Public ordinary functions
Function, make-histogram: Public ordinary functions
Function, make-histogram-pdf: Public ordinary functions
Function, make-histogram2d: Public ordinary functions
Function, make-histogram2d-pdf: Public ordinary functions
Function, make-initialize-instance: Private ordinary functions
Function, make-integration-workspace: Public ordinary functions
Function, make-interpolation: Public ordinary functions
Function, make-jacobian-matrix: Public ordinary functions
Function, make-levin: Public ordinary functions
Function, make-levin-truncated: Public ordinary functions
Function, make-list-from-pool: Private ordinary functions
Function, make-mathieu: Public ordinary functions
Function, make-mobject-defmcallbacks: Private ordinary functions
Function, make-monte-carlo-miser: Public ordinary functions
Function, make-monte-carlo-plain: Public ordinary functions
Function, make-monte-carlo-vegas: Public ordinary functions
Function, make-multi-dimensional-minimizer-f: Public ordinary functions
Function, make-multi-dimensional-minimizer-fdf: Public ordinary functions
Function, make-multi-dimensional-root-solver-f: Public ordinary functions
Function, make-multi-dimensional-root-solver-fdf: Public ordinary functions
Function, make-new-sa-state: Private ordinary functions
Function, make-nonlinear-fdffit: Public ordinary functions
Function, make-nonlinear-ffit: Public ordinary functions
Function, make-ntuple-example-data: Private ordinary functions
Function, make-ode-evolution: Public ordinary functions
Function, make-ode-stepper: Public ordinary functions
Function, make-one-dimensional-minimizer: Public ordinary functions
Function, make-one-dimensional-root-solver-f: Public ordinary functions
Function, make-one-dimensional-root-solver-fdf: Public ordinary functions
Function, make-permutation: Public ordinary functions
Function, make-polynomial-complex-workspace: Public ordinary functions
Function, make-qawo-table: Public ordinary functions
Function, make-qaws-table: Public ordinary functions
Function, make-quasi-random-number-generator: Public ordinary functions
Function, make-random-number-generator: Public ordinary functions
Function, make-reinitialize-instance: Private ordinary functions
Function, make-sa-states: Private ordinary functions
Function, make-scaled-control: Public ordinary functions
Function, make-spline: Public ordinary functions
Function, make-standard-control: Public ordinary functions
Function, make-symbol-cardinal: Private ordinary functions
Function, make-symbol-cardinals: Private ordinary functions
Function, make-urand-vector: Private ordinary functions
Function, make-wavelet: Public ordinary functions
Function, make-wavelet-workspace: Public ordinary functions
Function, make-y-control: Public ordinary functions
Function, make-yp-control: Public ordinary functions
Function, map-name: Private ordinary functions
Function, mappend: Private ordinary functions
Function, mathieu-a: Public ordinary functions
Function, mathieu-a-array: Public ordinary functions
Function, mathieu-b: Public ordinary functions
Function, mathieu-b-array: Public ordinary functions
Function, mathieu-ce: Public ordinary functions
Function, mathieu-ce-array: Public ordinary functions
Function, mathieu-mc: Public ordinary functions
Function, mathieu-mc-array: Public ordinary functions
Function, mathieu-ms: Public ordinary functions
Function, mathieu-ms-array: Public ordinary functions
Function, mathieu-se: Public ordinary functions
Function, mathieu-se-array: Public ordinary functions
Function, matrix-exponential: Public ordinary functions
Function, matrix-product-dimensions: Private ordinary functions
Function, mcrw: Private ordinary functions
Function, mean-2x: Private ordinary functions
Function, mean-2y: Private ordinary functions
Function, mfdfminimizer-gradient: Public ordinary functions
Function, mfdfminimizer-restart: Public ordinary functions
Function, min-test-gradient: Public ordinary functions
Function, min-test-interval: Public ordinary functions
Function, min-test-size: Public ordinary functions
Function, minimization-one-example: Private ordinary functions
Function, mobject-cbvname: Private ordinary functions
Function, mobject-cbvnames: Private ordinary functions
Function, mobject-fnvname: Private ordinary functions
Function, mobject-fnvnames: Private ordinary functions
Function, mobject-maker: Private ordinary functions
Function, mobject-variable-name: Private ordinary functions
Function, modulus: Public ordinary functions
Function, modulus2: Public ordinary functions
Function, monte-carlo-integrate-miser: Public ordinary functions
Function, monte-carlo-integrate-plain: Public ordinary functions
Function, monte-carlo-integrate-vegas: Public ordinary functions
Function, multi-linear-estimate: Public ordinary functions
Function, multi-linear-residuals: Public ordinary functions
Function, multimin-example-derivative: Private ordinary functions
Function, multimin-example-derivative-scalars: Private ordinary functions
Function, multimin-example-no-derivative: Private ordinary functions
Function, multinomial-log-pdf: Public ordinary functions
Function, multinomial-pdf: Public ordinary functions
Function, multiplier-estimate: Public ordinary functions
Function, multiplier-fit: Public ordinary functions
Function, multiply: Public ordinary functions
Function, multiply-err: Public ordinary functions
Function, multiroot-slot: Private ordinary functions
Function, multiroot-test-delta: Public ordinary functions
Function, multiroot-test-residual: Public ordinary functions
Function, mv-linear-least-squares-data: Private ordinary functions
Function, nanp: Public ordinary functions
Function, negative-binomial-p: Public ordinary functions
Function, negative-binomial-pdf: Public ordinary functions
Function, negative-binomial-q: Public ordinary functions
Function, next-float: Private ordinary functions
Function, nonlinear-least-squares-example: Private ordinary functions
Function, nonnormalized-incomplete-gamma: Public ordinary functions
Function, norm-f: Private ordinary functions
Function, ntuple-example-histogramming: Private ordinary functions
Function, ntuple-example-make-read: Private ordinary functions
Function, ntuple-example-read: Private ordinary functions
Function, ntuple-example-sel-func: Private ordinary functions
Function, ntuple-example-val-func: Private ordinary functions
Function, ntuple-example-values: Private ordinary functions
Function, number-of-breakpoints: Public ordinary functions
Function, number-of-callbacks: Private ordinary functions
Function, number-of-coefficients: Public ordinary functions
Function, open-ntuple: Public ordinary functions
Function, optional-args-to-switch-gsl-functions: Private ordinary functions
Function, paraboloid-and-derivative: Private ordinary functions
Function, paraboloid-and-derivative-scalar: Private ordinary functions
Function, paraboloid-derivative: Private ordinary functions
Function, paraboloid-derivative-scalar: Private ordinary functions
Function, paraboloid-scalar: Private ordinary functions
Function, paraboloid-vector: Private ordinary functions
Function, pareto-p: Public ordinary functions
Function, pareto-pdf: Public ordinary functions
Function, pareto-pinv: Public ordinary functions
Function, pareto-q: Public ordinary functions
Function, pareto-qinv: Public ordinary functions
Function, parse-callback-argspec: Private ordinary functions
Function, parse-callback-fnspec: Private ordinary functions
Function, parse-callback-static: Private ordinary functions
Function, pascal-p: Public ordinary functions
Function, pascal-pdf: Public ordinary functions
Function, pascal-q: Public ordinary functions
Function, perm-copy: Private ordinary functions
Function, permutation*: Public ordinary functions
Function, permutation-data: Public ordinary functions
Function, permutation-inverse: Public ordinary functions
Function, permutation-next: Public ordinary functions
Function, permutation-previous: Public ordinary functions
Function, permutation-reverse: Public ordinary functions
Function, plural-symbol: Private ordinary functions
Function, pochammer: Public ordinary functions
Function, poisson-p: Public ordinary functions
Function, poisson-pdf: Public ordinary functions
Function, poisson-q: Public ordinary functions
Function, polar-to-rectangular: Public ordinary functions
Function, polynomial-solve: Public ordinary functions
Function, pow: Public ordinary functions
Function, powell: Private ordinary functions
Function, power-of-2-p: Private ordinary functions
Function, project-ntuple: Public ordinary functions
Function, psi-1+iy: Public ordinary functions
Function, psi-n: Public ordinary functions
Function, qr-decomposition: Public ordinary functions
Function, qr-qrsolve: Public ordinary functions
Function, qr-qtvector: Public ordinary functions
Function, qr-qvector: Public ordinary functions
Function, qr-rsolve: Public ordinary functions
Function, qr-solve: Public ordinary functions
Function, qr-solve-least-squares: Public ordinary functions
Function, qr-unpack: Public ordinary functions
Function, qr-update: Public ordinary functions
Function, qrng-get: Public ordinary functions
Function, qrpt-decomposition: Public ordinary functions
Function, qrpt-decomposition*: Public ordinary functions
Function, qrpt-qrsolve: Public ordinary functions
Function, qrpt-rsolve: Public ordinary functions
Function, qrpt-solve: Public ordinary functions
Function, qrpt-update: Public ordinary functions
Function, quadratic: Private ordinary functions
Function, quadratic-and-derivative: Private ordinary functions
Function, quadratic-derivative: Private ordinary functions
Function, quasi-clone: Private ordinary functions
Function, quasi-copy: Private ordinary functions
Function, r-solve: Public ordinary functions
Function, random-walk-miser-example: Private ordinary functions
Function, random-walk-plain-example: Private ordinary functions
Function, random-walk-vegas-example: Private ordinary functions
Function, rayleigh-p: Public ordinary functions
Function, rayleigh-pdf: Public ordinary functions
Function, rayleigh-pinv: Public ordinary functions
Function, rayleigh-q: Public ordinary functions
Function, rayleigh-qinv: Public ordinary functions
Function, rayleigh-tail-pdf: Public ordinary functions
Function, read-ntuple: Public ordinary functions
Function, realpart-vector: Private ordinary functions
Function, record-callbacks-for-class: Private ordinary functions
Function, rectangular-to-polar: Public ordinary functions
Function, reference-foreign-element: Private ordinary functions
Function, relative-pochammer: Public ordinary functions
Function, reset-urand: Private ordinary functions
Function, restrict-positive: Public ordinary functions
Function, restrict-symmetric: Public ordinary functions
Function, rng-clone: Private ordinary functions
Function, rng-copy: Private ordinary functions
Function, rng-environment-setup: Public ordinary functions
Function, rng-max: Public ordinary functions
Function, rng-min: Public ordinary functions
Function, rng-types-setup: Private ordinary functions
Function, root-test-delta: Public ordinary functions
Function, root-test-interval: Public ordinary functions
Function, root-test-residual: Public ordinary functions
Function, roots-multi-example-derivative: Private ordinary functions
Function, roots-multi-example-no-derivative: Private ordinary functions
Function, roots-one-example-derivative: Private ordinary functions
Function, roots-one-example-no-derivative: Private ordinary functions
Function, rosenbrock: Private ordinary functions
Function, rosenbrock-df: Private ordinary functions
Function, rosenbrock-fdf: Private ordinary functions
Function, sa-state-value: Private ordinary functions
Function, sample-k-hankel: Public ordinary functions
Function, sample-x-hankel: Public ordinary functions
Function, scalar-default: Private ordinary functions
Function, sdot: Public ordinary functions
Function, set-cbstruct: Private ordinary functions
Function, set-floating-point-modes: Public ordinary functions
Function, set-mcm-parameters: Private ordinary functions
Function, set-mcv-parameters: Private ordinary functions
Function, set-parameters: Private ordinary functions
Function, set-parameters-gen: Private ordinary functions
Function, set-parameters-nonsymmetric: Private ordinary functions
Function, set-slot-function: Private ordinary functions
Function, set-structure-slot: Private ordinary functions
Function, sf-check-results: Private ordinary functions
Function, sf-check-single: Private ordinary functions
Function, sf-frac-diff: Private ordinary functions
Function, shi: Public ordinary functions
Function, si: Public ordinary functions
Function, sigma-2x: Private ordinary functions
Function, sigma-2y: Private ordinary functions
Function, signal-gsl-error: Private ordinary functions
Function, signal-gsl-warning: Private ordinary functions
Function, simulated-annealing: Public ordinary functions
Function, simulated-annealing-example: Private ordinary functions
Function, simulated-annealing-int: Private ordinary functions
Function, simulated-annealing-test: Private ordinary functions
Function, sin-err: Public ordinary functions
Function, sinc: Public ordinary functions
Function, singular-symbol: Private ordinary functions
Function, singularize: Private ordinary functions
Function, size-array: Private ordinary functions
Function, size-vector-scalar: Private ordinary functions
Function, solve-cubic: Public ordinary functions
Function, solve-cubic-complex: Public ordinary functions
Function, solve-cyclic-tridiagonal: Public ordinary functions
Function, solve-quadratic: Public ordinary functions
Function, solve-quadratic-complex: Public ordinary functions
Function, solve-symmetric-cyclic-tridiagonal: Public ordinary functions
Function, solve-symmetric-tridiagonal: Public ordinary functions
Function, solve-tridiagonal: Public ordinary functions
Function, solve-tridiagonal-example: Private ordinary functions
Function, spherical-bessel-i0-scaled: Public ordinary functions
Function, spherical-bessel-i1-scaled: Public ordinary functions
Function, spherical-bessel-i2-scaled: Public ordinary functions
Function, spherical-bessel-il-scaled: Public ordinary functions
Function, spherical-bessel-il-scaled-array: Public ordinary functions
Function, spherical-bessel-j0: Public ordinary functions
Function, spherical-bessel-j1: Public ordinary functions
Function, spherical-bessel-j2: Public ordinary functions
Function, spherical-bessel-jl: Public ordinary functions
Function, spherical-bessel-jl-array: Public ordinary functions
Function, spherical-bessel-jl-steed-array: Public ordinary functions
Function, spherical-bessel-k0-scaled: Public ordinary functions
Function, spherical-bessel-k1-scaled: Public ordinary functions
Function, spherical-bessel-k2-scaled: Public ordinary functions
Function, spherical-bessel-kl-scaled: Public ordinary functions
Function, spherical-bessel-kl-scaled-array: Public ordinary functions
Function, spherical-bessel-y0: Public ordinary functions
Function, spherical-bessel-y1: Public ordinary functions
Function, spherical-bessel-y2: Public ordinary functions
Function, spherical-bessel-yl: Public ordinary functions
Function, spherical-bessel-yl-array: Public ordinary functions
Function, spline-example: Private ordinary functions
Function, state-pointer: Private ordinary functions
Function, step-order: Public ordinary functions
Function, stupid-code-walk-eval-some: Private ordinary functions
Function, stupid-code-walk-find-variables: Private ordinary functions
Function, success-continue: Private ordinary functions
Function, success-failure: Private ordinary functions
Function, sv-decomposition: Public ordinary functions
Function, sv-jacobi-decomposition: Public ordinary functions
Function, sv-modified-decomposition: Public ordinary functions
Function, sv-solve: Public ordinary functions
Function, symbol-keyword-symbol: Private ordinary functions
Function, synchrotron-1: Public ordinary functions
Function, synchrotron-2: Public ordinary functions
Function, taylor-coefficient: Public ordinary functions
Function, taylor-divided-difference: Public ordinary functions
Function, tdist-p: Public ordinary functions
Function, tdist-pdf: Public ordinary functions
Function, tdist-pinv: Public ordinary functions
Function, tdist-q: Public ordinary functions
Function, tdist-qinv: Public ordinary functions
Function, test-cholesky-decomp-dim: Private ordinary functions
Function, test-cholesky-invert-dim: Private ordinary functions
Function, test-cholesky-solve-dim: Private ordinary functions
Function, test-complex-fft-noise: Private ordinary functions
Function, test-fft-noise: Private ordinary functions
Function, test-hh-solve-dim: Private ordinary functions
Function, test-lu-solve-dim: Private ordinary functions
Function, test-qr-decomp-dim: Private ordinary functions
Function, test-qr-lssolve-dim: Private ordinary functions
Function, test-qr-qrsolve-dim: Private ordinary functions
Function, test-qr-solve-dim: Private ordinary functions
Function, test-qr-update-dim: Private ordinary functions
Function, test-qrpt-decomp-dim: Private ordinary functions
Function, test-qrpt-qrsolve-dim: Private ordinary functions
Function, test-qrpt-solve-dim: Private ordinary functions
Function, test-real-fft-noise: Private ordinary functions
Function, test-sv-solve-dim: Private ordinary functions
Function, testpdf: Private ordinary functions
Function, transport-2: Public ordinary functions
Function, transport-3: Public ordinary functions
Function, transport-4: Public ordinary functions
Function, transport-5: Public ordinary functions
Function, trivial-example-energy: Private ordinary functions
Function, trivial-example-metric: Private ordinary functions
Function, trivial-example-step: Private ordinary functions
Function, trivial-test-energy: Private ordinary functions
Function, ugaussian-p: Public ordinary functions
Function, ugaussian-pdf: Public ordinary functions
Function, ugaussian-pinv: Public ordinary functions
Function, ugaussian-q: Public ordinary functions
Function, ugaussian-qinv: Public ordinary functions
Function, ugaussian-tail-pdf: Public ordinary functions
Function, uniform-knots: Public ordinary functions
Function, unpack: Public ordinary functions
Function, urand: Private ordinary functions
Function, value-from-dimensions: Private ordinary functions
Function, values-unless-singleton: Private ordinary functions
Function, values-with-errors: Private ordinary functions
Function, vanderpol: Private ordinary functions
Function, vanderpol-jacobian: Private ordinary functions
Function, variables-used-in-c-arguments: Private ordinary functions
Function, vdf: Private ordinary functions
Function, vdf-size: Private ordinary functions
Function, vector/length: Private ordinary functions
Function, view-bin-as-foreign-array: Private ordinary functions
Function, view-range-as-foreign-array: Private ordinary functions
Function, vspecs-direction: Private ordinary functions
Function, wavelet-2d-nonstandard-transform: Public ordinary functions
Function, wavelet-2d-nonstandard-transform-forward: Public ordinary functions
Function, wavelet-2d-nonstandard-transform-inverse: Public ordinary functions
Function, wavelet-2d-nonstandard-transform-matrix: Public ordinary functions
Function, wavelet-2d-nonstandard-transform-matrix-forward: Public ordinary functions
Function, wavelet-2d-nonstandard-transform-matrix-inverse: Public ordinary functions
Function, wavelet-2d-transform: Public ordinary functions
Function, wavelet-2d-transform-forward: Public ordinary functions
Function, wavelet-2d-transform-inverse: Public ordinary functions
Function, wavelet-2d-transform-matrix: Public ordinary functions
Function, wavelet-2d-transform-matrix-forward: Public ordinary functions
Function, wavelet-2d-transform-matrix-inverse: Public ordinary functions
Function, wavelet-example: Private ordinary functions
Function, wavelet-forward-example: Private ordinary functions
Function, wavelet-transform: Public ordinary functions
Function, wavelet-transform-forward: Public ordinary functions
Function, wavelet-transform-inverse: Public ordinary functions
Function, weibull-p: Public ordinary functions
Function, weibull-pdf: Public ordinary functions
Function, weibull-pinv: Public ordinary functions
Function, weibull-q: Public ordinary functions
Function, weibull-qinv: Public ordinary functions
Function, wfo-declare: Private ordinary functions
Function, wrap-index-export: Private ordinary functions
Function, wrap-letlike: Private ordinary functions
Function, wrap-progn: Private ordinary functions
Function, write-ntuple: Public ordinary functions
function-value: Public generic functions
function-value: Public generic functions
function-value: Public generic functions
function-value: Public generic functions
function-value: Public generic functions
function-value: Public generic functions
function-value: Public generic functions
functions: Private generic functions
functions: Private generic functions

G
gamma: Public ordinary functions
gamma*: Public ordinary functions
gamma-p: Public ordinary functions
gamma-pdf: Public ordinary functions
gamma-pinv: Public ordinary functions
gamma-q: Public ordinary functions
gamma-qinv: Public ordinary functions
gaussian-p: Public ordinary functions
gaussian-pdf: Public ordinary functions
gaussian-pinv: Public ordinary functions
gaussian-q: Public ordinary functions
gaussian-qinv: Public ordinary functions
gaussian-tail-pdf: Public ordinary functions
gegenbauer: Public ordinary functions
gegenbauer-1: Public ordinary functions
gegenbauer-2: Public ordinary functions
gegenbauer-3: Public ordinary functions
gegenbauer-array: Public ordinary functions
generate-all-array-tests: Private macros
generate-all-array-tests-body: Private ordinary functions
generate-all-permutations: Private ordinary functions
generate-all-permutations-backwards: Private ordinary functions
generate-methods: Private ordinary functions
generate-nlls-data: Private ordinary functions
Generic Function, (setf column): Public generic functions
Generic Function, (setf parameter): Public generic functions
Generic Function, (setf row): Public generic functions
Generic Function, absolute-deviation: Public generic functions
Generic Function, absolute-sum: Public generic functions
Generic Function, alloc-from-block: Private generic functions
Generic Function, allocate: Private generic functions
Generic Function, autocorrelation: Public generic functions
Generic Function, axpy: Public generic functions
Generic Function, backward-discrete-fourier-transform: Public generic functions
Generic Function, backward-fourier-transform-dif-radix2: Private generic functions
Generic Function, backward-fourier-transform-halfcomplex-nonradix2: Private generic functions
Generic Function, backward-fourier-transform-halfcomplex-radix2: Private generic functions
Generic Function, backward-fourier-transform-nonradix2: Private generic functions
Generic Function, backward-fourier-transform-radix2: Private generic functions
Generic Function, blas-copy: Public generic functions
Generic Function, blas-swap: Public generic functions
Generic Function, callback-struct: Private generic functions
Generic Function, cbinfo: Private generic functions
Generic Function, cdot: Public generic functions
Generic Function, cholesky-decomposition: Public generic functions
Generic Function, cholesky-solve: Public generic functions
Generic Function, column: Public generic functions
Generic Function, conjugate-rank-1-update: Public generic functions
Generic Function, correlation: Public generic functions
Generic Function, covariance: Public generic functions
Generic Function, cylindrical-bessel-i: Public generic functions
Generic Function, cylindrical-bessel-i-scaled: Public generic functions
Generic Function, cylindrical-bessel-j: Public generic functions
Generic Function, cylindrical-bessel-k: Public generic functions
Generic Function, cylindrical-bessel-k-scaled: Public generic functions
Generic Function, cylindrical-bessel-y: Public generic functions
Generic Function, dilogarithm: Public generic functions
Generic Function, dimension-names: Private generic functions
Generic Function, discrete-fourier-transform: Public generic functions
Generic Function, eigenvalues: Public generic functions
Generic Function, eigenvalues-eigenvectors: Public generic functions
Generic Function, eigenvalues-eigenvectors-gensymm: Public generic functions
Generic Function, eigenvalues-gensymm: Public generic functions
Generic Function, elt*: Public generic functions
Generic Function, elt+: Public generic functions
Generic Function, elt-: Public generic functions
Generic Function, elt/: Public generic functions
Generic Function, equal-bins-p: Public generic functions
Generic Function, error-number: Private generic functions
Generic Function, error-text: Private generic functions
Generic Function, euclidean-norm: Public generic functions
Generic Function, evaluate: Public generic functions
Generic Function, evaluate-derivative: Public generic functions
Generic Function, evaluate-integral: Public generic functions
Generic Function, evaluate-second-derivative: Public generic functions
Generic Function, explanation: Private generic functions
Generic Function, fft-half-complex-radix2-unpack: Private generic functions
Generic Function, fft-half-complex-unpack: Private generic functions
Generic Function, fft-real-unpack: Private generic functions
Generic Function, forward-discrete-fourier-transform: Public generic functions
Generic Function, forward-fourier-transform-dif-radix2: Private generic functions
Generic Function, forward-fourier-transform-halfcomplex-nonradix2: Private generic functions
Generic Function, forward-fourier-transform-halfcomplex-radix2: Private generic functions
Generic Function, forward-fourier-transform-nonradix2: Private generic functions
Generic Function, forward-fourier-transform-radix2: Private generic functions
Generic Function, fourier-transform-dif-radix2: Private generic functions
Generic Function, fourier-transform-radix2: Private generic functions
Generic Function, funcallables: Private generic functions
Generic Function, function-value: Public generic functions
Generic Function, functions: Private generic functions
Generic Function, givens-rotation: Public generic functions
Generic Function, givens-rotation-m: Public generic functions
Generic Function, gsl-cos: Public generic functions
Generic Function, gsl-log: Public generic functions
Generic Function, gsl-name: Private generic functions
Generic Function, gsl-sin: Public generic functions
Generic Function, gsl-version: Private generic functions
Generic Function, hermitian-rank-1-update: Public generic functions
Generic Function, hermitian-rank-2-update: Public generic functions
Generic Function, hypergeometric-1f1: Public generic functions
Generic Function, hypergeometric-u: Public generic functions
Generic Function, hypergeometric-u-e10: Public generic functions
Generic Function, increment: Public generic functions
Generic Function, index-max: Public generic functions
Generic Function, inverse-discrete-fourier-transform: Public generic functions
Generic Function, inverse-fourier-transform-dif-radix2: Private generic functions
Generic Function, inverse-fourier-transform-halfcomplex-nonradix2: Private generic functions
Generic Function, inverse-fourier-transform-halfcomplex-radix2: Private generic functions
Generic Function, inverse-fourier-transform-nonradix2: Private generic functions
Generic Function, inverse-fourier-transform-radix2: Private generic functions
Generic Function, inverse-matrix-product: Public generic functions
Generic Function, iterate: Public generic functions
Generic Function, kurtosis: Public generic functions
Generic Function, last-step: Public generic functions
Generic Function, line-number: Private generic functions
Generic Function, lu-decomposition: Public generic functions
Generic Function, lu-determinant: Public generic functions
Generic Function, lu-invert: Public generic functions
Generic Function, lu-log-determinant: Public generic functions
Generic Function, lu-refine: Public generic functions
Generic Function, lu-sgndet: Public generic functions
Generic Function, lu-solve: Public generic functions
Generic Function, matrix-product: Public generic functions
Generic Function, matrix-product-hermitian: Public generic functions
Generic Function, matrix-product-symmetric: Public generic functions
Generic Function, matrix-product-triangular: Public generic functions
Generic Function, matrix-transpose: Public generic functions
Generic Function, matrix-transpose*: Public generic functions
Generic Function, max-index: Public generic functions
Generic Function, max-range: Public generic functions
Generic Function, mean: Public generic functions
Generic Function, median: Public generic functions
Generic Function, min-index: Public generic functions
Generic Function, min-range: Public generic functions
Generic Function, minimum-size: Public generic functions
Generic Function, minmax: Public generic functions
Generic Function, minmax-index: Public generic functions
Generic Function, mmax: Public generic functions
Generic Function, mmin: Public generic functions
Generic Function, mminusp: Public generic functions
Generic Function, modified-givens-rotation: Public generic functions
Generic Function, modified-givens-rotation-m: Public generic functions
Generic Function, mplusp: Public generic functions
Generic Function, mpointer: Private generic functions
Generic Function, msort: Public generic functions
Generic Function, mzerop: Public generic functions
Generic Function, name: Public generic functions
Generic Function, non-negative-p: Public generic functions
Generic Function, order: Public generic functions
Generic Function, parameter: Public generic functions
Generic Function, permute: Public generic functions
Generic Function, permute-inverse: Public generic functions
Generic Function, psi: Public generic functions
Generic Function, psi-1: Public generic functions
Generic Function, quantile: Public generic functions
Generic Function, range: Public generic functions
Generic Function, rank-1-update: Public generic functions
Generic Function, rng-state: Public generic functions
Generic Function, row: Public generic functions
Generic Function, sample: Public generic functions
Generic Function, scalarsp: Private generic functions
Generic Function, scale: Public generic functions
Generic Function, set-all: Public generic functions
Generic Function, set-basis: Public generic functions
Generic Function, set-identity: Public generic functions
Generic Function, set-ranges-uniform: Public generic functions
Generic Function, set-zero: Public generic functions
Generic Function, shift: Public generic functions
Generic Function, sigma: Public generic functions
Generic Function, size: Public generic functions
Generic Function, skewness: Public generic functions
Generic Function, solution: Public generic functions
Generic Function, sort-eigenvalues-eigenvectors: Public generic functions
Generic Function, sort-index: Public generic functions
Generic Function, sort-largest: Public generic functions
Generic Function, sort-largest-index: Public generic functions
Generic Function, sort-smallest: Public generic functions
Generic Function, sort-smallest-index: Public generic functions
Generic Function, sort-vector: Public generic functions
Generic Function, sort-vector-index: Public generic functions
Generic Function, sort-vector-largest: Public generic functions
Generic Function, sort-vector-largest-index: Public generic functions
Generic Function, sort-vector-smallest: Public generic functions
Generic Function, sort-vector-smallest-index: Public generic functions
Generic Function, source-file: Private generic functions
Generic Function, standard-deviation: Public generic functions
Generic Function, standard-deviation-with-fixed-mean: Public generic functions
Generic Function, sum: Public generic functions
Generic Function, swap: Public generic functions
Generic Function, swap-columns: Public generic functions
Generic Function, swap-elements: Public generic functions
Generic Function, swap-row-column: Public generic functions
Generic Function, swap-rows: Public generic functions
Generic Function, symmetric-rank-1-update: Public generic functions
Generic Function, symmetric-rank-2-update: Public generic functions
Generic Function, tridiagonal-decomposition: Public generic functions
Generic Function, tridiagonal-unpack: Public generic functions
Generic Function, tridiagonal-unpack-t: Public generic functions
Generic Function, validp: Public generic functions
Generic Function, variance: Public generic functions
Generic Function, variance-with-fixed-mean: Public generic functions
Generic Function, vector-reverse: Public generic functions
Generic Function, weighted-absolute-deviation: Public generic functions
Generic Function, weighted-kurtosis: Public generic functions
Generic Function, weighted-mean: Public generic functions
Generic Function, weighted-skewness: Public generic functions
Generic Function, weighted-standard-deviation: Public generic functions
Generic Function, weighted-standard-deviation-with-fixed-mean: Public generic functions
Generic Function, weighted-variance: Public generic functions
Generic Function, weighted-variance-with-fixed-mean: Public generic functions
Generic Function, zeta: Public generic functions
Generic Function, zeta-1: Public generic functions
geometric-p: Public ordinary functions
geometric-pdf: Public ordinary functions
geometric-q: Public ordinary functions
get-callbacks-for-class: Private ordinary functions
get-mcm-parameters: Private ordinary functions
get-mcv-parameters: Private ordinary functions
get-random-number: Public ordinary functions
givens-rotation: Public generic functions
givens-rotation: Public generic functions
givens-rotation: Public generic functions
givens-rotation-m: Public generic functions
givens-rotation-m: Public generic functions
givens-rotation-m: Public generic functions
greville-abscissa: Public ordinary functions
gsl-asinh: Public ordinary functions
gsl-atanh: Public ordinary functions
gsl-config-pathname: Private ordinary functions
gsl-cos: Public generic functions
gsl-cos: Public generic functions
gsl-cos: Public generic functions
gsl-exp: Public ordinary functions
gsl-log: Public generic functions
gsl-log: Public generic functions
gsl-log: Public generic functions
gsl-lookup: Public ordinary functions
gsl-name: Private generic functions
gsl-name: Private generic functions
gsl-random-state: Public ordinary functions
gsl-sin: Public generic functions
gsl-sin: Public generic functions
gsl-sin: Public generic functions
gsl-version: Private generic functions
gsl-version: Private generic functions
gumbel1-p: Public ordinary functions
gumbel1-pdf: Public ordinary functions
gumbel1-pinv: Public ordinary functions
gumbel1-q: Public ordinary functions
gumbel1-qinv: Public ordinary functions
gumbel2-p: Public ordinary functions
gumbel2-pdf: Public ordinary functions
gumbel2-pinv: Public ordinary functions
gumbel2-q: Public ordinary functions
gumbel2-qinv: Public ordinary functions

H
have-at-least-gsl-version: Private ordinary functions
hazard: Public ordinary functions
heapsort: Public ordinary functions
heapsort-index: Public ordinary functions
hermitian-rank-1-update: Public generic functions
hermitian-rank-1-update: Public generic functions
hermitian-rank-1-update: Public generic functions
hermitian-rank-1-update: Public generic functions
hermitian-rank-1-update: Public generic functions
hermitian-rank-2-update: Public generic functions
hermitian-rank-2-update: Public generic functions
hermitian-rank-2-update: Public generic functions
hermitian-rank-2-update: Public generic functions
hermitian-rank-2-update: Public generic functions
histo-clone: Private ordinary functions
histo-copy: Private ordinary functions
histo2d-clone: Private ordinary functions
histo2d-copy: Private ordinary functions
histogram-covariance: Public ordinary functions
histogram-find: Public ordinary functions
householder-hm: Public ordinary functions
householder-hv: Public ordinary functions
householder-mh: Public ordinary functions
householder-solve: Public ordinary functions
householder-transform: Public ordinary functions
hurwitz-zeta: Public ordinary functions
hydrogenicr: Public ordinary functions
hydrogenicr-1: Public ordinary functions
hypergeometric-0f1: Public ordinary functions
hypergeometric-1f1: Public generic functions
hypergeometric-1f1: Public generic functions
hypergeometric-1f1: Public generic functions
hypergeometric-2f0: Public ordinary functions
hypergeometric-2f1: Public ordinary functions
hypergeometric-2f1-conj: Public ordinary functions
hypergeometric-2f1-conj-renorm: Public ordinary functions
hypergeometric-2f1-renorm: Public ordinary functions
hypergeometric-p: Public ordinary functions
hypergeometric-pdf: Public ordinary functions
hypergeometric-q: Public ordinary functions
hypergeometric-u: Public generic functions
hypergeometric-u: Public generic functions
hypergeometric-u: Public generic functions
hypergeometric-u-e10: Public generic functions
hypergeometric-u-e10: Public generic functions
hypergeometric-u-e10: Public generic functions
hypotenuse: Public ordinary functions
hypotenuse*: Public ordinary functions

I
ieee754-sign-bit: Private ordinary functions
incomplete-beta: Public ordinary functions
incomplete-gamma: Public ordinary functions
increment: Public generic functions
increment: Public generic functions
increment: Public generic functions
index-max: Public generic functions
index-max: Public generic functions
index-max: Public generic functions
index-max: Public generic functions
index-max: Public generic functions
infinityp: Public ordinary functions
init-first: Public ordinary functions
init-last: Public ordinary functions
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-suffix-switched-foreign: Private ordinary functions
integer-as-float: Public ordinary functions
integral-chebyshev: Public ordinary functions
integrate-vanderpol: Private ordinary functions
integration-qag: Public ordinary functions
integration-qagi: Public ordinary functions
integration-qagil: Public ordinary functions
integration-qagiu: Public ordinary functions
integration-qagp: Public ordinary functions
integration-qags: Public ordinary functions
integration-qawc: Public ordinary functions
integration-qawf: Public ordinary functions
integration-qawo: Public ordinary functions
integration-qaws: Public ordinary functions
integration-qng: Public ordinary functions
integration-test-f1: Private ordinary functions
integration-test-f11: Private ordinary functions
integration-test-f15: Private ordinary functions
integration-test-f16: Private ordinary functions
integration-test-f3: Private ordinary functions
integration-test-f454: Private ordinary functions
integration-test-f455: Private ordinary functions
integration-test-f456: Private ordinary functions
integration-test-f457: Private ordinary functions
integration-test-f458: Private ordinary functions
integration-test-f459: Private ordinary functions
integration-test-myfn1: Private ordinary functions
integration-test-myfn2: Private ordinary functions
interpolation-search: Public ordinary functions
inverse-discrete-fourier-transform: Public generic functions
inverse-discrete-fourier-transform: Public generic functions
inverse-discrete-fourier-transform: Public generic functions
inverse-fourier-transform: Public ordinary functions
inverse-fourier-transform-dif-radix2: Private generic functions
inverse-fourier-transform-dif-radix2: Private generic functions
inverse-fourier-transform-dif-radix2: Private generic functions
inverse-fourier-transform-halfcomplex-nonradix2: Private generic functions
inverse-fourier-transform-halfcomplex-nonradix2: Private generic functions
inverse-fourier-transform-halfcomplex-nonradix2: Private generic functions
inverse-fourier-transform-halfcomplex-radix2: Private generic functions
inverse-fourier-transform-halfcomplex-radix2: Private generic functions
inverse-fourier-transform-halfcomplex-radix2: Private generic functions
inverse-fourier-transform-nonradix2: Private generic functions
inverse-fourier-transform-nonradix2: Private generic functions
inverse-fourier-transform-nonradix2: Private generic functions
inverse-fourier-transform-radix2: Private generic functions
inverse-fourier-transform-radix2: Private generic functions
inverse-fourier-transform-radix2: Private generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inverse-matrix-product: Public generic functions
inversions: Public ordinary functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions
iterate: Public generic functions

J
jacobian: Public ordinary functions
jacobian-elliptic-functions: Public ordinary functions

K
knots: Public ordinary functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions
kurtosis: Public generic functions

L
laguerre: Public ordinary functions
laguerre-1: Public ordinary functions
laguerre-2: Public ordinary functions
laguerre-3: Public ordinary functions
lambert-w0: Public ordinary functions
lambert-wm1: Public ordinary functions
landau-pdf: Public ordinary functions
laplace-p: Public ordinary functions
laplace-pdf: Public ordinary functions
laplace-pinv: Public ordinary functions
laplace-q: Public ordinary functions
laplace-qinv: Public ordinary functions
last-step: Public generic functions
last-step: Public generic functions
last-step: Public generic functions
last-step: Public generic functions
legendre-conicalp-0: Public ordinary functions
legendre-conicalp-1: Public ordinary functions
legendre-conicalp-half: Public ordinary functions
legendre-conicalp-mhalf: Public ordinary functions
legendre-h3d: Public ordinary functions
legendre-h3d-0: Public ordinary functions
legendre-h3d-1: Public ordinary functions
legendre-h3d-array: Public ordinary functions
legendre-p1: Public ordinary functions
legendre-p2: Public ordinary functions
legendre-p3: Public ordinary functions
legendre-pl: Public ordinary functions
legendre-pl-array: Public ordinary functions
legendre-pl-deriv-array: Public ordinary functions
legendre-plm: Public ordinary functions
legendre-q0: Public ordinary functions
legendre-q1: Public ordinary functions
legendre-ql: Public ordinary functions
legendre-regular-cylindrical-conical: Public ordinary functions
legendre-regular-spherical-conical: Public ordinary functions
legendre-sphplm: Public ordinary functions
levin-value: Private ordinary functions
limits-check: Private ordinary functions
line-number: Private generic functions
line-number: Private generic functions
linear-cycles: Public ordinary functions
linear-estimate: Public ordinary functions
linear-fit: Public ordinary functions
linear-least-squares-multivariate-example: Private ordinary functions
linear-least-squares-univariate-example: Private ordinary functions
linear-mfit: Public ordinary functions
linear-mfit-nosvd: Private ordinary functions
linear-mfit-svd: Private ordinary functions
linear-to-canonical: Public ordinary functions
log+1: Public ordinary functions
log-1+x: Public ordinary functions
log-1+x-m1: Public ordinary functions
log-abs: Public ordinary functions
log-beta: Public ordinary functions
log-choose: Public ordinary functions
log-cosh: Public ordinary functions
log-double-factorial: Public ordinary functions
log-erfc: Public ordinary functions
log-factorial: Public ordinary functions
log-gamma: Public ordinary functions
log-gamma-complex: Public ordinary functions
log-gamma-sign: Public ordinary functions
log-modulus: Public ordinary functions
log-pochammer: Public ordinary functions
log-pochammer-sign: Public ordinary functions
log-sin: Public ordinary functions
log-sinh: Public ordinary functions
logarithmic-pdf: Public ordinary functions
logistic-p: Public ordinary functions
logistic-pdf: Public ordinary functions
logistic-pinv: Public ordinary functions
logistic-q: Public ordinary functions
logistic-qinv: Public ordinary functions
lognormal-p: Public ordinary functions
lognormal-pdf: Public ordinary functions
lognormal-pinv: Public ordinary functions
lognormal-q: Public ordinary functions
lognormal-qinv: Public ordinary functions
lookup-condition: Private ordinary functions
ls-covariance: Public ordinary functions
lu-decomposition: Public generic functions
lu-decomposition: Public generic functions
lu-decomposition: Public generic functions
lu-determinant: Public generic functions
lu-determinant: Public generic functions
lu-determinant: Public generic functions
lu-invert: Public generic functions
lu-invert: Public generic functions
lu-invert: Public generic functions
lu-log-determinant: Public generic functions
lu-log-determinant: Public generic functions
lu-log-determinant: Public generic functions
lu-refine: Public generic functions
lu-refine: Public generic functions
lu-refine: Public generic functions
lu-sgndet: Public generic functions
lu-sgndet: Public generic functions
lu-sgndet: Public generic functions
lu-solve: Public generic functions
lu-solve: Public generic functions
lu-solve: Public generic functions

M
Macro, all-fft-test-forms: Private macros
Macro, assert-neginf: Private macros
Macro, assert-posinf: Private macros
Macro, assert-sf-scale: Private macros
Macro, assert-to-tolerance: Private macros
Macro, def-ci-subclass: Private macros
Macro, def-ci-subclass-1d: Private macros
Macro, def-rng-type: Private macros
Macro, defcomparison: Private macros
Macro, define-gsl-condition: Private macros
Macro, defmcallback: Private macros
Macro, defmfun: Private macros
Macro, defmobject: Private macros
Macro, defmpar: Private macros
Macro, fft-complex-result-check: Private macros
Macro, fft-real-result-check: Private macros
Macro, foreign-pointer-method: Private macros
Macro, generate-all-array-tests: Private macros
Macro, maref: Public macros
Macro, pmnil: Private macros
Macro, return-value-on-error: Public macros
Macro, save-test: Private macros
Macro, set-maref: Private macros
Macro, with-defmfun-key-args: Private macros
Macro, with-fourier-transform-environment: Public macros
Macro, with-ode-integration: Public macros
make-acceleration: Public ordinary functions
make-and-init-vector: Private ordinary functions
make-basis-spline: Public ordinary functions
make-cbstruct: Private ordinary functions
make-cbstruct-object: Private ordinary functions
make-chebyshev: Public ordinary functions
make-combination: Public ordinary functions
make-compiled-funcallable: Private ordinary functions
make-defmcallbacks: Private ordinary functions
make-discrete-random: Public ordinary functions
make-eigen-gen: Public ordinary functions
make-eigen-genherm: Public ordinary functions
make-eigen-genhermv: Public ordinary functions
make-eigen-gensymm: Public ordinary functions
make-eigen-gensymmv: Public ordinary functions
make-eigen-genv: Public ordinary functions
make-eigen-herm: Public ordinary functions
make-eigen-hermv: Public ordinary functions
make-eigen-nonsymm: Public ordinary functions
make-eigen-nonsymmv: Public ordinary functions
make-eigen-symm: Public ordinary functions
make-eigen-symmv: Public ordinary functions
make-exponent-fit-data: Private ordinary functions
make-fft-complex-wavetable-double-float: Private ordinary functions
make-fft-complex-wavetable-single-float: Private ordinary functions
make-fft-complex-workspace-double-float: Private ordinary functions
make-fft-complex-workspace-single-float: Private ordinary functions
make-fft-half-complex-wavetable-double-float: Private ordinary functions
make-fft-half-complex-wavetable-single-float: Private ordinary functions
make-fft-real-wavetable-double-float: Private ordinary functions
make-fft-real-wavetable-single-float: Private ordinary functions
make-fft-real-workspace-double-float: Private ordinary functions
make-fft-real-workspace-single-float: Private ordinary functions
make-fft-wavetable: Public ordinary functions
make-fft-workspace: Public ordinary functions
make-fit-workspace: Public ordinary functions
make-foreign-array-from-mpointer: Private ordinary functions
make-funcallable-form: Private ordinary functions
make-funcallables-for-object: Private ordinary functions
make-gsl-metadata: Private ordinary functions
make-hankel: Public ordinary functions
make-histogram: Public ordinary functions
make-histogram-pdf: Public ordinary functions
make-histogram2d: Public ordinary functions
make-histogram2d-pdf: Public ordinary functions
make-initialize-instance: Private ordinary functions
make-integration-workspace: Public ordinary functions
make-interpolation: Public ordinary functions
make-jacobian-matrix: Public ordinary functions
make-levin: Public ordinary functions
make-levin-truncated: Public ordinary functions
make-list-from-pool: Private ordinary functions
make-mathieu: Public ordinary functions
make-mobject-defmcallbacks: Private ordinary functions
make-monte-carlo-miser: Public ordinary functions
make-monte-carlo-plain: Public ordinary functions
make-monte-carlo-vegas: Public ordinary functions
make-multi-dimensional-minimizer-f: Public ordinary functions
make-multi-dimensional-minimizer-fdf: Public ordinary functions
make-multi-dimensional-root-solver-f: Public ordinary functions
make-multi-dimensional-root-solver-fdf: Public ordinary functions
make-new-sa-state: Private ordinary functions
make-nonlinear-fdffit: Public ordinary functions
make-nonlinear-ffit: Public ordinary functions
make-ntuple-example-data: Private ordinary functions
make-ode-evolution: Public ordinary functions
make-ode-stepper: Public ordinary functions
make-one-dimensional-minimizer: Public ordinary functions
make-one-dimensional-root-solver-f: Public ordinary functions
make-one-dimensional-root-solver-fdf: Public ordinary functions
make-permutation: Public ordinary functions
make-polynomial-complex-workspace: Public ordinary functions
make-qawo-table: Public ordinary functions
make-qaws-table: Public ordinary functions
make-quasi-random-number-generator: Public ordinary functions
make-random-number-generator: Public ordinary functions
make-reinitialize-instance: Private ordinary functions
make-sa-states: Private ordinary functions
make-scaled-control: Public ordinary functions
make-spline: Public ordinary functions
make-standard-control: Public ordinary functions
make-symbol-cardinal: Private ordinary functions
make-symbol-cardinals: Private ordinary functions
make-urand-vector: Private ordinary functions
make-wavelet: Public ordinary functions
make-wavelet-workspace: Public ordinary functions
make-y-control: Public ordinary functions
make-yp-control: Public ordinary functions
map-name: Private ordinary functions
mappend: Private ordinary functions
maref: Public macros
mathieu-a: Public ordinary functions
mathieu-a-array: Public ordinary functions
mathieu-b: Public ordinary functions
mathieu-b-array: Public ordinary functions
mathieu-ce: Public ordinary functions
mathieu-ce-array: Public ordinary functions
mathieu-mc: Public ordinary functions
mathieu-mc-array: Public ordinary functions
mathieu-ms: Public ordinary functions
mathieu-ms-array: Public ordinary functions
mathieu-se: Public ordinary functions
mathieu-se-array: Public ordinary functions
matrix-exponential: Public ordinary functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product: Public generic functions
matrix-product-dimensions: Private ordinary functions
matrix-product-hermitian: Public generic functions
matrix-product-hermitian: Public generic functions
matrix-product-hermitian: Public generic functions
matrix-product-hermitian: Public generic functions
matrix-product-hermitian: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-symmetric: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-product-triangular: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
matrix-transpose*: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-index: Public generic functions
max-range: Public generic functions
max-range: Public generic functions
max-range: Public generic functions
mcrw: Private ordinary functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean: Public generic functions
mean-2x: Private ordinary functions
mean-2y: Private ordinary functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
median: Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf column): Public generic functions
Method, (setf parameter): Public generic functions
Method, (setf parameter): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, (setf row): Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-deviation: Public generic functions
Method, absolute-sum: Public generic functions
Method, absolute-sum: Public generic functions
Method, absolute-sum: Public generic functions
Method, absolute-sum: Public generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, alloc-from-block: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, allocate: Private generic functions
Method, aref: Public standalone methods
Method, aref: Public standalone methods
Method, aref: Public standalone methods
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, autocorrelation: Public generic functions
Method, axpy: Public generic functions
Method, axpy: Public generic functions
Method, axpy: Public generic functions
Method, axpy: Public generic functions
Method, backward-discrete-fourier-transform: Public generic functions
Method, backward-discrete-fourier-transform: Public generic functions
Method, backward-fourier-transform-dif-radix2: Private generic functions
Method, backward-fourier-transform-dif-radix2: Private generic functions
Method, backward-fourier-transform-halfcomplex-nonradix2: Private generic functions
Method, backward-fourier-transform-halfcomplex-nonradix2: Private generic functions
Method, backward-fourier-transform-halfcomplex-radix2: Private generic functions
Method, backward-fourier-transform-halfcomplex-radix2: Private generic functions
Method, backward-fourier-transform-nonradix2: Private generic functions
Method, backward-fourier-transform-nonradix2: Private generic functions
Method, backward-fourier-transform-radix2: Private generic functions
Method, backward-fourier-transform-radix2: Private generic functions
Method, blas-copy: Public generic functions
Method, blas-copy: Public generic functions
Method, blas-copy: Public generic functions
Method, blas-copy: Public generic functions
Method, blas-swap: Public generic functions
Method, blas-swap: Public generic functions
Method, blas-swap: Public generic functions
Method, blas-swap: Public generic functions
Method, callback-struct: Private generic functions
Method, cbinfo: Private generic functions
Method, cdot: Public generic functions
Method, cdot: Public generic functions
Method, cholesky-decomposition: Public generic functions
Method, cholesky-decomposition: Public generic functions
Method, cholesky-solve: Public generic functions
Method, cholesky-solve: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, column: Public generic functions
Method, conjugate-rank-1-update: Public generic functions
Method, conjugate-rank-1-update: Public generic functions
Method, copy: Public standalone methods
Method, copy: Public standalone methods
Method, copy: Public standalone methods
Method, copy: Public standalone methods
Method, copy: Public standalone methods
Method, copy: Public standalone methods
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, correlation: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, covariance: Public generic functions
Method, cylindrical-bessel-i: Public generic functions
Method, cylindrical-bessel-i: Public generic functions
Method, cylindrical-bessel-i-scaled: Public generic functions
Method, cylindrical-bessel-i-scaled: Public generic functions
Method, cylindrical-bessel-j: Public generic functions
Method, cylindrical-bessel-j: Public generic functions
Method, cylindrical-bessel-k: Public generic functions
Method, cylindrical-bessel-k: Public generic functions
Method, cylindrical-bessel-k-scaled: Public generic functions
Method, cylindrical-bessel-k-scaled: Public generic functions
Method, cylindrical-bessel-y: Public generic functions
Method, cylindrical-bessel-y: Public generic functions
Method, dilogarithm: Public generic functions
Method, dilogarithm: Public generic functions
Method, dimension-names: Private generic functions
Method, dimensions: Public standalone methods
Method, dimensions: Public standalone methods
Method, dimensions: Public standalone methods
Method, dimensions: Public standalone methods
Method, discrete-fourier-transform: Public generic functions
Method, discrete-fourier-transform: Public generic functions
Method, eigenvalues: Public generic functions
Method, eigenvalues: Public generic functions
Method, eigenvalues-eigenvectors: Public generic functions
Method, eigenvalues-eigenvectors: Public generic functions
Method, eigenvalues-eigenvectors-gensymm: Public generic functions
Method, eigenvalues-eigenvectors-gensymm: Public generic functions
Method, eigenvalues-gensymm: Public generic functions
Method, eigenvalues-gensymm: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt*: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt+: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt-: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, elt/: Public generic functions
Method, equal-bins-p: Public generic functions
Method, equal-bins-p: Public generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-number: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, error-text: Private generic functions
Method, euclidean-norm: Public generic functions
Method, euclidean-norm: Public generic functions
Method, euclidean-norm: Public generic functions
Method, euclidean-norm: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate: Public generic functions
Method, evaluate-derivative: Public generic functions
Method, evaluate-derivative: Public generic functions
Method, evaluate-integral: Public generic functions
Method, evaluate-integral: Public generic functions
Method, evaluate-second-derivative: Public generic functions
Method, evaluate-second-derivative: Public generic functions
Method, explanation: Private generic functions
Method, fft-half-complex-radix2-unpack: Private generic functions
Method, fft-half-complex-radix2-unpack: Private generic functions
Method, fft-half-complex-unpack: Private generic functions
Method, fft-half-complex-unpack: Private generic functions
Method, fft-real-unpack: Private generic functions
Method, fft-real-unpack: Private generic functions
Method, forward-discrete-fourier-transform: Public generic functions
Method, forward-discrete-fourier-transform: Public generic functions
Method, forward-fourier-transform-dif-radix2: Private generic functions
Method, forward-fourier-transform-dif-radix2: Private generic functions
Method, forward-fourier-transform-halfcomplex-nonradix2: Private generic functions
Method, forward-fourier-transform-halfcomplex-nonradix2: Private generic functions
Method, forward-fourier-transform-halfcomplex-radix2: Private generic functions
Method, forward-fourier-transform-halfcomplex-radix2: Private generic functions
Method, forward-fourier-transform-nonradix2: Private generic functions
Method, forward-fourier-transform-nonradix2: Private generic functions
Method, forward-fourier-transform-nonradix2: Private generic functions
Method, forward-fourier-transform-nonradix2: Private generic functions
Method, forward-fourier-transform-radix2: Private generic functions
Method, forward-fourier-transform-radix2: Private generic functions
Method, forward-fourier-transform-radix2: Private generic functions
Method, forward-fourier-transform-radix2: Private generic functions
Method, fourier-transform-dif-radix2: Private generic functions
Method, fourier-transform-dif-radix2: Private generic functions
Method, fourier-transform-radix2: Private generic functions
Method, fourier-transform-radix2: Private generic functions
Method, funcallables: Private generic functions
Method, function-value: Public generic functions
Method, function-value: Public generic functions
Method, function-value: Public generic functions
Method, function-value: Public generic functions
Method, function-value: Public generic functions
Method, function-value: Public generic functions
Method, functions: Private generic functions
Method, givens-rotation: Public generic functions
Method, givens-rotation: Public generic functions
Method, givens-rotation-m: Public generic functions
Method, givens-rotation-m: Public generic functions
Method, gsl-cos: Public generic functions
Method, gsl-cos: Public generic functions
Method, gsl-log: Public generic functions
Method, gsl-log: Public generic functions
Method, gsl-name: Private generic functions
Method, gsl-sin: Public generic functions
Method, gsl-sin: Public generic functions
Method, gsl-version: Private generic functions
Method, hermitian-rank-1-update: Public generic functions
Method, hermitian-rank-1-update: Public generic functions
Method, hermitian-rank-1-update: Public generic functions
Method, hermitian-rank-1-update: Public generic functions
Method, hermitian-rank-2-update: Public generic functions
Method, hermitian-rank-2-update: Public generic functions
Method, hermitian-rank-2-update: Public generic functions
Method, hermitian-rank-2-update: Public generic functions
Method, hypergeometric-1f1: Public generic functions
Method, hypergeometric-1f1: Public generic functions
Method, hypergeometric-u: Public generic functions
Method, hypergeometric-u: Public generic functions
Method, hypergeometric-u-e10: Public generic functions
Method, hypergeometric-u-e10: Public generic functions
Method, increment: Public generic functions
Method, increment: Public generic functions
Method, index-max: Public generic functions
Method, index-max: Public generic functions
Method, index-max: Public generic functions
Method, index-max: Public generic functions
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, inverse-discrete-fourier-transform: Public generic functions
Method, inverse-discrete-fourier-transform: Public generic functions
Method, inverse-fourier-transform-dif-radix2: Private generic functions
Method, inverse-fourier-transform-dif-radix2: Private generic functions
Method, inverse-fourier-transform-halfcomplex-nonradix2: Private generic functions
Method, inverse-fourier-transform-halfcomplex-nonradix2: Private generic functions
Method, inverse-fourier-transform-halfcomplex-radix2: Private generic functions
Method, inverse-fourier-transform-halfcomplex-radix2: Private generic functions
Method, inverse-fourier-transform-nonradix2: Private generic functions
Method, inverse-fourier-transform-nonradix2: Private generic functions
Method, inverse-fourier-transform-radix2: Private generic functions
Method, inverse-fourier-transform-radix2: Private generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, inverse-matrix-product: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, iterate: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, kurtosis: Public generic functions
Method, last-step: Public generic functions
Method, last-step: Public generic functions
Method, last-step: Public generic functions
Method, line-number: Private generic functions
Method, lu-decomposition: Public generic functions
Method, lu-decomposition: Public generic functions
Method, lu-determinant: Public generic functions
Method, lu-determinant: Public generic functions
Method, lu-invert: Public generic functions
Method, lu-invert: Public generic functions
Method, lu-log-determinant: Public generic functions
Method, lu-log-determinant: Public generic functions
Method, lu-refine: Public generic functions
Method, lu-refine: Public generic functions
Method, lu-sgndet: Public generic functions
Method, lu-sgndet: Public generic functions
Method, lu-solve: Public generic functions
Method, lu-solve: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product: Public generic functions
Method, matrix-product-hermitian: Public generic functions
Method, matrix-product-hermitian: Public generic functions
Method, matrix-product-hermitian: Public generic functions
Method, matrix-product-hermitian: Public generic functions
Method, matrix-product-symmetric: Public generic functions
Method, matrix-product-symmetric: Public generic functions
Method, matrix-product-symmetric: Public generic functions
Method, matrix-product-symmetric: Public generic functions
Method, matrix-product-symmetric: Public generic functions
Method, matrix-product-symmetric: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-product-triangular: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, matrix-transpose*: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-index: Public generic functions
Method, max-range: Public generic functions
Method, max-range: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, mean: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, median: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-index: Public generic functions
Method, min-range: Public generic functions
Method, min-range: Public generic functions
Method, minimum-size: Public generic functions
Method, minimum-size: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, minmax-index: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmax: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mmin: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, mminusp: Public generic functions
Method, modified-givens-rotation: Public generic functions
Method, modified-givens-rotation: Public generic functions
Method, modified-givens-rotation-m: Public generic functions
Method, modified-givens-rotation-m: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mplusp: Public generic functions
Method, mpointer: Private generic functions
Method, mpointer: Private generic functions
Method, mpointer: Private generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, msort: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, mzerop: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, name: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, non-negative-p: Public generic functions
Method, order: Public generic functions
Method, order: Public generic functions
Method, parameter: Public generic functions
Method, parameter: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, permute-inverse: Public generic functions
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, psi: Public generic functions
Method, psi: Public generic functions
Method, psi-1: Public generic functions
Method, psi-1: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, quantile: Public generic functions
Method, range: Public generic functions
Method, range: Public generic functions
Method, rank-1-update: Public generic functions
Method, rank-1-update: Public generic functions
Method, rank-1-update: Public generic functions
Method, rank-1-update: Public generic functions
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, reinitialize-instance: Public standalone methods
Method, rng-state: Public generic functions
Method, rng-state: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, row: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, sample: Public generic functions
Method, scalarsp: Private generic functions
Method, scale: Public generic functions
Method, scale: Public generic functions
Method, scale: Public generic functions
Method, scale: Public generic functions
Method, scale: Public generic functions
Method, scale: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-all: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-basis: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-identity: Public generic functions
Method, set-ranges-uniform: Public generic functions
Method, set-ranges-uniform: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, set-zero: Public generic functions
Method, shift: Public generic functions
Method, shift: Public generic functions
Method, sigma: Public generic functions
Method, sigma: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, size: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, skewness: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, solution: Public generic functions
Method, sort-eigenvalues-eigenvectors: Public generic functions
Method, sort-eigenvalues-eigenvectors: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-index: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-largest-index: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-smallest-index: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-index: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-largest-index: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, sort-vector-smallest-index: Public generic functions
Method, source-file: Private generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, standard-deviation-with-fixed-mean: Public generic functions
Method, sum: Public generic functions
Method, sum: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-columns: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-elements: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-row-column: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, swap-rows: Public generic functions
Method, symmetric-rank-1-update: Public generic functions
Method, symmetric-rank-1-update: Public generic functions
Method, symmetric-rank-1-update: Public generic functions
Method, symmetric-rank-1-update: Public generic functions
Method, symmetric-rank-1-update: Public generic functions
Method, symmetric-rank-1-update: Public generic functions
Method, symmetric-rank-2-update: Public generic functions
Method, symmetric-rank-2-update: Public generic functions
Method, symmetric-rank-2-update: Public generic functions
Method, symmetric-rank-2-update: Public generic functions
Method, symmetric-rank-2-update: Public generic functions
Method, symmetric-rank-2-update: Public generic functions
Method, tridiagonal-decomposition: Public generic functions
Method, tridiagonal-decomposition: Public generic functions
Method, tridiagonal-unpack: Public generic functions
Method, tridiagonal-unpack: Public generic functions
Method, tridiagonal-unpack-t: Public generic functions
Method, tridiagonal-unpack-t: Public generic functions
Method, validp: Public generic functions
Method, validp: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, variance-with-fixed-mean: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, vector-reverse: Public generic functions
Method, weighted-absolute-deviation: Public generic functions
Method, weighted-absolute-deviation: Public generic functions
Method, weighted-kurtosis: Public generic functions
Method, weighted-kurtosis: Public generic functions
Method, weighted-mean: Public generic functions
Method, weighted-mean: Public generic functions
Method, weighted-mean: Public generic functions
Method, weighted-mean: Public generic functions
Method, weighted-skewness: Public generic functions
Method, weighted-skewness: Public generic functions
Method, weighted-standard-deviation: Public generic functions
Method, weighted-standard-deviation: Public generic functions
Method, weighted-standard-deviation: Public generic functions
Method, weighted-standard-deviation: Public generic functions
Method, weighted-standard-deviation-with-fixed-mean: Public generic functions
Method, weighted-standard-deviation-with-fixed-mean: Public generic functions
Method, weighted-standard-deviation-with-fixed-mean: Public generic functions
Method, weighted-standard-deviation-with-fixed-mean: Public generic functions
Method, weighted-variance: Public generic functions
Method, weighted-variance: Public generic functions
Method, weighted-variance: Public generic functions
Method, weighted-variance: Public generic functions
Method, weighted-variance-with-fixed-mean: Public generic functions
Method, weighted-variance-with-fixed-mean: Public generic functions
Method, weighted-variance-with-fixed-mean: Public generic functions
Method, weighted-variance-with-fixed-mean: Public generic functions
Method, zeta: Public generic functions
Method, zeta: Public generic functions
Method, zeta-1: Public generic functions
Method, zeta-1: Public generic functions
mfdfminimizer-gradient: Public ordinary functions
mfdfminimizer-restart: Public ordinary functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-index: Public generic functions
min-range: Public generic functions
min-range: Public generic functions
min-range: Public generic functions
min-test-gradient: Public ordinary functions
min-test-interval: Public ordinary functions
min-test-size: Public ordinary functions
minimization-one-example: Private ordinary functions
minimum-size: Public generic functions
minimum-size: Public generic functions
minimum-size: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
minmax-index: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmax: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mmin: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mminusp: Public generic functions
mobject-cbvname: Private ordinary functions
mobject-cbvnames: Private ordinary functions
mobject-fnvname: Private ordinary functions
mobject-fnvnames: Private ordinary functions
mobject-maker: Private ordinary functions
mobject-variable-name: Private ordinary functions
modified-givens-rotation: Public generic functions
modified-givens-rotation: Public generic functions
modified-givens-rotation: Public generic functions
modified-givens-rotation-m: Public generic functions
modified-givens-rotation-m: Public generic functions
modified-givens-rotation-m: Public generic functions
modulus: Public ordinary functions
modulus2: Public ordinary functions
monte-carlo-integrate-miser: Public ordinary functions
monte-carlo-integrate-plain: Public ordinary functions
monte-carlo-integrate-vegas: Public ordinary functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mplusp: Public generic functions
mpointer: Private generic functions
mpointer: Private generic functions
mpointer: Private generic functions
mpointer: Private generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
msort: Public generic functions
multi-linear-estimate: Public ordinary functions
multi-linear-residuals: Public ordinary functions
multimin-example-derivative: Private ordinary functions
multimin-example-derivative-scalars: Private ordinary functions
multimin-example-no-derivative: Private ordinary functions
multinomial-log-pdf: Public ordinary functions
multinomial-pdf: Public ordinary functions
multiplier-estimate: Public ordinary functions
multiplier-fit: Public ordinary functions
multiply: Public ordinary functions
multiply-err: Public ordinary functions
multiroot-slot: Private ordinary functions
multiroot-test-delta: Public ordinary functions
multiroot-test-residual: Public ordinary functions
mv-linear-least-squares-data: Private ordinary functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions
mzerop: Public generic functions

N
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
name: Public generic functions
nanp: Public ordinary functions
negative-binomial-p: Public ordinary functions
negative-binomial-pdf: Public ordinary functions
negative-binomial-q: Public ordinary functions
next-float: Private ordinary functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
non-negative-p: Public generic functions
nonlinear-least-squares-example: Private ordinary functions
nonnormalized-incomplete-gamma: Public ordinary functions
norm-f: Private ordinary functions
ntuple-example-histogramming: Private ordinary functions
ntuple-example-make-read: Private ordinary functions
ntuple-example-read: Private ordinary functions
ntuple-example-sel-func: Private ordinary functions
ntuple-example-val-func: Private ordinary functions
ntuple-example-values: Private ordinary functions
number-of-breakpoints: Public ordinary functions
number-of-callbacks: Private ordinary functions
number-of-coefficients: Public ordinary functions

O
open-ntuple: Public ordinary functions
optional-args-to-switch-gsl-functions: Private ordinary functions
order: Public generic functions
order: Public generic functions
order: Public generic functions

P
paraboloid-and-derivative: Private ordinary functions
paraboloid-and-derivative-scalar: Private ordinary functions
paraboloid-derivative: Private ordinary functions
paraboloid-derivative-scalar: Private ordinary functions
paraboloid-scalar: Private ordinary functions
paraboloid-vector: Private ordinary functions
parameter: Public generic functions
parameter: Public generic functions
parameter: Public generic functions
pareto-p: Public ordinary functions
pareto-pdf: Public ordinary functions
pareto-pinv: Public ordinary functions
pareto-q: Public ordinary functions
pareto-qinv: Public ordinary functions
parse-callback-argspec: Private ordinary functions
parse-callback-fnspec: Private ordinary functions
parse-callback-static: Private ordinary functions
pascal-p: Public ordinary functions
pascal-pdf: Public ordinary functions
pascal-q: Public ordinary functions
perm-copy: Private ordinary functions
permutation*: Public ordinary functions
permutation-data: Public ordinary functions
permutation-inverse: Public ordinary functions
permutation-next: Public ordinary functions
permutation-previous: Public ordinary functions
permutation-reverse: Public ordinary functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
permute-inverse: Public generic functions
plural-symbol: Private ordinary functions
pmnil: Private macros
pochammer: Public ordinary functions
poisson-p: Public ordinary functions
poisson-pdf: Public ordinary functions
poisson-q: Public ordinary functions
polar-to-rectangular: Public ordinary functions
polynomial-solve: Public ordinary functions
pow: Public ordinary functions
powell: Private ordinary functions
power-of-2-p: Private ordinary functions
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
project-ntuple: Public ordinary functions
psi: Public generic functions
psi: Public generic functions
psi: Public generic functions
psi-1: Public generic functions
psi-1: Public generic functions
psi-1: Public generic functions
psi-1+iy: Public ordinary functions
psi-n: Public ordinary functions

Q
qr-decomposition: Public ordinary functions
qr-qrsolve: Public ordinary functions
qr-qtvector: Public ordinary functions
qr-qvector: Public ordinary functions
qr-rsolve: Public ordinary functions
qr-solve: Public ordinary functions
qr-solve-least-squares: Public ordinary functions
qr-unpack: Public ordinary functions
qr-update: Public ordinary functions
qrng-get: Public ordinary functions
qrpt-decomposition: Public ordinary functions
qrpt-decomposition*: Public ordinary functions
qrpt-qrsolve: Public ordinary functions
qrpt-rsolve: Public ordinary functions
qrpt-solve: Public ordinary functions
qrpt-update: Public ordinary functions
quadratic: Private ordinary functions
quadratic-and-derivative: Private ordinary functions
quadratic-derivative: Private ordinary functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quantile: Public generic functions
quasi-clone: Private ordinary functions
quasi-copy: Private ordinary functions

R
r-solve: Public ordinary functions
random-walk-miser-example: Private ordinary functions
random-walk-plain-example: Private ordinary functions
random-walk-vegas-example: Private ordinary functions
range: Public generic functions
range: Public generic functions
range: Public generic functions
rank-1-update: Public generic functions
rank-1-update: Public generic functions
rank-1-update: Public generic functions
rank-1-update: Public generic functions
rank-1-update: Public generic functions
rayleigh-p: Public ordinary functions
rayleigh-pdf: Public ordinary functions
rayleigh-pinv: Public ordinary functions
rayleigh-q: Public ordinary functions
rayleigh-qinv: Public ordinary functions
rayleigh-tail-pdf: Public ordinary functions
read-ntuple: Public ordinary functions
realpart-vector: Private ordinary functions
record-callbacks-for-class: Private ordinary functions
rectangular-to-polar: Public ordinary functions
reference-foreign-element: Private ordinary functions
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
reinitialize-instance: Public standalone methods
relative-pochammer: Public ordinary functions
reset-urand: Private ordinary functions
restrict-positive: Public ordinary functions
restrict-symmetric: Public ordinary functions
return-value-on-error: Public macros
rng-clone: Private ordinary functions
rng-copy: Private ordinary functions
rng-environment-setup: Public ordinary functions
rng-max: Public ordinary functions
rng-min: Public ordinary functions
rng-state: Public generic functions
rng-state: Public generic functions
rng-state: Public generic functions
rng-types-setup: Private ordinary functions
root-test-delta: Public ordinary functions
root-test-interval: Public ordinary functions
root-test-residual: Public ordinary functions
roots-multi-example-derivative: Private ordinary functions
roots-multi-example-no-derivative: Private ordinary functions
roots-one-example-derivative: Private ordinary functions
roots-one-example-no-derivative: Private ordinary functions
rosenbrock: Private ordinary functions
rosenbrock-df: Private ordinary functions
rosenbrock-fdf: Private ordinary functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions
row: Public generic functions

S
sa-state-value: Private ordinary functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample: Public generic functions
sample-k-hankel: Public ordinary functions
sample-x-hankel: Public ordinary functions
save-test: Private macros
scalar-default: Private ordinary functions
scalarsp: Private generic functions
scalarsp: Private generic functions
scale: Public generic functions
scale: Public generic functions
scale: Public generic functions
scale: Public generic functions
scale: Public generic functions
scale: Public generic functions
scale: Public generic functions
sdot: Public ordinary functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-all: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-basis: Public generic functions
set-cbstruct: Private ordinary functions
set-floating-point-modes: Public ordinary functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-identity: Public generic functions
set-maref: Private macros
set-mcm-parameters: Private ordinary functions
set-mcv-parameters: Private ordinary functions
set-parameters: Private ordinary functions
set-parameters-gen: Private ordinary functions
set-parameters-nonsymmetric: Private ordinary functions
set-ranges-uniform: Public generic functions
set-ranges-uniform: Public generic functions
set-ranges-uniform: Public generic functions
set-slot-function: Private ordinary functions
set-structure-slot: Private ordinary functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
set-zero: Public generic functions
Setf Expander, (setf maref): Public setf expanders
sf-check-results: Private ordinary functions
sf-check-single: Private ordinary functions
sf-frac-diff: Private ordinary functions
shi: Public ordinary functions
shift: Public generic functions
shift: Public generic functions
shift: Public generic functions
si: Public ordinary functions
sigma: Public generic functions
sigma: Public generic functions
sigma: Public generic functions
sigma-2x: Private ordinary functions
sigma-2y: Private ordinary functions
signal-gsl-error: Private ordinary functions
signal-gsl-warning: Private ordinary functions
simulated-annealing: Public ordinary functions
simulated-annealing-example: Private ordinary functions
simulated-annealing-int: Private ordinary functions
simulated-annealing-test: Private ordinary functions
sin-err: Public ordinary functions
sinc: Public ordinary functions
singular-symbol: Private ordinary functions
singularize: Private ordinary functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size: Public generic functions
size-array: Private ordinary functions
size-vector-scalar: Private ordinary functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
skewness: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solution: Public generic functions
solve-cubic: Public ordinary functions
solve-cubic-complex: Public ordinary functions
solve-cyclic-tridiagonal: Public ordinary functions
solve-quadratic: Public ordinary functions
solve-quadratic-complex: Public ordinary functions
solve-symmetric-cyclic-tridiagonal: Public ordinary functions
solve-symmetric-tridiagonal: Public ordinary functions
solve-tridiagonal: Public ordinary functions
solve-tridiagonal-example: Private ordinary functions
sort-eigenvalues-eigenvectors: Public generic functions
sort-eigenvalues-eigenvectors: Public generic functions
sort-eigenvalues-eigenvectors: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-index: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-largest-index: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-smallest-index: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-index: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-largest-index: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
sort-vector-smallest-index: Public generic functions
source-file: Private generic functions
source-file: Private generic functions
spherical-bessel-i0-scaled: Public ordinary functions
spherical-bessel-i1-scaled: Public ordinary functions
spherical-bessel-i2-scaled: Public ordinary functions
spherical-bessel-il-scaled: Public ordinary functions
spherical-bessel-il-scaled-array: Public ordinary functions
spherical-bessel-j0: Public ordinary functions
spherical-bessel-j1: Public ordinary functions
spherical-bessel-j2: Public ordinary functions
spherical-bessel-jl: Public ordinary functions
spherical-bessel-jl-array: Public ordinary functions
spherical-bessel-jl-steed-array: Public ordinary functions
spherical-bessel-k0-scaled: Public ordinary functions
spherical-bessel-k1-scaled: Public ordinary functions
spherical-bessel-k2-scaled: Public ordinary functions
spherical-bessel-kl-scaled: Public ordinary functions
spherical-bessel-kl-scaled-array: Public ordinary functions
spherical-bessel-y0: Public ordinary functions
spherical-bessel-y1: Public ordinary functions
spherical-bessel-y2: Public ordinary functions
spherical-bessel-yl: Public ordinary functions
spherical-bessel-yl-array: Public ordinary functions
spline-example: Private ordinary functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
standard-deviation-with-fixed-mean: Public generic functions
state-pointer: Private ordinary functions
step-order: Public ordinary functions
stupid-code-walk-eval-some: Private ordinary functions
stupid-code-walk-find-variables: Private ordinary functions
success-continue: Private ordinary functions
success-failure: Private ordinary functions
sum: Public generic functions
sum: Public generic functions
sum: Public generic functions
sv-decomposition: Public ordinary functions
sv-jacobi-decomposition: Public ordinary functions
sv-modified-decomposition: Public ordinary functions
sv-solve: Public ordinary functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-columns: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-elements: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-row-column: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
swap-rows: Public generic functions
symbol-keyword-symbol: Private ordinary functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-1-update: Public generic functions
symmetric-rank-2-update: Public generic functions
symmetric-rank-2-update: Public generic functions
symmetric-rank-2-update: Public generic functions
symmetric-rank-2-update: Public generic functions
symmetric-rank-2-update: Public generic functions
symmetric-rank-2-update: Public generic functions
symmetric-rank-2-update: Public generic functions
synchrotron-1: Public ordinary functions
synchrotron-2: Public ordinary functions

T
taylor-coefficient: Public ordinary functions
taylor-divided-difference: Public ordinary functions
tdist-p: Public ordinary functions
tdist-pdf: Public ordinary functions
tdist-pinv: Public ordinary functions
tdist-q: Public ordinary functions
tdist-qinv: Public ordinary functions
test-cholesky-decomp-dim: Private ordinary functions
test-cholesky-invert-dim: Private ordinary functions
test-cholesky-solve-dim: Private ordinary functions
test-complex-fft-noise: Private ordinary functions
test-fft-noise: Private ordinary functions
test-hh-solve-dim: Private ordinary functions
test-lu-solve-dim: Private ordinary functions
test-qr-decomp-dim: Private ordinary functions
test-qr-lssolve-dim: Private ordinary functions
test-qr-qrsolve-dim: Private ordinary functions
test-qr-solve-dim: Private ordinary functions
test-qr-update-dim: Private ordinary functions
test-qrpt-decomp-dim: Private ordinary functions
test-qrpt-qrsolve-dim: Private ordinary functions
test-qrpt-solve-dim: Private ordinary functions
test-real-fft-noise: Private ordinary functions
test-sv-solve-dim: Private ordinary functions
testpdf: Private ordinary functions
transport-2: Public ordinary functions
transport-3: Public ordinary functions
transport-4: Public ordinary functions
transport-5: Public ordinary functions
tridiagonal-decomposition: Public generic functions
tridiagonal-decomposition: Public generic functions
tridiagonal-decomposition: Public generic functions
tridiagonal-unpack: Public generic functions
tridiagonal-unpack: Public generic functions
tridiagonal-unpack: Public generic functions
tridiagonal-unpack-t: Public generic functions
tridiagonal-unpack-t: Public generic functions
tridiagonal-unpack-t: Public generic functions
trivial-example-energy: Private ordinary functions
trivial-example-metric: Private ordinary functions
trivial-example-step: Private ordinary functions
trivial-test-energy: Private ordinary functions

U
ugaussian-p: Public ordinary functions
ugaussian-pdf: Public ordinary functions
ugaussian-pinv: Public ordinary functions
ugaussian-q: Public ordinary functions
ugaussian-qinv: Public ordinary functions
ugaussian-tail-pdf: Public ordinary functions
uniform-knots: Public ordinary functions
unpack: Public ordinary functions
urand: Private ordinary functions

V
validp: Public generic functions
validp: Public generic functions
validp: Public generic functions
value-from-dimensions: Private ordinary functions
values-unless-singleton: Private ordinary functions
values-with-errors: Private ordinary functions
vanderpol: Private ordinary functions
vanderpol-jacobian: Private ordinary functions
variables-used-in-c-arguments: Private ordinary functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
variance-with-fixed-mean: Public generic functions
vdf: Private ordinary functions
vdf-size: Private ordinary functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector-reverse: Public generic functions
vector/length: Private ordinary functions
view-bin-as-foreign-array: Private ordinary functions
view-range-as-foreign-array: Private ordinary functions
vspecs-direction: Private ordinary functions

W
wavelet-2d-nonstandard-transform: Public ordinary functions
wavelet-2d-nonstandard-transform-forward: Public ordinary functions
wavelet-2d-nonstandard-transform-inverse: Public ordinary functions
wavelet-2d-nonstandard-transform-matrix: Public ordinary functions
wavelet-2d-nonstandard-transform-matrix-forward: Public ordinary functions
wavelet-2d-nonstandard-transform-matrix-inverse: Public ordinary functions
wavelet-2d-transform: Public ordinary functions
wavelet-2d-transform-forward: Public ordinary functions
wavelet-2d-transform-inverse: Public ordinary functions
wavelet-2d-transform-matrix: Public ordinary functions
wavelet-2d-transform-matrix-forward: Public ordinary functions
wavelet-2d-transform-matrix-inverse: Public ordinary functions
wavelet-example: Private ordinary functions
wavelet-forward-example: Private ordinary functions
wavelet-transform: Public ordinary functions
wavelet-transform-forward: Public ordinary functions
wavelet-transform-inverse: Public ordinary functions
weibull-p: Public ordinary functions
weibull-pdf: Public ordinary functions
weibull-pinv: Public ordinary functions
weibull-q: Public ordinary functions
weibull-qinv: Public ordinary functions
weighted-absolute-deviation: Public generic functions
weighted-absolute-deviation: Public generic functions
weighted-absolute-deviation: Public generic functions
weighted-kurtosis: Public generic functions
weighted-kurtosis: Public generic functions
weighted-kurtosis: Public generic functions
weighted-mean: Public generic functions
weighted-mean: Public generic functions
weighted-mean: Public generic functions
weighted-mean: Public generic functions
weighted-mean: Public generic functions
weighted-skewness: Public generic functions
weighted-skewness: Public generic functions
weighted-skewness: Public generic functions
weighted-standard-deviation: Public generic functions
weighted-standard-deviation: Public generic functions
weighted-standard-deviation: Public generic functions
weighted-standard-deviation: Public generic functions
weighted-standard-deviation: Public generic functions
weighted-standard-deviation-with-fixed-mean: Public generic functions
weighted-standard-deviation-with-fixed-mean: Public generic functions
weighted-standard-deviation-with-fixed-mean: Public generic functions
weighted-standard-deviation-with-fixed-mean: Public generic functions
weighted-standard-deviation-with-fixed-mean: Public generic functions
weighted-variance: Public generic functions
weighted-variance: Public generic functions
weighted-variance: Public generic functions
weighted-variance: Public generic functions
weighted-variance: Public generic functions
weighted-variance-with-fixed-mean: Public generic functions
weighted-variance-with-fixed-mean: Public generic functions
weighted-variance-with-fixed-mean: Public generic functions
weighted-variance-with-fixed-mean: Public generic functions
weighted-variance-with-fixed-mean: Public generic functions
wfo-declare: Private ordinary functions
with-defmfun-key-args: Private macros
with-fourier-transform-environment: Public macros
with-ode-integration: Public macros
wrap-index-export: Private ordinary functions
wrap-letlike: Private ordinary functions
wrap-progn: Private ordinary functions
write-ntuple: Public ordinary functions

Z
zeta: Public generic functions
zeta: Public generic functions
zeta: Public generic functions
zeta-1: Public generic functions
zeta-1: Public generic functions
zeta-1: Public generic functions


A.3 Variables

Jump to:   *   +  
C   D   E   F   G   L   M   N   S   Y  
Index Entry  Section

*
*all-generated-tests*: Private special variables
*allowed-ticks*: Private special variables
*blas-splice-fp-types*: Private special variables
*callbacks-for-classes*: Private special variables
*cstd-blas-mapping*: Private special variables
*cstd-gsl-mapping*: Private special variables
*default-absolute-error*: Public special variables
*default-relative-error*: Public special variables
*default-sf-array-size*: Private special variables
*defmfun-llk*: Private special variables
*defmfun-optk*: Private special variables
*double-float-pool*: Private special variables
*elljac-a*: Private special variables
*elljac-b*: Private special variables
*elljac-c*: Private special variables
*elljac-c2*: Private special variables
*elljac-k*: Private special variables
*errorno-keyword*: Private special variables
*gsl-splice-fp-types*: Private special variables
*gsl-splice-int-types*: Private special variables
*gsl-symbol-equivalence*: Private special variables
*gsl-version*: Public symbol macros
*hilb12*: Private special variables
*hilb12-soln*: Private special variables
*hilb2*: Private special variables
*hilb2-soln*: Private special variables
*hilb3*: Private special variables
*hilb3-soln*: Private special variables
*hilb4*: Private special variables
*hilb4-soln*: Private special variables
*m35*: Private special variables
*m53*: Private special variables
*max-iter*: Private special variables
*mc-lower*: Private special variables
*mc-upper*: Private special variables
*monte-carlo-default-samples-per-dimension*: Private special variables
*nlls-example-data*: Private special variables
*ntuple-example-data-file*: Private special variables
*ntuple-example-scale*: Private special variables
*paraboloid-center*: Private special variables
*pdf-number-of-tries*: Private special variables
*pointer-offset*: Private special variables
*powell-a*: Private special variables
*rosenbrock-a*: Private special variables
*rosenbrock-b*: Private special variables
*s35*: Private special variables
*s53*: Private special variables
*signed-byte-pool*: Private special variables
*special-c-return*: Private special variables
*unsigned-byte-pool*: Private special variables
*vander12*: Private special variables
*vander12-soln*: Private special variables
*vander2*: Private special variables
*vander2-soln*: Private special variables
*vander3*: Private special variables
*vander3-soln*: Private special variables
*vander4*: Private special variables
*vander4-soln*: Private special variables
*wavelet-sample*: Private special variables

+
+akima-interpolation+: Public symbol macros
+bisection-fsolver+: Public symbol macros
+borosh13+: Public symbol macros
+brent-fminimizer+: Public symbol macros
+brent-fsolver+: Public symbol macros
+broyden+: Public symbol macros
+bspline-wavelet+: Public symbol macros
+bspline-wavelet-centered+: Public symbol macros
+cmrg+: Public symbol macros
+conjugate-fletcher-reeves+: Public symbol macros
+conjugate-polak-ribiere+: Public symbol macros
+continue+: Private constants
+coveyou+: Public symbol macros
+cubic-spline-interpolation+: Public symbol macros
+daubechies-wavelet+: Public symbol macros
+daubechies-wavelet-centered+: Public symbol macros
+default-seed+: Public symbol macros
+default-type+: Public symbol macros
+discrete-newton+: Public symbol macros
+ebadfunc+: Private constants
+ebadlen+: Private constants
+ebadtol+: Private constants
+ecache+: Private constants
+ediverge+: Private constants
+edom+: Private constants
+efactor+: Private constants
+efailed+: Private constants
+efault+: Private constants
+einval+: Private constants
+eloss+: Private constants
+emaxiter+: Private constants
+enomem+: Private constants
+enoprog+: Private constants
+enoprogj+: Private constants
+enotsqr+: Private constants
+eof+: Private constants
+eovrflw+: Private constants
+erange+: Private constants
+eround+: Private constants
+erunaway+: Private constants
+esanity+: Private constants
+esing+: Private constants
+etable+: Private constants
+etol+: Private constants
+etolf+: Private constants
+etolg+: Private constants
+etolx+: Private constants
+eundrflw+: Private constants
+eunimpl+: Private constants
+eunsup+: Private constants
+exp-x+: Private constants
+ezerodiv+: Private constants
+failure+: Private constants
+false-position-fsolver+: Public symbol macros
+fishman18+: Public symbol macros
+fishman20+: Public symbol macros
+fishman2x+: Public symbol macros
+gamma-xmax+: Private constants
+gfsr4+: Public symbol macros
+gnewton-mfdfsolver+: Public symbol macros
+golden-section-fminimizer+: Public symbol macros
+gslt-bin-size+: Private constants
+gslt-bins+: Private constants
+gslt-lower-limit+: Private constants
+gslt-upper-limit+: Private constants
+haar-wavelet+: Public symbol macros
+haar-wavelet-centered+: Public symbol macros
+halton+: Public symbol macros
+hybrid-scaled+: Public symbol macros
+hybrid-unscaled+: Public symbol macros
+initial-number-of-samples+: Private constants
+knuthran+: Public symbol macros
+knuthran2+: Public symbol macros
+knuthran2002+: Public symbol macros
+lecuyer21+: Public symbol macros
+levenberg-marquardt+: Public symbol macros
+levenberg-marquardt-unscaled+: Public symbol macros
+linear-interpolation+: Public symbol macros
+ln2+: Private constants
+minstd+: Public symbol macros
+mrg+: Public symbol macros
+mt19937+: Public symbol macros
+mt19937-1998+: Public symbol macros
+mt19937-1999+: Public symbol macros
+nan+: Public constants
+negative-infinity+: Public constants
+newton-fdfsolver+: Public symbol macros
+newton-mfdfsolver+: Public symbol macros
+niederreiter2+: Public symbol macros
+periodic-akima-interpolation+: Public symbol macros
+periodic-cubic-spline-interpolation+: Public symbol macros
+polynomial-interpolation+: Public symbol macros
+positive-infinity+: Public constants
+powells-hybrid+: Public symbol macros
+powells-hybrid-unscaled+: Public symbol macros
+quad-golden-fminimizer+: Public symbol macros
+r250+: Public symbol macros
+ran0+: Public symbol macros
+ran1+: Public symbol macros
+ran2+: Public symbol macros
+ran3+: Public symbol macros
+rand+: Public symbol macros
+rand48+: Public symbol macros
+random128_bsd+: Public symbol macros
+random128_glibc2+: Public symbol macros
+random128_libc5+: Public symbol macros
+random256_bsd+: Public symbol macros
+random256_glibc2+: Public symbol macros
+random256_libc5+: Public symbol macros
+random32_bsd+: Public symbol macros
+random32_glibc2+: Public symbol macros
+random32_libc5+: Public symbol macros
+random64_bsd+: Public symbol macros
+random64_glibc2+: Public symbol macros
+random64_libc5+: Public symbol macros
+random8_bsd+: Public symbol macros
+random8_glibc2+: Public symbol macros
+random8_libc5+: Public symbol macros
+random_bsd+: Public symbol macros
+random_glibc2+: Public symbol macros
+random_libc5+: Public symbol macros
+randu+: Public symbol macros
+ranf+: Public symbol macros
+ranlux+: Public symbol macros
+ranlux389+: Public symbol macros
+ranlxd1+: Public symbol macros
+ranlxd2+: Public symbol macros
+ranlxs0+: Public symbol macros
+ranlxs1+: Public symbol macros
+ranlxs2+: Public symbol macros
+ranmar+: Public symbol macros
+reverse-halton+: Public symbol macros
+secant-fdfsolver+: Public symbol macros
+simplex-nelder-mead+: Public symbol macros
+simplex-nelder-mead-on2+: Public symbol macros
+simplex-nelder-mead-random+: Public symbol macros
+slatec+: Public symbol macros
+sobol+: Public symbol macros
+steffenson-fdfsolver+: Public symbol macros
+step-bsimp+: Public symbol macros
+step-gear1+: Public symbol macros
+step-gear2+: Public symbol macros
+step-rk2+: Public symbol macros
+step-rk2imp+: Public symbol macros
+step-rk4+: Public symbol macros
+step-rk4imp+: Public symbol macros
+step-rk8pd+: Public symbol macros
+step-rkck+: Public symbol macros
+step-rkf45+: Public symbol macros
+success+: Private constants
+taus+: Public symbol macros
+taus113+: Public symbol macros
+taus2+: Public symbol macros
+test-factor+: Private constants
+test-sigma+: Private constants
+test-sqrt-tol0+: Private constants
+test-tol0+: Private constants
+test-tol1+: Private constants
+test-tol2+: Private constants
+test-tol3+: Private constants
+test-tol4+: Private constants
+test-tol5+: Private constants
+test-tol6+: Private constants
+transputer+: Public symbol macros
+tt800+: Public symbol macros
+uni+: Public symbol macros
+uni32+: Public symbol macros
+vax+: Public symbol macros
+vector-bfgs+: Public symbol macros
+vector-bfgs2+: Public symbol macros
+waterman14+: Public symbol macros
+zuf+: Public symbol macros

C
callback: Private classes
cbinfo: Private classes
Constant, +continue+: Private constants
Constant, +ebadfunc+: Private constants
Constant, +ebadlen+: Private constants
Constant, +ebadtol+: Private constants
Constant, +ecache+: Private constants
Constant, +ediverge+: Private constants
Constant, +edom+: Private constants
Constant, +efactor+: Private constants
Constant, +efailed+: Private constants
Constant, +efault+: Private constants
Constant, +einval+: Private constants
Constant, +eloss+: Private constants
Constant, +emaxiter+: Private constants
Constant, +enomem+: Private constants
Constant, +enoprog+: Private constants
Constant, +enoprogj+: Private constants
Constant, +enotsqr+: Private constants
Constant, +eof+: Private constants
Constant, +eovrflw+: Private constants
Constant, +erange+: Private constants
Constant, +eround+: Private constants
Constant, +erunaway+: Private constants
Constant, +esanity+: Private constants
Constant, +esing+: Private constants
Constant, +etable+: Private constants
Constant, +etol+: Private constants
Constant, +etolf+: Private constants
Constant, +etolg+: Private constants
Constant, +etolx+: Private constants
Constant, +eundrflw+: Private constants
Constant, +eunimpl+: Private constants
Constant, +eunsup+: Private constants
Constant, +exp-x+: Private constants
Constant, +ezerodiv+: Private constants
Constant, +failure+: Private constants
Constant, +gamma-xmax+: Private constants
Constant, +gslt-bin-size+: Private constants
Constant, +gslt-bins+: Private constants
Constant, +gslt-lower-limit+: Private constants
Constant, +gslt-upper-limit+: Private constants
Constant, +initial-number-of-samples+: Private constants
Constant, +ln2+: Private constants
Constant, +nan+: Public constants
Constant, +negative-infinity+: Public constants
Constant, +positive-infinity+: Public constants
Constant, +success+: Private constants
Constant, +test-factor+: Private constants
Constant, +test-sigma+: Private constants
Constant, +test-sqrt-tol0+: Private constants
Constant, +test-tol0+: Private constants
Constant, +test-tol1+: Private constants
Constant, +test-tol2+: Private constants
Constant, +test-tol3+: Private constants
Constant, +test-tol4+: Private constants
Constant, +test-tol5+: Private constants
Constant, +test-tol6+: Private constants
Constant, dpi: Private constants

D
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Public classes
dimension-names: Private classes
dimensions: Public classes
dimensions: Public classes
dimensions: Public classes
dimensions: Public classes
dimensions: Private classes
dpi: Private constants

E
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-number: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Public conditions
error-text: Private conditions
explanation: Public conditions

F
funcallables: Private classes
functions: Private classes

G
gsl-name: Private conditions
gsl-version: Private conditions

L
line-number: Public conditions

M
mpointer: Private classes

N
n: Private structures
name: Private conditions

S
scalarsp: Public classes
scalarsp: Public classes
scalarsp: Public classes
scalarsp: Public classes
scalarsp: Private classes
sigma: Private structures
Slot, callback: Private classes
Slot, cbinfo: Private classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Public classes
Slot, dimension-names: Private classes
Slot, dimensions: Public classes
Slot, dimensions: Public classes
Slot, dimensions: Public classes
Slot, dimensions: Public classes
Slot, dimensions: Private classes
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-number: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Public conditions
Slot, error-text: Private conditions
Slot, explanation: Public conditions
Slot, funcallables: Private classes
Slot, functions: Private classes
Slot, gsl-name: Private conditions
Slot, gsl-version: Private conditions
Slot, line-number: Public conditions
Slot, mpointer: Private classes
Slot, n: Private structures
Slot, name: Private conditions
Slot, scalarsp: Public classes
Slot, scalarsp: Public classes
Slot, scalarsp: Public classes
Slot, scalarsp: Public classes
Slot, scalarsp: Private classes
Slot, sigma: Private structures
Slot, source-file: Public conditions
Slot, y: Private structures
source-file: Public conditions
Special Variable, *all-generated-tests*: Private special variables
Special Variable, *allowed-ticks*: Private special variables
Special Variable, *blas-splice-fp-types*: Private special variables
Special Variable, *callbacks-for-classes*: Private special variables
Special Variable, *cstd-blas-mapping*: Private special variables
Special Variable, *cstd-gsl-mapping*: Private special variables
Special Variable, *default-absolute-error*: Public special variables
Special Variable, *default-relative-error*: Public special variables
Special Variable, *default-sf-array-size*: Private special variables
Special Variable, *defmfun-llk*: Private special variables
Special Variable, *defmfun-optk*: Private special variables
Special Variable, *double-float-pool*: Private special variables
Special Variable, *elljac-a*: Private special variables
Special Variable, *elljac-b*: Private special variables
Special Variable, *elljac-c*: Private special variables
Special Variable, *elljac-c2*: Private special variables
Special Variable, *elljac-k*: Private special variables
Special Variable, *errorno-keyword*: Private special variables
Special Variable, *gsl-splice-fp-types*: Private special variables
Special Variable, *gsl-splice-int-types*: Private special variables
Special Variable, *gsl-symbol-equivalence*: Private special variables
Special Variable, *hilb12*: Private special variables
Special Variable, *hilb12-soln*: Private special variables
Special Variable, *hilb2*: Private special variables
Special Variable, *hilb2-soln*: Private special variables
Special Variable, *hilb3*: Private special variables
Special Variable, *hilb3-soln*: Private special variables
Special Variable, *hilb4*: Private special variables
Special Variable, *hilb4-soln*: Private special variables
Special Variable, *m35*: Private special variables
Special Variable, *m53*: Private special variables
Special Variable, *max-iter*: Private special variables
Special Variable, *mc-lower*: Private special variables
Special Variable, *mc-upper*: Private special variables
Special Variable, *monte-carlo-default-samples-per-dimension*: Private special variables
Special Variable, *nlls-example-data*: Private special variables
Special Variable, *ntuple-example-data-file*: Private special variables
Special Variable, *ntuple-example-scale*: Private special variables
Special Variable, *paraboloid-center*: Private special variables
Special Variable, *pdf-number-of-tries*: Private special variables
Special Variable, *pointer-offset*: Private special variables
Special Variable, *powell-a*: Private special variables
Special Variable, *rosenbrock-a*: Private special variables
Special Variable, *rosenbrock-b*: Private special variables
Special Variable, *s35*: Private special variables
Special Variable, *s53*: Private special variables
Special Variable, *signed-byte-pool*: Private special variables
Special Variable, *special-c-return*: Private special variables
Special Variable, *unsigned-byte-pool*: Private special variables
Special Variable, *vander12*: Private special variables
Special Variable, *vander12-soln*: Private special variables
Special Variable, *vander2*: Private special variables
Special Variable, *vander2-soln*: Private special variables
Special Variable, *vander3*: Private special variables
Special Variable, *vander3-soln*: Private special variables
Special Variable, *vander4*: Private special variables
Special Variable, *vander4-soln*: Private special variables
Special Variable, *wavelet-sample*: Private special variables
Symbol Macro, *gsl-version*: Public symbol macros
Symbol Macro, +akima-interpolation+: Public symbol macros
Symbol Macro, +bisection-fsolver+: Public symbol macros
Symbol Macro, +borosh13+: Public symbol macros
Symbol Macro, +brent-fminimizer+: Public symbol macros
Symbol Macro, +brent-fsolver+: Public symbol macros
Symbol Macro, +broyden+: Public symbol macros
Symbol Macro, +bspline-wavelet+: Public symbol macros
Symbol Macro, +bspline-wavelet-centered+: Public symbol macros
Symbol Macro, +cmrg+: Public symbol macros
Symbol Macro, +conjugate-fletcher-reeves+: Public symbol macros
Symbol Macro, +conjugate-polak-ribiere+: Public symbol macros
Symbol Macro, +coveyou+: Public symbol macros
Symbol Macro, +cubic-spline-interpolation+: Public symbol macros
Symbol Macro, +daubechies-wavelet+: Public symbol macros
Symbol Macro, +daubechies-wavelet-centered+: Public symbol macros
Symbol Macro, +default-seed+: Public symbol macros
Symbol Macro, +default-type+: Public symbol macros
Symbol Macro, +discrete-newton+: Public symbol macros
Symbol Macro, +false-position-fsolver+: Public symbol macros
Symbol Macro, +fishman18+: Public symbol macros
Symbol Macro, +fishman20+: Public symbol macros
Symbol Macro, +fishman2x+: Public symbol macros
Symbol Macro, +gfsr4+: Public symbol macros
Symbol Macro, +gnewton-mfdfsolver+: Public symbol macros
Symbol Macro, +golden-section-fminimizer+: Public symbol macros
Symbol Macro, +haar-wavelet+: Public symbol macros
Symbol Macro, +haar-wavelet-centered+: Public symbol macros
Symbol Macro, +halton+: Public symbol macros
Symbol Macro, +hybrid-scaled+: Public symbol macros
Symbol Macro, +hybrid-unscaled+: Public symbol macros
Symbol Macro, +knuthran+: Public symbol macros
Symbol Macro, +knuthran2+: Public symbol macros
Symbol Macro, +knuthran2002+: Public symbol macros
Symbol Macro, +lecuyer21+: Public symbol macros
Symbol Macro, +levenberg-marquardt+: Public symbol macros
Symbol Macro, +levenberg-marquardt-unscaled+: Public symbol macros
Symbol Macro, +linear-interpolation+: Public symbol macros
Symbol Macro, +minstd+: Public symbol macros
Symbol Macro, +mrg+: Public symbol macros
Symbol Macro, +mt19937+: Public symbol macros
Symbol Macro, +mt19937-1998+: Public symbol macros
Symbol Macro, +mt19937-1999+: Public symbol macros
Symbol Macro, +newton-fdfsolver+: Public symbol macros
Symbol Macro, +newton-mfdfsolver+: Public symbol macros
Symbol Macro, +niederreiter2+: Public symbol macros
Symbol Macro, +periodic-akima-interpolation+: Public symbol macros
Symbol Macro, +periodic-cubic-spline-interpolation+: Public symbol macros
Symbol Macro, +polynomial-interpolation+: Public symbol macros
Symbol Macro, +powells-hybrid+: Public symbol macros
Symbol Macro, +powells-hybrid-unscaled+: Public symbol macros
Symbol Macro, +quad-golden-fminimizer+: Public symbol macros
Symbol Macro, +r250+: Public symbol macros
Symbol Macro, +ran0+: Public symbol macros
Symbol Macro, +ran1+: Public symbol macros
Symbol Macro, +ran2+: Public symbol macros
Symbol Macro, +ran3+: Public symbol macros
Symbol Macro, +rand+: Public symbol macros
Symbol Macro, +rand48+: Public symbol macros
Symbol Macro, +random128_bsd+: Public symbol macros
Symbol Macro, +random128_glibc2+: Public symbol macros
Symbol Macro, +random128_libc5+: Public symbol macros
Symbol Macro, +random256_bsd+: Public symbol macros
Symbol Macro, +random256_glibc2+: Public symbol macros
Symbol Macro, +random256_libc5+: Public symbol macros
Symbol Macro, +random32_bsd+: Public symbol macros
Symbol Macro, +random32_glibc2+: Public symbol macros
Symbol Macro, +random32_libc5+: Public symbol macros
Symbol Macro, +random64_bsd+: Public symbol macros
Symbol Macro, +random64_glibc2+: Public symbol macros
Symbol Macro, +random64_libc5+: Public symbol macros
Symbol Macro, +random8_bsd+: Public symbol macros
Symbol Macro, +random8_glibc2+: Public symbol macros
Symbol Macro, +random8_libc5+: Public symbol macros
Symbol Macro, +random_bsd+: Public symbol macros
Symbol Macro, +random_glibc2+: Public symbol macros
Symbol Macro, +random_libc5+: Public symbol macros
Symbol Macro, +randu+: Public symbol macros
Symbol Macro, +ranf+: Public symbol macros
Symbol Macro, +ranlux+: Public symbol macros
Symbol Macro, +ranlux389+: Public symbol macros
Symbol Macro, +ranlxd1+: Public symbol macros
Symbol Macro, +ranlxd2+: Public symbol macros
Symbol Macro, +ranlxs0+: Public symbol macros
Symbol Macro, +ranlxs1+: Public symbol macros
Symbol Macro, +ranlxs2+: Public symbol macros
Symbol Macro, +ranmar+: Public symbol macros
Symbol Macro, +reverse-halton+: Public symbol macros
Symbol Macro, +secant-fdfsolver+: Public symbol macros
Symbol Macro, +simplex-nelder-mead+: Public symbol macros
Symbol Macro, +simplex-nelder-mead-on2+: Public symbol macros
Symbol Macro, +simplex-nelder-mead-random+: Public symbol macros
Symbol Macro, +slatec+: Public symbol macros
Symbol Macro, +sobol+: Public symbol macros
Symbol Macro, +steffenson-fdfsolver+: Public symbol macros
Symbol Macro, +step-bsimp+: Public symbol macros
Symbol Macro, +step-gear1+: Public symbol macros
Symbol Macro, +step-gear2+: Public symbol macros
Symbol Macro, +step-rk2+: Public symbol macros
Symbol Macro, +step-rk2imp+: Public symbol macros
Symbol Macro, +step-rk4+: Public symbol macros
Symbol Macro, +step-rk4imp+: Public symbol macros
Symbol Macro, +step-rk8pd+: Public symbol macros
Symbol Macro, +step-rkck+: Public symbol macros
Symbol Macro, +step-rkf45+: Public symbol macros
Symbol Macro, +taus+: Public symbol macros
Symbol Macro, +taus113+: Public symbol macros
Symbol Macro, +taus2+: Public symbol macros
Symbol Macro, +transputer+: Public symbol macros
Symbol Macro, +tt800+: Public symbol macros
Symbol Macro, +uni+: Public symbol macros
Symbol Macro, +uni32+: Public symbol macros
Symbol Macro, +vax+: Public symbol macros
Symbol Macro, +vector-bfgs+: Public symbol macros
Symbol Macro, +vector-bfgs2+: Public symbol macros
Symbol Macro, +waterman14+: Public symbol macros
Symbol Macro, +zuf+: Public symbol macros

Y
y: Private structures


A.4 Data types

Jump to:   A   B   C   D   E   F   G   H   I   J   L   M   N   O   P   Q   R   S   T   U   V   W   Y   Z  
Index Entry  Section

A
absolute-deviation.lisp: The gsll/statistics/absolute-deviation․lisp file
absolute-deviation.lisp: The gsll/tests/absolute-deviation․lisp file
absolute-sum.lisp: The gsll/tests/absolute-sum․lisp file
acceleration: Public classes
airy.lisp: The gsll/special-functions/airy․lisp file
airy.lisp: The gsll/tests/airy․lisp file
array-structs.lisp: The gsll/data/array-structs․lisp file
array-tests.lisp: The gsll/data/array-tests․lisp file
augment.lisp: The gsll/test-unit/augment․lisp file
autocorrelation.lisp: The gsll/statistics/autocorrelation․lisp file
autocorrelation.lisp: The gsll/tests/autocorrelation․lisp file
axpy.lisp: The gsll/tests/axpy․lisp file

B
backward.lisp: The gsll/fast-fourier-transforms/backward․lisp file
bad-function-supplied: Public conditions
basis-spline: Public classes
basis-spline.lisp: The gsll/tests/basis-spline․lisp file
basis-splines.lisp: The gsll/basis-splines․lisp file
bernoulli.lisp: The gsll/random/bernoulli․lisp file
bernoulli.lisp: The gsll/tests/bernoulli․lisp file
bessel.lisp: The gsll/special-functions/bessel․lisp file
bessel.lisp: The gsll/tests/bessel․lisp file
beta.lisp: The gsll/random/beta․lisp file
beta.lisp: The gsll/tests/beta․lisp file
binomial.lisp: The gsll/random/binomial․lisp file
binomial.lisp: The gsll/tests/binomial․lisp file
blas-copy.lisp: The gsll/tests/blas-copy․lisp file
blas-swap.lisp: The gsll/tests/blas-swap․lisp file
blas1.lisp: The gsll/linear-algebra/blas1․lisp file
blas2.lisp: The gsll/linear-algebra/blas2․lisp file
blas3.lisp: The gsll/linear-algebra/blas3․lisp file
body-expand.lisp: The gsll/init/body-expand․lisp file
both.lisp: The gsll/data/both․lisp file

C
cache-limit-exceeded: Public conditions
calculus: The gsll/calculus module
callback-compile-defs.lisp: The gsll/init/callback-compile-defs․lisp file
callback-included: Private classes
callback-included-cl: Private classes
callback-included.lisp: The gsll/init/callback-included․lisp file
callback-struct.lisp: The gsll/init/callback-struct․lisp file
callback.lisp: The gsll/init/callback․lisp file
cauchy.lisp: The gsll/random/cauchy․lisp file
cauchy.lisp: The gsll/tests/cauchy․lisp file
cdot.lisp: The gsll/tests/cdot․lisp file
cgsm.lisp: The gsll/physical-constants/cgsm․lisp file
chebyshev: Public classes
chebyshev.lisp: The gsll/chebyshev․lisp file
chebyshev.lisp: The gsll/tests/chebyshev․lisp file
chi-squared.lisp: The gsll/random/chi-squared․lisp file
chi-squared.lisp: The gsll/tests/chi-squared․lisp file
cholesky.lisp: The gsll/linear-algebra/cholesky․lisp file
cholesky.lisp: The gsll/tests/cholesky․lisp file
Class, acceleration: Public classes
Class, basis-spline: Public classes
Class, callback-included: Private classes
Class, callback-included-cl: Private classes
Class, chebyshev: Public classes
Class, combination: Private classes
Class, discrete-random: Public classes
Class, eigen-gen: Public classes
Class, eigen-genherm: Public classes
Class, eigen-genhermv: Public classes
Class, eigen-gensymm: Public classes
Class, eigen-gensymmv: Public classes
Class, eigen-genv: Public classes
Class, eigen-herm: Public classes
Class, eigen-hermv: Public classes
Class, eigen-nonsymm: Public classes
Class, eigen-nonsymmv: Public classes
Class, eigen-symm: Public classes
Class, eigen-symmv: Public classes
Class, fft-complex-wavetable-double-float: Private classes
Class, fft-complex-wavetable-single-float: Private classes
Class, fft-complex-workspace-double-float: Private classes
Class, fft-complex-workspace-single-float: Private classes
Class, fft-half-complex-wavetable-double-float: Private classes
Class, fft-half-complex-wavetable-single-float: Private classes
Class, fft-real-wavetable-double-float: Private classes
Class, fft-real-wavetable-single-float: Private classes
Class, fft-real-workspace-double-float: Private classes
Class, fft-real-workspace-single-float: Private classes
Class, fit-workspace: Public classes
Class, hankel: Public classes
Class, histogram: Public classes
Class, histogram-c-tclass: Private classes
Class, histogram-pdf: Public classes
Class, histogram2d: Public classes
Class, histogram2d-pdf: Public classes
Class, integration-workspace: Public classes
Class, interpolation: Public classes
Class, levin: Public classes
Class, levin-truncated: Public classes
Class, mathieu: Public classes
Class, mobject: Private classes
Class, monte-carlo-miser: Public classes
Class, monte-carlo-plain: Public classes
Class, monte-carlo-vegas: Public classes
Class, multi-dimensional-minimizer-f: Public classes
Class, multi-dimensional-minimizer-fdf: Public classes
Class, multi-dimensional-root-solver-f: Public classes
Class, multi-dimensional-root-solver-fdf: Public classes
Class, nonlinear-fdffit: Public classes
Class, nonlinear-ffit: Public classes
Class, ntuple-data-tclass: Private classes
Class, ode-control: Private classes
Class, ode-evolution: Public classes
Class, ode-stepper: Public classes
Class, one-dimensional-minimizer: Public classes
Class, one-dimensional-root-solver-f: Public classes
Class, one-dimensional-root-solver-fdf: Public classes
Class, permutation: Public classes
Class, polynomial-complex-workspace: Public classes
Class, qawo-table: Public classes
Class, qaws-table: Public classes
Class, quasi-random-number-generator: Public classes
Class, random-number-generator: Public classes
Class, scaled-control: Public classes
Class, simulated-annealing-parameters-tclass: Private classes
Class, spline: Public classes
Class, standard-control: Public classes
Class, wavelet: Public classes
Class, wavelet-workspace: Public classes
Class, y-control: Public classes
Class, yp-control: Public classes
clausen.lisp: The gsll/special-functions/clausen․lisp file
clausen.lisp: The gsll/tests/clausen․lisp file
column.lisp: The gsll/tests/column․lisp file
combination: Private classes
combination.lisp: The gsll/data/combination․lisp file
combination.lisp: The gsll/tests/combination․lisp file
complex.lisp: The gsll/mathematical/complex․lisp file
Condition, bad-function-supplied: Public conditions
Condition, cache-limit-exceeded: Public conditions
Condition, divergence: Public conditions
Condition, exceeded-maximum-iterations: Public conditions
Condition, factorization-failure: Public conditions
Condition, failure-to-reach-tolerance: Public conditions
Condition, failure-to-reach-tolerance-f: Public conditions
Condition, failure-to-reach-tolerance-g: Public conditions
Condition, failure-to-reach-tolerance-x: Public conditions
Condition, generic-failure-1: Public conditions
Condition, generic-failure-2: Public conditions
Condition, gsl-condition: Public conditions
Condition, gsl-division-by-zero: Public conditions
Condition, gsl-eof: Public conditions
Condition, input-domain: Public conditions
Condition, input-range: Public conditions
Condition, invalid-argument: Public conditions
Condition, invalid-pointer: Public conditions
Condition, invalid-tolerance: Public conditions
Condition, jacobian-not-improving: Public conditions
Condition, loss-of-accuracy: Public conditions
Condition, memory-allocation-failure: Public conditions
Condition, no-progress: Public conditions
Condition, nonconformant-dimensions: Public conditions
Condition, nonsquare-matrix: Public conditions
Condition, obsolete-gsl-version: Private conditions
Condition, overflow: Public conditions
Condition, roundoff-failure: Public conditions
Condition, runaway-iteration: Public conditions
Condition, sanity-check-failure: Public conditions
Condition, singularity: Public conditions
Condition, table-limit-exceeded: Public conditions
Condition, underflow: Public conditions
Condition, unimplemented-feature: Public conditions
Condition, unspecified-errno: Private conditions
Condition, unsupported-feature: Public conditions
conditions.lisp: The gsll/init/conditions․lisp file
control.lisp: The gsll/ordinary-differential-equations/control․lisp file
correlation.lisp: The gsll/tests/correlation․lisp file
coulomb.lisp: The gsll/special-functions/coulomb․lisp file
coulomb.lisp: The gsll/tests/coulomb․lisp file
coupling.lisp: The gsll/special-functions/coupling․lisp file
coupling.lisp: The gsll/tests/coupling․lisp file
covariance.lisp: The gsll/statistics/covariance․lisp file
covariance.lisp: The gsll/tests/covariance․lisp file

D
data: The gsll/data module
dawson.lisp: The gsll/special-functions/dawson․lisp file
dawson.lisp: The gsll/tests/dawson․lisp file
debye.lisp: The gsll/special-functions/debye․lisp file
debye.lisp: The gsll/tests/debye․lisp file
defmfun-array.lisp: The gsll/init/defmfun-array․lisp file
defmfun-single.lisp: The gsll/init/defmfun-single․lisp file
defmfun.lisp: The gsll/init/defmfun․lisp file
diagonal.lisp: The gsll/linear-algebra/diagonal․lisp file
dilogarithm.lisp: The gsll/special-functions/dilogarithm․lisp file
dilogarithm.lisp: The gsll/tests/dilogarithm․lisp file
dirichlet.lisp: The gsll/random/dirichlet․lisp file
dirichlet.lisp: The gsll/tests/dirichlet․lisp file
discrete-random: Public classes
discrete.lisp: The gsll/fast-fourier-transforms/discrete․lisp file
discrete.lisp: The gsll/random/discrete․lisp file
discrete.lisp: The gsll/tests/discrete․lisp file
divergence: Public conditions
dot.lisp: The gsll/tests/dot․lisp file

E
eigen-gen: Public classes
eigen-genherm: Public classes
eigen-genhermv: Public classes
eigen-gensymm: Public classes
eigen-gensymmv: Public classes
eigen-genv: Public classes
eigen-herm: Public classes
eigen-hermv: Public classes
eigen-nonsymm: Public classes
eigen-nonsymmv: Public classes
eigen-struct.lisp: The gsll/eigensystems/eigen-struct․lisp file
eigen-symm: Public classes
eigen-symmv: Public classes
eigensystems: The gsll/eigensystems module
eigensystems.lisp: The gsll/tests/eigensystems․lisp file
elementary.lisp: The gsll/special-functions/elementary․lisp file
elementary.lisp: The gsll/tests/elementary․lisp file
elliptic-functions.lisp: The gsll/special-functions/elliptic-functions․lisp file
elliptic-functions.lisp: The gsll/tests/elliptic-functions․lisp file
elliptic-integrals.lisp: The gsll/special-functions/elliptic-integrals․lisp file
elliptic-integrals.lisp: The gsll/tests/elliptic-integrals․lisp file
error-functions.lisp: The gsll/special-functions/error-functions․lisp file
error-functions.lisp: The gsll/tests/error-functions․lisp file
euclidean-norm.lisp: The gsll/tests/euclidean-norm․lisp file
evaluation.lisp: The gsll/interpolation/evaluation․lisp file
evolution.lisp: The gsll/ordinary-differential-equations/evolution․lisp file
example.lisp: The gsll/fast-fourier-transforms/example․lisp file
exceeded-maximum-iterations: Public conditions
exponent-fit-data: Private structures
exponential-functions.lisp: The gsll/special-functions/exponential-functions․lisp file
exponential-functions.lisp: The gsll/tests/exponential-functions․lisp file
exponential-integrals.lisp: The gsll/special-functions/exponential-integrals․lisp file
exponential-integrals.lisp: The gsll/tests/exponential-integrals․lisp file
exponential-power.lisp: The gsll/random/exponential-power․lisp file
exponential-power.lisp: The gsll/tests/exponential-power․lisp file
exponential.lisp: The gsll/linear-algebra/exponential․lisp file
exponential.lisp: The gsll/random/exponential․lisp file
exponential.lisp: The gsll/tests/exponential․lisp file
export.lisp: The gsll/physical-constants/export․lisp file
extras.lisp: The gsll/fast-fourier-transforms/extras․lisp file

F
factorization-failure: Public conditions
failure-to-reach-tolerance: Public conditions
failure-to-reach-tolerance-f: Public conditions
failure-to-reach-tolerance-g: Public conditions
failure-to-reach-tolerance-x: Public conditions
fast-fourier-transform.lisp: The gsll/tests/fast-fourier-transform․lisp file
fast-fourier-transforms: The gsll/fast-fourier-transforms module
fdist.lisp: The gsll/random/fdist․lisp file
fdist.lisp: The gsll/tests/fdist․lisp file
fermi-dirac.lisp: The gsll/special-functions/fermi-dirac․lisp file
fermi-dirac.lisp: The gsll/tests/fermi-dirac․lisp file
fft-complex-wavetable-double-float: Private classes
fft-complex-wavetable-single-float: Private classes
fft-complex-workspace-double-float: Private classes
fft-complex-workspace-single-float: Private classes
fft-half-complex-wavetable-double-float: Private classes
fft-half-complex-wavetable-single-float: Private classes
fft-real-wavetable-double-float: Private classes
fft-real-wavetable-single-float: Private classes
fft-real-workspace-double-float: Private classes
fft-real-workspace-single-float: Private classes
File, absolute-deviation.lisp: The gsll/statistics/absolute-deviation․lisp file
File, absolute-deviation.lisp: The gsll/tests/absolute-deviation․lisp file
File, absolute-sum.lisp: The gsll/tests/absolute-sum․lisp file
File, airy.lisp: The gsll/special-functions/airy․lisp file
File, airy.lisp: The gsll/tests/airy․lisp file
File, array-structs.lisp: The gsll/data/array-structs․lisp file
File, array-tests.lisp: The gsll/data/array-tests․lisp file
File, augment.lisp: The gsll/test-unit/augment․lisp file
File, autocorrelation.lisp: The gsll/statistics/autocorrelation․lisp file
File, autocorrelation.lisp: The gsll/tests/autocorrelation․lisp file
File, axpy.lisp: The gsll/tests/axpy․lisp file
File, backward.lisp: The gsll/fast-fourier-transforms/backward․lisp file
File, basis-spline.lisp: The gsll/tests/basis-spline․lisp file
File, basis-splines.lisp: The gsll/basis-splines․lisp file
File, bernoulli.lisp: The gsll/random/bernoulli․lisp file
File, bernoulli.lisp: The gsll/tests/bernoulli․lisp file
File, bessel.lisp: The gsll/special-functions/bessel․lisp file
File, bessel.lisp: The gsll/tests/bessel․lisp file
File, beta.lisp: The gsll/random/beta․lisp file
File, beta.lisp: The gsll/tests/beta․lisp file
File, binomial.lisp: The gsll/random/binomial․lisp file
File, binomial.lisp: The gsll/tests/binomial․lisp file
File, blas-copy.lisp: The gsll/tests/blas-copy․lisp file
File, blas-swap.lisp: The gsll/tests/blas-swap․lisp file
File, blas1.lisp: The gsll/linear-algebra/blas1․lisp file
File, blas2.lisp: The gsll/linear-algebra/blas2․lisp file
File, blas3.lisp: The gsll/linear-algebra/blas3․lisp file
File, body-expand.lisp: The gsll/init/body-expand․lisp file
File, both.lisp: The gsll/data/both․lisp file
File, callback-compile-defs.lisp: The gsll/init/callback-compile-defs․lisp file
File, callback-included.lisp: The gsll/init/callback-included․lisp file
File, callback-struct.lisp: The gsll/init/callback-struct․lisp file
File, callback.lisp: The gsll/init/callback․lisp file
File, cauchy.lisp: The gsll/random/cauchy․lisp file
File, cauchy.lisp: The gsll/tests/cauchy․lisp file
File, cdot.lisp: The gsll/tests/cdot․lisp file
File, cgsm.lisp: The gsll/physical-constants/cgsm․lisp file
File, chebyshev.lisp: The gsll/chebyshev․lisp file
File, chebyshev.lisp: The gsll/tests/chebyshev․lisp file
File, chi-squared.lisp: The gsll/random/chi-squared․lisp file
File, chi-squared.lisp: The gsll/tests/chi-squared․lisp file
File, cholesky.lisp: The gsll/linear-algebra/cholesky․lisp file
File, cholesky.lisp: The gsll/tests/cholesky․lisp file
File, clausen.lisp: The gsll/special-functions/clausen․lisp file
File, clausen.lisp: The gsll/tests/clausen․lisp file
File, column.lisp: The gsll/tests/column․lisp file
File, combination.lisp: The gsll/data/combination․lisp file
File, combination.lisp: The gsll/tests/combination․lisp file
File, complex.lisp: The gsll/mathematical/complex․lisp file
File, conditions.lisp: The gsll/init/conditions․lisp file
File, control.lisp: The gsll/ordinary-differential-equations/control․lisp file
File, correlation.lisp: The gsll/tests/correlation․lisp file
File, coulomb.lisp: The gsll/special-functions/coulomb․lisp file
File, coulomb.lisp: The gsll/tests/coulomb․lisp file
File, coupling.lisp: The gsll/special-functions/coupling․lisp file
File, coupling.lisp: The gsll/tests/coupling․lisp file
File, covariance.lisp: The gsll/statistics/covariance․lisp file
File, covariance.lisp: The gsll/tests/covariance․lisp file
File, dawson.lisp: The gsll/special-functions/dawson․lisp file
File, dawson.lisp: The gsll/tests/dawson․lisp file
File, debye.lisp: The gsll/special-functions/debye․lisp file
File, debye.lisp: The gsll/tests/debye․lisp file
File, defmfun-array.lisp: The gsll/init/defmfun-array․lisp file
File, defmfun-single.lisp: The gsll/init/defmfun-single․lisp file
File, defmfun.lisp: The gsll/init/defmfun․lisp file
File, diagonal.lisp: The gsll/linear-algebra/diagonal․lisp file
File, dilogarithm.lisp: The gsll/special-functions/dilogarithm․lisp file
File, dilogarithm.lisp: The gsll/tests/dilogarithm․lisp file
File, dirichlet.lisp: The gsll/random/dirichlet․lisp file
File, dirichlet.lisp: The gsll/tests/dirichlet․lisp file
File, discrete.lisp: The gsll/fast-fourier-transforms/discrete․lisp file
File, discrete.lisp: The gsll/random/discrete․lisp file
File, discrete.lisp: The gsll/tests/discrete․lisp file
File, dot.lisp: The gsll/tests/dot․lisp file
File, eigen-struct.lisp: The gsll/eigensystems/eigen-struct․lisp file
File, eigensystems.lisp: The gsll/tests/eigensystems․lisp file
File, elementary.lisp: The gsll/special-functions/elementary․lisp file
File, elementary.lisp: The gsll/tests/elementary․lisp file
File, elliptic-functions.lisp: The gsll/special-functions/elliptic-functions․lisp file
File, elliptic-functions.lisp: The gsll/tests/elliptic-functions․lisp file
File, elliptic-integrals.lisp: The gsll/special-functions/elliptic-integrals․lisp file
File, elliptic-integrals.lisp: The gsll/tests/elliptic-integrals․lisp file
File, error-functions.lisp: The gsll/special-functions/error-functions․lisp file
File, error-functions.lisp: The gsll/tests/error-functions․lisp file
File, euclidean-norm.lisp: The gsll/tests/euclidean-norm․lisp file
File, evaluation.lisp: The gsll/interpolation/evaluation․lisp file
File, evolution.lisp: The gsll/ordinary-differential-equations/evolution․lisp file
File, example.lisp: The gsll/fast-fourier-transforms/example․lisp file
File, exponential-functions.lisp: The gsll/special-functions/exponential-functions․lisp file
File, exponential-functions.lisp: The gsll/tests/exponential-functions․lisp file
File, exponential-integrals.lisp: The gsll/special-functions/exponential-integrals․lisp file
File, exponential-integrals.lisp: The gsll/tests/exponential-integrals․lisp file
File, exponential-power.lisp: The gsll/random/exponential-power․lisp file
File, exponential-power.lisp: The gsll/tests/exponential-power․lisp file
File, exponential.lisp: The gsll/linear-algebra/exponential․lisp file
File, exponential.lisp: The gsll/random/exponential․lisp file
File, exponential.lisp: The gsll/tests/exponential․lisp file
File, export.lisp: The gsll/physical-constants/export․lisp file
File, extras.lisp: The gsll/fast-fourier-transforms/extras․lisp file
File, fast-fourier-transform.lisp: The gsll/tests/fast-fourier-transform․lisp file
File, fdist.lisp: The gsll/random/fdist․lisp file
File, fdist.lisp: The gsll/tests/fdist․lisp file
File, fermi-dirac.lisp: The gsll/special-functions/fermi-dirac․lisp file
File, fermi-dirac.lisp: The gsll/tests/fermi-dirac․lisp file
File, flat.lisp: The gsll/random/flat․lisp file
File, flat.lisp: The gsll/tests/flat․lisp file
File, floating-point.lisp: The gsll/floating-point/floating-point․lisp file
File, foreign-array.lisp: The gsll/data/foreign-array․lisp file
File, forms.lisp: The gsll/init/forms․lisp file
File, forward.lisp: The gsll/fast-fourier-transforms/forward․lisp file
File, funcallable.lisp: The gsll/init/funcallable․lisp file
File, gamma-randist.lisp: The gsll/tests/gamma-randist․lisp file
File, gamma.lisp: The gsll/special-functions/gamma․lisp file
File, gamma.lisp: The gsll/random/gamma․lisp file
File, gamma.lisp: The gsll/tests/gamma․lisp file
File, gaussian-bivariate.lisp: The gsll/random/gaussian-bivariate․lisp file
File, gaussian-bivariate.lisp: The gsll/tests/gaussian-bivariate․lisp file
File, gaussian-tail.lisp: The gsll/random/gaussian-tail․lisp file
File, gaussian-tail.lisp: The gsll/tests/gaussian-tail․lisp file
File, gaussian.lisp: The gsll/random/gaussian․lisp file
File, gaussian.lisp: The gsll/tests/gaussian․lisp file
File, gegenbauer.lisp: The gsll/special-functions/gegenbauer․lisp file
File, gegenbauer.lisp: The gsll/tests/gegenbauer․lisp file
File, generalized.lisp: The gsll/eigensystems/generalized․lisp file
File, generate-examples.lisp: The gsll/init/generate-examples․lisp file
File, generators.lisp: The gsll/random/generators․lisp file
File, generic.lisp: The gsll/init/generic․lisp file
File, generic.lisp: The gsll/solve-minimize-fit/generic․lisp file
File, geometric.lisp: The gsll/random/geometric․lisp file
File, geometric.lisp: The gsll/tests/geometric․lisp file
File, givens.lisp: The gsll/tests/givens․lisp file
File, gsl-version.lisp: The gsll/init/gsl-version․lisp file
File, gsll.asd: The gsll/gsll․asd file
File, gumbel1.lisp: The gsll/random/gumbel1․lisp file
File, gumbel1.lisp: The gsll/tests/gumbel1․lisp file
File, gumbel2.lisp: The gsll/random/gumbel2․lisp file
File, gumbel2.lisp: The gsll/tests/gumbel2․lisp file
File, hankel.lisp: The gsll/hankel․lisp file
File, hankel.lisp: The gsll/tests/hankel․lisp file
File, higher-moments.lisp: The gsll/statistics/higher-moments․lisp file
File, higher-moments.lisp: The gsll/tests/higher-moments․lisp file
File, histogram.lisp: The gsll/histogram/histogram․lisp file
File, histogram.lisp: The gsll/tests/histogram․lisp file
File, householder.lisp: The gsll/linear-algebra/householder․lisp file
File, householder.lisp: The gsll/tests/householder․lisp file
File, hypergeometric-randist.lisp: The gsll/tests/hypergeometric-randist․lisp file
File, hypergeometric.lisp: The gsll/special-functions/hypergeometric․lisp file
File, hypergeometric.lisp: The gsll/random/hypergeometric․lisp file
File, hypergeometric.lisp: The gsll/tests/hypergeometric․lisp file
File, ieee-modes.lisp: The gsll/floating-point/ieee-modes․lisp file
File, index-max.lisp: The gsll/tests/index-max․lisp file
File, init.lisp: The gsll/init/init․lisp file
File, interface.lisp: The gsll/init/interface․lisp file
File, interpolation.lisp: The gsll/interpolation/interpolation․lisp file
File, interpolation.lisp: The gsll/tests/interpolation․lisp file
File, inverse-matrix-product.lisp: The gsll/tests/inverse-matrix-product․lisp file
File, inverse.lisp: The gsll/fast-fourier-transforms/inverse․lisp file
File, laguerre.lisp: The gsll/special-functions/laguerre․lisp file
File, laguerre.lisp: The gsll/tests/laguerre․lisp file
File, lambert.lisp: The gsll/special-functions/lambert․lisp file
File, lambert.lisp: The gsll/tests/lambert․lisp file
File, landau.lisp: The gsll/random/landau․lisp file
File, landau.lisp: The gsll/tests/landau․lisp file
File, laplace.lisp: The gsll/random/laplace․lisp file
File, laplace.lisp: The gsll/tests/laplace․lisp file
File, legendre.lisp: The gsll/special-functions/legendre․lisp file
File, legendre.lisp: The gsll/tests/legendre․lisp file
File, levy.lisp: The gsll/random/levy․lisp file
File, levy.lisp: The gsll/tests/levy․lisp file
File, libgsl.lisp: The gsll/init/libgsl․lisp file
File, linear-least-squares.lisp: The gsll/solve-minimize-fit/linear-least-squares․lisp file
File, linear-least-squares.lisp: The gsll/tests/linear-least-squares․lisp file
File, logarithm.lisp: The gsll/special-functions/logarithm․lisp file
File, logarithm.lisp: The gsll/tests/logarithm․lisp file
File, logarithmic.lisp: The gsll/random/logarithmic․lisp file
File, logarithmic.lisp: The gsll/tests/logarithmic․lisp file
File, logistic.lisp: The gsll/random/logistic․lisp file
File, logistic.lisp: The gsll/tests/logistic․lisp file
File, lognormal.lisp: The gsll/random/lognormal․lisp file
File, lognormal.lisp: The gsll/tests/lognormal․lisp file
File, lookup.lisp: The gsll/interpolation/lookup․lisp file
File, lu.lisp: The gsll/linear-algebra/lu․lisp file
File, lu.lisp: The gsll/tests/lu․lisp file
File, machine.lisp: The gsll/test-unit/machine․lisp file
File, mathematical.lisp: The gsll/mathematical/mathematical․lisp file
File, mathematical.lisp: The gsll/tests/mathematical․lisp file
File, mathieu.lisp: The gsll/special-functions/mathieu․lisp file
File, mathieu.lisp: The gsll/tests/mathieu․lisp file
File, matrix-add.lisp: The gsll/tests/matrix-add․lisp file
File, matrix-div.lisp: The gsll/tests/matrix-div․lisp file
File, matrix-generation.lisp: The gsll/linear-algebra/matrix-generation․lisp file
File, matrix-max-index.lisp: The gsll/tests/matrix-max-index․lisp file
File, matrix-max.lisp: The gsll/tests/matrix-max․lisp file
File, matrix-mean.lisp: The gsll/tests/matrix-mean․lisp file
File, matrix-min-index.lisp: The gsll/tests/matrix-min-index․lisp file
File, matrix-min.lisp: The gsll/tests/matrix-min․lisp file
File, matrix-minmax-index.lisp: The gsll/tests/matrix-minmax-index․lisp file
File, matrix-minmax.lisp: The gsll/tests/matrix-minmax․lisp file
File, matrix-mult.lisp: The gsll/tests/matrix-mult․lisp file
File, matrix-product-hermitian.lisp: The gsll/tests/matrix-product-hermitian․lisp file
File, matrix-product-nonsquare.lisp: The gsll/tests/matrix-product-nonsquare․lisp file
File, matrix-product-symmetric.lisp: The gsll/tests/matrix-product-symmetric․lisp file
File, matrix-product-triangular.lisp: The gsll/tests/matrix-product-triangular․lisp file
File, matrix-product.lisp: The gsll/tests/matrix-product․lisp file
File, matrix-set-all.lisp: The gsll/tests/matrix-set-all․lisp file
File, matrix-set-zero.lisp: The gsll/tests/matrix-set-zero․lisp file
File, matrix-standard-deviation-with-fixed-mean.lisp: The gsll/tests/matrix-standard-deviation-with-fixed-mean․lisp file
File, matrix-standard-deviation-with-mean.lisp: The gsll/tests/matrix-standard-deviation-with-mean․lisp file
File, matrix-standard-deviation.lisp: The gsll/tests/matrix-standard-deviation․lisp file
File, matrix-sub.lisp: The gsll/tests/matrix-sub․lisp file
File, matrix-swap.lisp: The gsll/tests/matrix-swap․lisp file
File, matrix-transpose-copy.lisp: The gsll/tests/matrix-transpose-copy․lisp file
File, matrix-transpose.lisp: The gsll/tests/matrix-transpose․lisp file
File, matrix-variance-with-fixed-mean.lisp: The gsll/tests/matrix-variance-with-fixed-mean․lisp file
File, matrix-variance-with-mean.lisp: The gsll/tests/matrix-variance-with-mean․lisp file
File, matrix-variance.lisp: The gsll/tests/matrix-variance․lisp file
File, matrix.lisp: The gsll/data/matrix․lisp file
File, mean-variance.lisp: The gsll/statistics/mean-variance․lisp file
File, median-percentile.lisp: The gsll/statistics/median-percentile․lisp file
File, median-percentile.lisp: The gsll/tests/median-percentile․lisp file
File, minimization-multi.lisp: The gsll/solve-minimize-fit/minimization-multi․lisp file
File, minimization-multi.lisp: The gsll/tests/minimization-multi․lisp file
File, minimization-one.lisp: The gsll/solve-minimize-fit/minimization-one․lisp file
File, minimization-one.lisp: The gsll/tests/minimization-one․lisp file
File, mksa.lisp: The gsll/physical-constants/mksa․lisp file
File, mobject.lisp: The gsll/init/mobject․lisp file
File, monte-carlo-structs.lisp: The gsll/calculus/monte-carlo-structs․lisp file
File, monte-carlo.lisp: The gsll/calculus/monte-carlo․lisp file
File, monte-carlo.lisp: The gsll/tests/monte-carlo․lisp file
File, multinomial.lisp: The gsll/random/multinomial․lisp file
File, multinomial.lisp: The gsll/tests/multinomial․lisp file
File, negative-binomial.lisp: The gsll/random/negative-binomial․lisp file
File, negative-binomial.lisp: The gsll/tests/negative-binomial․lisp file
File, nonlinear-least-squares.lisp: The gsll/solve-minimize-fit/nonlinear-least-squares․lisp file
File, nonlinear-least-squares.lisp: The gsll/tests/nonlinear-least-squares․lisp file
File, nonsymmetric-generalized.lisp: The gsll/eigensystems/nonsymmetric-generalized․lisp file
File, nonsymmetric.lisp: The gsll/eigensystems/nonsymmetric․lisp file
File, ntuple.lisp: The gsll/histogram/ntuple․lisp file
File, ntuple.lisp: The gsll/tests/ntuple․lisp file
File, num.lisp: The gsll/physical-constants/num․lisp file
File, numerical-differentiation.lisp: The gsll/calculus/numerical-differentiation․lisp file
File, numerical-differentiation.lisp: The gsll/tests/numerical-differentiation․lisp file
File, numerical-integration-with-tables.lisp: The gsll/calculus/numerical-integration-with-tables․lisp file
File, numerical-integration.lisp: The gsll/calculus/numerical-integration․lisp file
File, numerical-integration.lisp: The gsll/tests/numerical-integration․lisp file
File, ode-example.lisp: The gsll/ordinary-differential-equations/ode-example․lisp file
File, ode-struct.lisp: The gsll/ordinary-differential-equations/ode-struct․lisp file
File, ode-system.lisp: The gsll/ordinary-differential-equations/ode-system․lisp file
File, ode.lisp: The gsll/tests/ode․lisp file
File, operations.lisp: The gsll/histogram/operations․lisp file
File, pareto.lisp: The gsll/random/pareto․lisp file
File, pareto.lisp: The gsll/tests/pareto․lisp file
File, permutation.lisp: The gsll/data/permutation․lisp file
File, permutation.lisp: The gsll/tests/permutation․lisp file
File, poisson.lisp: The gsll/random/poisson․lisp file
File, poisson.lisp: The gsll/tests/poisson․lisp file
File, polynomial.lisp: The gsll/polynomial․lisp file
File, polynomial.lisp: The gsll/tests/polynomial․lisp file
File, power.lisp: The gsll/special-functions/power․lisp file
File, power.lisp: The gsll/tests/power․lisp file
File, probability-distribution.lisp: The gsll/histogram/probability-distribution․lisp file
File, psi.lisp: The gsll/special-functions/psi․lisp file
File, psi.lisp: The gsll/tests/psi․lisp file
File, qr.lisp: The gsll/linear-algebra/qr․lisp file
File, qr.lisp: The gsll/tests/qr․lisp file
File, qrpt.lisp: The gsll/linear-algebra/qrpt․lisp file
File, qrpt.lisp: The gsll/tests/qrpt․lisp file
File, quasi-random-number-generators.lisp: The gsll/tests/quasi-random-number-generators․lisp file
File, quasi.lisp: The gsll/random/quasi․lisp file
File, random-number-generators.lisp: The gsll/tests/random-number-generators․lisp file
File, rank-1-update.lisp: The gsll/tests/rank-1-update․lisp file
File, rayleigh-tail.lisp: The gsll/random/rayleigh-tail․lisp file
File, rayleigh-tail.lisp: The gsll/tests/rayleigh-tail․lisp file
File, rayleigh.lisp: The gsll/random/rayleigh․lisp file
File, rayleigh.lisp: The gsll/tests/rayleigh․lisp file
File, return-structures.lisp: The gsll/special-functions/return-structures․lisp file
File, rng-types.lisp: The gsll/random/rng-types․lisp file
File, roots-multi.lisp: The gsll/solve-minimize-fit/roots-multi․lisp file
File, roots-multi.lisp: The gsll/tests/roots-multi․lisp file
File, roots-one.lisp: The gsll/solve-minimize-fit/roots-one․lisp file
File, roots-one.lisp: The gsll/tests/roots-one․lisp file
File, row.lisp: The gsll/tests/row․lisp file
File, scale.lisp: The gsll/tests/scale․lisp file
File, select-direction.lisp: The gsll/fast-fourier-transforms/select-direction․lisp file
File, series-acceleration.lisp: The gsll/series-acceleration․lisp file
File, series-acceleration.lisp: The gsll/tests/series-acceleration․lisp file
File, series-struct.lisp: The gsll/series-struct․lisp file
File, set-basis.lisp: The gsll/tests/set-basis․lisp file
File, set-identity.lisp: The gsll/tests/set-identity․lisp file
File, setf-column.lisp: The gsll/tests/setf-column․lisp file
File, setf-row.lisp: The gsll/tests/setf-row․lisp file
File, sf-result.lisp: The gsll/special-functions/sf-result․lisp file
File, shuffling-sampling.lisp: The gsll/random/shuffling-sampling․lisp file
File, shuffling-sampling.lisp: The gsll/tests/shuffling-sampling․lisp file
File, simulated-annealing.lisp: The gsll/solve-minimize-fit/simulated-annealing․lisp file
File, solver-struct.lisp: The gsll/solve-minimize-fit/solver-struct․lisp file
File, sort-matrix-largest.lisp: The gsll/tests/sort-matrix-largest․lisp file
File, sort-matrix-smallest.lisp: The gsll/tests/sort-matrix-smallest․lisp file
File, sort-matrix.lisp: The gsll/tests/sort-matrix․lisp file
File, sort-vector-index.lisp: The gsll/tests/sort-vector-index․lisp file
File, sort-vector-largest-index.lisp: The gsll/tests/sort-vector-largest-index․lisp file
File, sort-vector-largest.lisp: The gsll/tests/sort-vector-largest․lisp file
File, sort-vector-smallest-index.lisp: The gsll/tests/sort-vector-smallest-index․lisp file
File, sort-vector-smallest.lisp: The gsll/tests/sort-vector-smallest․lisp file
File, sort-vector.lisp: The gsll/tests/sort-vector․lisp file
File, sorting.lisp: The gsll/sorting․lisp file
File, spherical-vector.lisp: The gsll/random/spherical-vector․lisp file
File, spherical-vector.lisp: The gsll/tests/spherical-vector․lisp file
File, spline-example.lisp: The gsll/interpolation/spline-example․lisp file
File, statistics.lisp: The gsll/histogram/statistics․lisp file
File, stepping.lisp: The gsll/ordinary-differential-equations/stepping․lisp file
File, svd.lisp: The gsll/linear-algebra/svd․lisp file
File, svd.lisp: The gsll/tests/svd․lisp file
File, swap-columns.lisp: The gsll/tests/swap-columns․lisp file
File, swap-elements.lisp: The gsll/tests/swap-elements․lisp file
File, swap-row-column.lisp: The gsll/tests/swap-row-column․lisp file
File, swap-rows.lisp: The gsll/tests/swap-rows․lisp file
File, symmetric-hermitian.lisp: The gsll/eigensystems/symmetric-hermitian․lisp file
File, synchrotron.lisp: The gsll/special-functions/synchrotron․lisp file
File, synchrotron.lisp: The gsll/tests/synchrotron․lisp file
File, tdist.lisp: The gsll/random/tdist․lisp file
File, tdist.lisp: The gsll/tests/tdist․lisp file
File, tests.lisp: The gsll/random/tests․lisp file
File, transport.lisp: The gsll/special-functions/transport․lisp file
File, transport.lisp: The gsll/tests/transport․lisp file
File, trigonometry.lisp: The gsll/special-functions/trigonometry․lisp file
File, trigonometry.lisp: The gsll/tests/trigonometry․lisp file
File, types.lisp: The gsll/init/types․lisp file
File, types.lisp: The gsll/interpolation/types․lisp file
File, unpack.lisp: The gsll/fast-fourier-transforms/unpack․lisp file
File, updating-accessing.lisp: The gsll/histogram/updating-accessing․lisp file
File, utility.lisp: The gsll/init/utility․lisp file
File, vector-add.lisp: The gsll/tests/vector-add․lisp file
File, vector-div.lisp: The gsll/tests/vector-div․lisp file
File, vector-max-index.lisp: The gsll/tests/vector-max-index․lisp file
File, vector-max.lisp: The gsll/tests/vector-max․lisp file
File, vector-mean.lisp: The gsll/tests/vector-mean․lisp file
File, vector-min-index.lisp: The gsll/tests/vector-min-index․lisp file
File, vector-min.lisp: The gsll/tests/vector-min․lisp file
File, vector-minmax-index.lisp: The gsll/tests/vector-minmax-index․lisp file
File, vector-minmax.lisp: The gsll/tests/vector-minmax․lisp file
File, vector-mult.lisp: The gsll/tests/vector-mult․lisp file
File, vector-reverse.lisp: The gsll/tests/vector-reverse․lisp file
File, vector-set-all.lisp: The gsll/tests/vector-set-all․lisp file
File, vector-set-zero.lisp: The gsll/tests/vector-set-zero․lisp file
File, vector-standard-deviation-with-fixed-mean.lisp: The gsll/tests/vector-standard-deviation-with-fixed-mean․lisp file
File, vector-standard-deviation-with-mean.lisp: The gsll/tests/vector-standard-deviation-with-mean․lisp file
File, vector-standard-deviation.lisp: The gsll/tests/vector-standard-deviation․lisp file
File, vector-sub.lisp: The gsll/tests/vector-sub․lisp file
File, vector-swap.lisp: The gsll/tests/vector-swap․lisp file
File, vector-variance-with-fixed-mean.lisp: The gsll/tests/vector-variance-with-fixed-mean․lisp file
File, vector-variance-with-mean.lisp: The gsll/tests/vector-variance-with-mean․lisp file
File, vector-variance.lisp: The gsll/tests/vector-variance․lisp file
File, vector.lisp: The gsll/data/vector․lisp file
File, wavelet.lisp: The gsll/wavelet․lisp file
File, wavetable-workspace.lisp: The gsll/fast-fourier-transforms/wavetable-workspace․lisp file
File, weibull.lisp: The gsll/random/weibull․lisp file
File, weibull.lisp: The gsll/tests/weibull․lisp file
File, zeta.lisp: The gsll/special-functions/zeta․lisp file
File, zeta.lisp: The gsll/tests/zeta․lisp file
fit-workspace: Public classes
flat.lisp: The gsll/random/flat․lisp file
flat.lisp: The gsll/tests/flat․lisp file
floating-point: The gsll/floating-point module
floating-point.lisp: The gsll/floating-point/floating-point․lisp file
foreign-array.lisp: The gsll/data/foreign-array․lisp file
forms.lisp: The gsll/init/forms․lisp file
forward.lisp: The gsll/fast-fourier-transforms/forward․lisp file
funcallable.lisp: The gsll/init/funcallable․lisp file

G
gamma-randist.lisp: The gsll/tests/gamma-randist․lisp file
gamma.lisp: The gsll/special-functions/gamma․lisp file
gamma.lisp: The gsll/random/gamma․lisp file
gamma.lisp: The gsll/tests/gamma․lisp file
gaussian-bivariate.lisp: The gsll/random/gaussian-bivariate․lisp file
gaussian-bivariate.lisp: The gsll/tests/gaussian-bivariate․lisp file
gaussian-tail.lisp: The gsll/random/gaussian-tail․lisp file
gaussian-tail.lisp: The gsll/tests/gaussian-tail․lisp file
gaussian.lisp: The gsll/random/gaussian․lisp file
gaussian.lisp: The gsll/tests/gaussian․lisp file
gegenbauer.lisp: The gsll/special-functions/gegenbauer․lisp file
gegenbauer.lisp: The gsll/tests/gegenbauer․lisp file
generalized.lisp: The gsll/eigensystems/generalized․lisp file
generate-examples.lisp: The gsll/init/generate-examples․lisp file
generators.lisp: The gsll/random/generators․lisp file
generic-failure-1: Public conditions
generic-failure-2: Public conditions
generic.lisp: The gsll/init/generic․lisp file
generic.lisp: The gsll/solve-minimize-fit/generic․lisp file
geometric.lisp: The gsll/random/geometric․lisp file
geometric.lisp: The gsll/tests/geometric․lisp file
givens.lisp: The gsll/tests/givens․lisp file
gsl-condition: Public conditions
gsl-division-by-zero: Public conditions
gsl-eof: Public conditions
gsl-version.lisp: The gsll/init/gsl-version․lisp file
gsll: The gsll system
gsll: The gsll package
gsll.asd: The gsll/gsll․asd file
gumbel1.lisp: The gsll/random/gumbel1․lisp file
gumbel1.lisp: The gsll/tests/gumbel1․lisp file
gumbel2.lisp: The gsll/random/gumbel2․lisp file
gumbel2.lisp: The gsll/tests/gumbel2․lisp file

H
hankel: Public classes
hankel.lisp: The gsll/hankel․lisp file
hankel.lisp: The gsll/tests/hankel․lisp file
higher-moments.lisp: The gsll/statistics/higher-moments․lisp file
higher-moments.lisp: The gsll/tests/higher-moments․lisp file
histogram: The gsll/histogram module
histogram: Public classes
histogram-c-tclass: Private classes
histogram-pdf: Public classes
histogram.lisp: The gsll/histogram/histogram․lisp file
histogram.lisp: The gsll/tests/histogram․lisp file
histogram2d: Public classes
histogram2d-pdf: Public classes
householder.lisp: The gsll/linear-algebra/householder․lisp file
householder.lisp: The gsll/tests/householder․lisp file
hypergeometric-randist.lisp: The gsll/tests/hypergeometric-randist․lisp file
hypergeometric.lisp: The gsll/special-functions/hypergeometric․lisp file
hypergeometric.lisp: The gsll/random/hypergeometric․lisp file
hypergeometric.lisp: The gsll/tests/hypergeometric․lisp file

I
ieee-modes.lisp: The gsll/floating-point/ieee-modes․lisp file
index-max.lisp: The gsll/tests/index-max․lisp file
init: The gsll/init module
init.lisp: The gsll/init/init․lisp file
input-domain: Public conditions
input-range: Public conditions
integration-workspace: Public classes
interface.lisp: The gsll/init/interface․lisp file
interpolation: The gsll/interpolation module
interpolation: Public classes
interpolation.lisp: The gsll/interpolation/interpolation․lisp file
interpolation.lisp: The gsll/tests/interpolation․lisp file
invalid-argument: Public conditions
invalid-pointer: Public conditions
invalid-tolerance: Public conditions
inverse-matrix-product.lisp: The gsll/tests/inverse-matrix-product․lisp file
inverse.lisp: The gsll/fast-fourier-transforms/inverse․lisp file

J
jacobian-not-improving: Public conditions

L
laguerre.lisp: The gsll/special-functions/laguerre․lisp file
laguerre.lisp: The gsll/tests/laguerre․lisp file
lambert.lisp: The gsll/special-functions/lambert․lisp file
lambert.lisp: The gsll/tests/lambert․lisp file
landau.lisp: The gsll/random/landau․lisp file
landau.lisp: The gsll/tests/landau․lisp file
laplace.lisp: The gsll/random/laplace․lisp file
laplace.lisp: The gsll/tests/laplace․lisp file
legendre.lisp: The gsll/special-functions/legendre․lisp file
legendre.lisp: The gsll/tests/legendre․lisp file
levin: Public classes
levin-truncated: Public classes
levy.lisp: The gsll/random/levy․lisp file
levy.lisp: The gsll/tests/levy․lisp file
libgsl.lisp: The gsll/init/libgsl․lisp file
linear-algebra: The gsll/linear-algebra module
linear-least-squares.lisp: The gsll/solve-minimize-fit/linear-least-squares․lisp file
linear-least-squares.lisp: The gsll/tests/linear-least-squares․lisp file
logarithm.lisp: The gsll/special-functions/logarithm․lisp file
logarithm.lisp: The gsll/tests/logarithm․lisp file
logarithmic.lisp: The gsll/random/logarithmic․lisp file
logarithmic.lisp: The gsll/tests/logarithmic․lisp file
logistic.lisp: The gsll/random/logistic․lisp file
logistic.lisp: The gsll/tests/logistic․lisp file
lognormal.lisp: The gsll/random/lognormal․lisp file
lognormal.lisp: The gsll/tests/lognormal․lisp file
lookup.lisp: The gsll/interpolation/lookup․lisp file
loss-of-accuracy: Public conditions
lu.lisp: The gsll/linear-algebra/lu․lisp file
lu.lisp: The gsll/tests/lu․lisp file

M
machine.lisp: The gsll/test-unit/machine․lisp file
mathematical: The gsll/mathematical module
mathematical.lisp: The gsll/mathematical/mathematical․lisp file
mathematical.lisp: The gsll/tests/mathematical․lisp file
mathieu: Public classes
mathieu.lisp: The gsll/special-functions/mathieu․lisp file
mathieu.lisp: The gsll/tests/mathieu․lisp file
matrix-add.lisp: The gsll/tests/matrix-add․lisp file
matrix-div.lisp: The gsll/tests/matrix-div․lisp file
matrix-generation.lisp: The gsll/linear-algebra/matrix-generation․lisp file
matrix-max-index.lisp: The gsll/tests/matrix-max-index․lisp file
matrix-max.lisp: The gsll/tests/matrix-max․lisp file
matrix-mean.lisp: The gsll/tests/matrix-mean․lisp file
matrix-min-index.lisp: The gsll/tests/matrix-min-index․lisp file
matrix-min.lisp: The gsll/tests/matrix-min․lisp file
matrix-minmax-index.lisp: The gsll/tests/matrix-minmax-index․lisp file
matrix-minmax.lisp: The gsll/tests/matrix-minmax․lisp file
matrix-mult.lisp: The gsll/tests/matrix-mult․lisp file
matrix-product-hermitian.lisp: The gsll/tests/matrix-product-hermitian․lisp file
matrix-product-nonsquare.lisp: The gsll/tests/matrix-product-nonsquare․lisp file
matrix-product-symmetric.lisp: The gsll/tests/matrix-product-symmetric․lisp file
matrix-product-triangular.lisp: The gsll/tests/matrix-product-triangular․lisp file
matrix-product.lisp: The gsll/tests/matrix-product․lisp file
matrix-set-all.lisp: The gsll/tests/matrix-set-all․lisp file
matrix-set-zero.lisp: The gsll/tests/matrix-set-zero․lisp file
matrix-standard-deviation-with-fixed-mean.lisp: The gsll/tests/matrix-standard-deviation-with-fixed-mean․lisp file
matrix-standard-deviation-with-mean.lisp: The gsll/tests/matrix-standard-deviation-with-mean․lisp file
matrix-standard-deviation.lisp: The gsll/tests/matrix-standard-deviation․lisp file
matrix-sub.lisp: The gsll/tests/matrix-sub․lisp file
matrix-swap.lisp: The gsll/tests/matrix-swap․lisp file
matrix-transpose-copy.lisp: The gsll/tests/matrix-transpose-copy․lisp file
matrix-transpose.lisp: The gsll/tests/matrix-transpose․lisp file
matrix-variance-with-fixed-mean.lisp: The gsll/tests/matrix-variance-with-fixed-mean․lisp file
matrix-variance-with-mean.lisp: The gsll/tests/matrix-variance-with-mean․lisp file
matrix-variance.lisp: The gsll/tests/matrix-variance․lisp file
matrix.lisp: The gsll/data/matrix․lisp file
mean-variance.lisp: The gsll/statistics/mean-variance․lisp file
median-percentile.lisp: The gsll/statistics/median-percentile․lisp file
median-percentile.lisp: The gsll/tests/median-percentile․lisp file
memory-allocation-failure: Public conditions
minimization-multi.lisp: The gsll/solve-minimize-fit/minimization-multi․lisp file
minimization-multi.lisp: The gsll/tests/minimization-multi․lisp file
minimization-one.lisp: The gsll/solve-minimize-fit/minimization-one․lisp file
minimization-one.lisp: The gsll/tests/minimization-one․lisp file
mksa.lisp: The gsll/physical-constants/mksa․lisp file
mobject: Private classes
mobject.lisp: The gsll/init/mobject․lisp file
Module, calculus: The gsll/calculus module
Module, data: The gsll/data module
Module, eigensystems: The gsll/eigensystems module
Module, fast-fourier-transforms: The gsll/fast-fourier-transforms module
Module, floating-point: The gsll/floating-point module
Module, histogram: The gsll/histogram module
Module, init: The gsll/init module
Module, interpolation: The gsll/interpolation module
Module, linear-algebra: The gsll/linear-algebra module
Module, mathematical: The gsll/mathematical module
Module, ordinary-differential-equations: The gsll/ordinary-differential-equations module
Module, physical-constants: The gsll/physical-constants module
Module, random: The gsll/random module
Module, solve-minimize-fit: The gsll/solve-minimize-fit module
Module, special-functions: The gsll/special-functions module
Module, statistics: The gsll/statistics module
Module, test-unit: The gsll/test-unit module
Module, tests: The gsll/tests module
monte-carlo-miser: Public classes
monte-carlo-plain: Public classes
monte-carlo-structs.lisp: The gsll/calculus/monte-carlo-structs․lisp file
monte-carlo-vegas: Public classes
monte-carlo.lisp: The gsll/calculus/monte-carlo․lisp file
monte-carlo.lisp: The gsll/tests/monte-carlo․lisp file
multi-dimensional-minimizer-f: Public classes
multi-dimensional-minimizer-fdf: Public classes
multi-dimensional-root-solver-f: Public classes
multi-dimensional-root-solver-fdf: Public classes
multinomial.lisp: The gsll/random/multinomial․lisp file
multinomial.lisp: The gsll/tests/multinomial․lisp file

N
negative-binomial.lisp: The gsll/random/negative-binomial․lisp file
negative-binomial.lisp: The gsll/tests/negative-binomial․lisp file
no-progress: Public conditions
nonconformant-dimensions: Public conditions
nonlinear-fdffit: Public classes
nonlinear-ffit: Public classes
nonlinear-least-squares.lisp: The gsll/solve-minimize-fit/nonlinear-least-squares․lisp file
nonlinear-least-squares.lisp: The gsll/tests/nonlinear-least-squares․lisp file
nonsquare-matrix: Public conditions
nonsymmetric-generalized.lisp: The gsll/eigensystems/nonsymmetric-generalized․lisp file
nonsymmetric.lisp: The gsll/eigensystems/nonsymmetric․lisp file
ntuple-data-tclass: Private classes
ntuple.lisp: The gsll/histogram/ntuple․lisp file
ntuple.lisp: The gsll/tests/ntuple․lisp file
num.lisp: The gsll/physical-constants/num․lisp file
numerical-differentiation.lisp: The gsll/calculus/numerical-differentiation․lisp file
numerical-differentiation.lisp: The gsll/tests/numerical-differentiation․lisp file
numerical-integration-with-tables.lisp: The gsll/calculus/numerical-integration-with-tables․lisp file
numerical-integration.lisp: The gsll/calculus/numerical-integration․lisp file
numerical-integration.lisp: The gsll/tests/numerical-integration․lisp file

O
obsolete-gsl-version: Private conditions
ode-control: Private classes
ode-evolution: Public classes
ode-example.lisp: The gsll/ordinary-differential-equations/ode-example․lisp file
ode-stepper: Public classes
ode-struct.lisp: The gsll/ordinary-differential-equations/ode-struct․lisp file
ode-system.lisp: The gsll/ordinary-differential-equations/ode-system․lisp file
ode.lisp: The gsll/tests/ode․lisp file
one-dimensional-minimizer: Public classes
one-dimensional-root-solver-f: Public classes
one-dimensional-root-solver-fdf: Public classes
operations.lisp: The gsll/histogram/operations․lisp file
ordinary-differential-equations: The gsll/ordinary-differential-equations module
overflow: Public conditions

P
Package, gsll: The gsll package
pareto.lisp: The gsll/random/pareto․lisp file
pareto.lisp: The gsll/tests/pareto․lisp file
permutation: Public classes
permutation.lisp: The gsll/data/permutation․lisp file
permutation.lisp: The gsll/tests/permutation․lisp file
physical-constants: The gsll/physical-constants module
poisson.lisp: The gsll/random/poisson․lisp file
poisson.lisp: The gsll/tests/poisson․lisp file
polynomial-complex-workspace: Public classes
polynomial.lisp: The gsll/polynomial․lisp file
polynomial.lisp: The gsll/tests/polynomial․lisp file
power.lisp: The gsll/special-functions/power․lisp file
power.lisp: The gsll/tests/power․lisp file
probability-distribution.lisp: The gsll/histogram/probability-distribution․lisp file
psi.lisp: The gsll/special-functions/psi․lisp file
psi.lisp: The gsll/tests/psi․lisp file

Q
qawo-table: Public classes
qaws-table: Public classes
qr.lisp: The gsll/linear-algebra/qr․lisp file
qr.lisp: The gsll/tests/qr․lisp file
qrpt.lisp: The gsll/linear-algebra/qrpt․lisp file
qrpt.lisp: The gsll/tests/qrpt․lisp file
quasi-random-number-generator: Public classes
quasi-random-number-generators.lisp: The gsll/tests/quasi-random-number-generators․lisp file
quasi.lisp: The gsll/random/quasi․lisp file

R
random: The gsll/random module
random-number-generator: Public classes
random-number-generators.lisp: The gsll/tests/random-number-generators․lisp file
rank-1-update.lisp: The gsll/tests/rank-1-update․lisp file
rayleigh-tail.lisp: The gsll/random/rayleigh-tail․lisp file
rayleigh-tail.lisp: The gsll/tests/rayleigh-tail․lisp file
rayleigh.lisp: The gsll/random/rayleigh․lisp file
rayleigh.lisp: The gsll/tests/rayleigh․lisp file
return-structures.lisp: The gsll/special-functions/return-structures․lisp file
rng-types.lisp: The gsll/random/rng-types․lisp file
roots-multi.lisp: The gsll/solve-minimize-fit/roots-multi․lisp file
roots-multi.lisp: The gsll/tests/roots-multi․lisp file
roots-one.lisp: The gsll/solve-minimize-fit/roots-one․lisp file
roots-one.lisp: The gsll/tests/roots-one․lisp file
roundoff-failure: Public conditions
row.lisp: The gsll/tests/row․lisp file
runaway-iteration: Public conditions

S
sanity-check-failure: Public conditions
scale.lisp: The gsll/tests/scale․lisp file
scaled-control: Public classes
select-direction.lisp: The gsll/fast-fourier-transforms/select-direction․lisp file
series-acceleration.lisp: The gsll/series-acceleration․lisp file
series-acceleration.lisp: The gsll/tests/series-acceleration․lisp file
series-struct.lisp: The gsll/series-struct․lisp file
set-basis.lisp: The gsll/tests/set-basis․lisp file
set-identity.lisp: The gsll/tests/set-identity․lisp file
setf-column.lisp: The gsll/tests/setf-column․lisp file
setf-row.lisp: The gsll/tests/setf-row․lisp file
sf-result.lisp: The gsll/special-functions/sf-result․lisp file
shuffling-sampling.lisp: The gsll/random/shuffling-sampling․lisp file
shuffling-sampling.lisp: The gsll/tests/shuffling-sampling․lisp file
simulated-annealing-parameters-tclass: Private classes
simulated-annealing.lisp: The gsll/solve-minimize-fit/simulated-annealing․lisp file
singularity: Public conditions
solve-minimize-fit: The gsll/solve-minimize-fit module
solver-struct.lisp: The gsll/solve-minimize-fit/solver-struct․lisp file
sort-matrix-largest.lisp: The gsll/tests/sort-matrix-largest․lisp file
sort-matrix-smallest.lisp: The gsll/tests/sort-matrix-smallest․lisp file
sort-matrix.lisp: The gsll/tests/sort-matrix․lisp file
sort-vector-index.lisp: The gsll/tests/sort-vector-index․lisp file
sort-vector-largest-index.lisp: The gsll/tests/sort-vector-largest-index․lisp file
sort-vector-largest.lisp: The gsll/tests/sort-vector-largest․lisp file
sort-vector-smallest-index.lisp: The gsll/tests/sort-vector-smallest-index․lisp file
sort-vector-smallest.lisp: The gsll/tests/sort-vector-smallest․lisp file
sort-vector.lisp: The gsll/tests/sort-vector․lisp file
sorting.lisp: The gsll/sorting․lisp file
special-functions: The gsll/special-functions module
spherical-vector.lisp: The gsll/random/spherical-vector․lisp file
spherical-vector.lisp: The gsll/tests/spherical-vector․lisp file
spline: Public classes
spline-example.lisp: The gsll/interpolation/spline-example․lisp file
standard-control: Public classes
statistics: The gsll/statistics module
statistics.lisp: The gsll/histogram/statistics․lisp file
stepping.lisp: The gsll/ordinary-differential-equations/stepping․lisp file
Structure, exponent-fit-data: Private structures
svd.lisp: The gsll/linear-algebra/svd․lisp file
svd.lisp: The gsll/tests/svd․lisp file
swap-columns.lisp: The gsll/tests/swap-columns․lisp file
swap-elements.lisp: The gsll/tests/swap-elements․lisp file
swap-row-column.lisp: The gsll/tests/swap-row-column․lisp file
swap-rows.lisp: The gsll/tests/swap-rows․lisp file
symmetric-hermitian.lisp: The gsll/eigensystems/symmetric-hermitian․lisp file
synchrotron.lisp: The gsll/special-functions/synchrotron․lisp file
synchrotron.lisp: The gsll/tests/synchrotron․lisp file
System, gsll: The gsll system

T
table-limit-exceeded: Public conditions
tdist.lisp: The gsll/random/tdist․lisp file
tdist.lisp: The gsll/tests/tdist․lisp file
test-unit: The gsll/test-unit module
tests: The gsll/tests module
tests.lisp: The gsll/random/tests․lisp file
transport.lisp: The gsll/special-functions/transport․lisp file
transport.lisp: The gsll/tests/transport․lisp file
trigonometry.lisp: The gsll/special-functions/trigonometry․lisp file
trigonometry.lisp: The gsll/tests/trigonometry․lisp file
types.lisp: The gsll/init/types․lisp file
types.lisp: The gsll/interpolation/types․lisp file

U
underflow: Public conditions
unimplemented-feature: Public conditions
unpack.lisp: The gsll/fast-fourier-transforms/unpack․lisp file
unspecified-errno: Private conditions
unsupported-feature: Public conditions
updating-accessing.lisp: The gsll/histogram/updating-accessing․lisp file
utility.lisp: The gsll/init/utility․lisp file

V
vector-add.lisp: The gsll/tests/vector-add․lisp file
vector-div.lisp: The gsll/tests/vector-div․lisp file
vector-max-index.lisp: The gsll/tests/vector-max-index․lisp file
vector-max.lisp: The gsll/tests/vector-max․lisp file
vector-mean.lisp: The gsll/tests/vector-mean․lisp file
vector-min-index.lisp: The gsll/tests/vector-min-index․lisp file
vector-min.lisp: The gsll/tests/vector-min․lisp file
vector-minmax-index.lisp: The gsll/tests/vector-minmax-index․lisp file
vector-minmax.lisp: The gsll/tests/vector-minmax․lisp file
vector-mult.lisp: The gsll/tests/vector-mult․lisp file
vector-reverse.lisp: The gsll/tests/vector-reverse․lisp file
vector-set-all.lisp: The gsll/tests/vector-set-all․lisp file
vector-set-zero.lisp: The gsll/tests/vector-set-zero․lisp file
vector-standard-deviation-with-fixed-mean.lisp: The gsll/tests/vector-standard-deviation-with-fixed-mean․lisp file
vector-standard-deviation-with-mean.lisp: The gsll/tests/vector-standard-deviation-with-mean․lisp file
vector-standard-deviation.lisp: The gsll/tests/vector-standard-deviation․lisp file
vector-sub.lisp: The gsll/tests/vector-sub․lisp file
vector-swap.lisp: The gsll/tests/vector-swap․lisp file
vector-variance-with-fixed-mean.lisp: The gsll/tests/vector-variance-with-fixed-mean․lisp file
vector-variance-with-mean.lisp: The gsll/tests/vector-variance-with-mean․lisp file
vector-variance.lisp: The gsll/tests/vector-variance․lisp file
vector.lisp: The gsll/data/vector․lisp file

W
wavelet: Public classes
wavelet-workspace: Public classes
wavelet.lisp: The gsll/wavelet․lisp file
wavetable-workspace.lisp: The gsll/fast-fourier-transforms/wavetable-workspace․lisp file
weibull.lisp: The gsll/random/weibull․lisp file
weibull.lisp: The gsll/tests/weibull․lisp file

Y
y-control: Public classes
yp-control: Public classes

Z
zeta.lisp: The gsll/special-functions/zeta․lisp file
zeta.lisp: The gsll/tests/zeta․lisp file