The gsll Reference Manual

absolute-deviation.lisp.

Source

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.

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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

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.

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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.

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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.

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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.

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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.

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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

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

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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.

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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.

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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.

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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

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

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).

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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)}.

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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).

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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).

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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).

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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).

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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

Source

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

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

Source

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

Source

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

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

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

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

Source

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

Source

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

Source

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

Source

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

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

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

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

Source

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

Source

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

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

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

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

Source

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

Source

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

Source

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

Source

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

Source

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)) ¶

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)) ¶

Source: roots-one.lisp.

Method: iterate ((solver one-dimensional-root-solver-f)) ¶

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

median-percentile.lisp.

Source

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

Source

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

Source

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

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

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

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

median-percentile.lisp.

Source

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

Source

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

Source

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

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

Source

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

Source

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

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

Source

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

Source

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

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

Source

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

Source

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

Source

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

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

Source

statistics.lisp.

Methods

Method: sigma ((histogram histogram2d)) ¶

Method: sigma ((histogram histogram)) ¶

Generic Function: size (object) ¶

The size of the GSL object.

Package

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

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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

Source

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

Source

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

Source

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

Source

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

Source

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

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

Source

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

Source

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

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

Source

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

Source

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

Source

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

Source

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

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

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

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

Source

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

Source

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

Source

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

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

absolute-deviation.lisp.

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

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

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.

Next: Conditions, Previous: Generic functions, Up: Public Interface [Contents][Index]

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.

Next: Classes, Previous: Standalone methods, Up: Public Interface [Contents][Index]

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

arithmetic-error.
warning.

Direct subclasses

Direct methods

error-number.
error-text.
explanation.
line-number.
source-file.

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

Source

Direct superclasses

division-by-zero.
gsl-condition.

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

end-of-file.

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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

Source

Direct superclasses

Direct methods

error-number.
error-text.

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.

Previous: Conditions, Up: Public Interface [Contents][Index]

5.1.10 Classes

Class: acceleration ¶

The GSL representation of the acceleration for interpolation.

Package

Source

lookup.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: basis-spline ¶

The GSL representation of the basis spline.

Package

Source

basis-splines.lisp.

Direct superclasses

Direct methods

allocate.
evaluate.
initialize-instance.
order.

Class: chebyshev ¶

The GSL representation of the Chebyshev series.

Package

Source

chebyshev.lisp.

Direct superclasses

Direct methods

allocate.
evaluate.
initialize-instance.
order.
reinitialize-instance.
size.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-gen ¶

The GSL representation of the generalized nonsymmetric eigenvalue workspace.

Package

nonsymmetric-generalized.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-genherm ¶

The GSL representation of the hermitian generalized eigenvalue workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-genhermv ¶

The GSL representation of the hermitian generalized eigensystem workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-gensymm ¶

The GSL representation of the symmetric generalized eigenvalue workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-gensymmv ¶

The GSL representation of the symmetric generalized eigensystem workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-genv ¶

The GSL representation of the generalized nonsymmetric eigenvector and eigenvalue workspace.

Package

nonsymmetric-generalized.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-herm ¶

The GSL representation of the Hermitian eigenvalue workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-hermv ¶

The GSL representation of the Hermitian eigensystem workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-nonsymm ¶

The GSL representation of the non-symmetric eigenvalue workspace.

Package

Source

nonsymmetric.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-nonsymmv ¶

The GSL representation of the non-symmetric eigenvector and eigenvalue workspace.

Package

Source

nonsymmetric.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-symm ¶

The GSL representation of the symmetric eigenvalue workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: eigen-symmv ¶

The GSL representation of the symmetric eigensystem workspace.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: fit-workspace ¶

The GSL representation of the multi-dimensional root solver with function only.

Package

linear-least-squares.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: hankel ¶

The GSL representation of the discrete Hankel Transform.

Package

Source

hankel.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: histogram ¶

The GSL representation of the one-dimensional histogram, including bin boundaries and bin contents.

Package

Source

Direct superclasses

Direct methods

Class: histogram-pdf ¶

The GSL representation of the one-dimensional histogram PDF.

Package

probability-distribution.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.
sample.
sample.

Class: histogram2d ¶

The GSL representation of the two-dimensional histogram, including bin boundaries and bin contents..

Package

Source

Direct superclasses

Direct methods

Class: histogram2d-pdf ¶

The GSL representation of the two-dimensional histogram PDF.

Package

probability-distribution.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.
sample.
sample.

Class: integration-workspace ¶

The GSL representation of the integration workspace.

Package

numerical-integration.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: interpolation ¶

The GSL representation of the interpolation.

Package

Source

interpolation.lisp.

Direct superclasses

Direct methods

allocate.
evaluate.
evaluate-derivative.
evaluate-integral.
evaluate-second-derivative.
initialize-instance.
minimum-size.
name.
reinitialize-instance.

Class: levin ¶

The GSL representation of the Levin u-transform.

Package

series-acceleration.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: levin-truncated ¶

The GSL representation of the truncated Levin u-transform.

Package

series-acceleration.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: mathieu ¶

The GSL representation of the workspace for Mathieu functions.

Package

Source

mathieu.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: monte-carlo-miser ¶

The GSL representation of the miser Monte Carlo integration.

Package

Source

monte-carlo.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
(setf parameter).
parameter.
reinitialize-instance.

Class: monte-carlo-plain ¶

The GSL representation of the plain Monte Carlo integration.

Package

Source

monte-carlo.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: monte-carlo-vegas ¶

The GSL representation of the vegas Monte Carlo integration.

Package

Source

monte-carlo.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
(setf parameter).
parameter.
reinitialize-instance.

Class: multi-dimensional-minimizer-f ¶

The GSL representation of the multi-dimensional minimizer with function only.

Package

minimization-multi.lisp.

Source

Direct superclasses

Direct methods

allocate.
function-value.
initialize-instance.
iterate.
name.
reinitialize-instance.
size.
solution.

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

minimization-multi.lisp.

Source

Direct superclasses

Direct methods

allocate.
function-value.
initialize-instance.
iterate.
name.
reinitialize-instance.
solution.

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

Source

roots-multi.lisp.

Direct superclasses

Direct methods

allocate.
function-value.
initialize-instance.
iterate.
last-step.
name.
reinitialize-instance.
solution.

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

Source

roots-multi.lisp.

Direct superclasses

Direct methods

allocate.
function-value.
initialize-instance.
iterate.
last-step.
name.
reinitialize-instance.
solution.

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

nonlinear-least-squares.lisp.

Source

Direct superclasses

Direct methods

allocate.
function-value.
initialize-instance.
iterate.
last-step.
name.
reinitialize-instance.
solution.

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

nonlinear-least-squares.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
iterate.
name.
reinitialize-instance.
solution.

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

Source

evolution.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: ode-stepper ¶

The GSL representation of the stepper for ordinary differential equations.

Package

Source

stepping.lisp.

Direct superclasses

callback-included-cl.

Direct methods

allocate.
initialize-instance.
name.
reinitialize-instance.

Direct slots

Slot: dimension-names ¶

Allocation: :class
Initform: (quote (gsll::dimension))

Class: one-dimensional-minimizer ¶

The GSL representation of the one-dimensional minimizer.

Package

Source

minimization-one.lisp.

Direct superclasses

Direct methods

allocate.
function-value.
initialize-instance.
iterate.
name.
reinitialize-instance.
solution.

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

Source

roots-one.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
iterate.
name.
reinitialize-instance.
solution.

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

Source

roots-one.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
iterate.
name.
reinitialize-instance.
solution.

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

Source

Direct superclasses

Direct methods

Class: polynomial-complex-workspace ¶

The GSL representation of the complex workspace for polynomials.

Package

Source

polynomial.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: qawo-table ¶

The GSL representation of the table for QAWO numerical integration method.

Package

numerical-integration-with-tables.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: qaws-table ¶

The GSL representation of the table for QAWS numerical integration method.

Package

numerical-integration-with-tables.lisp.

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: quasi-random-number-generator ¶

The GSL representation of the quasi random number generator.

Package

Source

quasi.lisp.

Direct superclasses

Direct methods

allocate.
copy.
initialize-instance.
name.
reinitialize-instance.
rng-state.
size.

Class: random-number-generator ¶

The GSL representation of the random number generator.

Package

Source

generators.lisp.

Direct superclasses

Direct methods

Class: scaled-control ¶

The GSL representation of the scaled control for ordinary differential equations.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: spline ¶

The GSL representation of the spline.

Package

Source

interpolation.lisp.

Direct superclasses

Direct methods

allocate.
evaluate.
evaluate-derivative.
evaluate-integral.
evaluate-second-derivative.
initialize-instance.
minimum-size.
name.
reinitialize-instance.

Class: standard-control ¶

The GSL representation of the standard control for ordinary differential equations.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: wavelet ¶

The GSL representation of the wavelet.

Package

Source

wavelet.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.
name.

Class: wavelet-workspace ¶

The GSL representation of the wavelet workspace.

Package

Source

wavelet.lisp.

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: y-control ¶

The GSL representation of the y control for ordinary differential equations.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Class: yp-control ¶

The GSL representation of the yp control for ordinary differential equations.

Package

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.
reinitialize-instance.

Previous: Public Interface, Up: Definitions [Contents][Index]

Next: Special variables, Previous: Internals, Up: Internals [Contents][Index]

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.

Next: Macros, Previous: Constants, Up: Internals [Contents][Index]

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.

Next: Ordinary functions, Previous: Special variables, Up: Internals [Contents][Index]

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.

Next: Generic functions, Previous: Macros, Up: Internals [Contents][Index]

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) ¶

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.

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.

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.

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.

Next: Conditions, Previous: Ordinary functions, Up: Internals [Contents][Index]

5.2.5 Generic functions

Generic Function: alloc-from-block (object blockptr) ¶

Allocate memory for the GSL struct given a block pointer.

Package

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

Source

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

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

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

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

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

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

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

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

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

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

Source

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

Source

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

Source

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

Source

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

Source

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

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

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

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

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

Methods

Reader Method: gsl-name ((condition obsolete-gsl-version)) ¶

Source: defmfun-single.lisp.
Target Slot: gsl-name.

Generic Reader: gsl-version (condition) ¶

Package

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

Source

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

Source

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

Source

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

Source

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

Source

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

Methods

Reader Method: line-number ((condition gsl-condition)) ¶

Source: conditions.lisp.
Target Slot: line-number.

Generic Function: mpointer (object) ¶

Package

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

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

Methods

Reader Method: source-file ((condition gsl-condition)) ¶

Source: conditions.lisp.
Target Slot: source-file.

Next: Structures, Previous: Generic functions, Up: Internals [Contents][Index]

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

Source

defmfun-single.lisp.

Direct superclasses

error.

Direct methods

gsl-name.
gsl-version.
name.

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

Source

Direct superclasses

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.

Next: Classes, Previous: Conditions, Up: Internals [Contents][Index]

5.2.7 Structures

Structure: exponent-fit-data ¶

Package

nonlinear-least-squares.lisp.

Source

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).

Previous: Structures, Up: Internals [Contents][Index]

5.2.8 Classes

Class: callback-included ¶

A mobject that includes a callback function or functions to GSL.

Package

callback-included.lisp.

Source

Direct superclasses

Direct subclasses

callback-included-cl.
chebyshev.
multi-dimensional-minimizer-f.
multi-dimensional-minimizer-fdf.
multi-dimensional-root-solver-f.
multi-dimensional-root-solver-fdf.
nonlinear-fdffit.
nonlinear-ffit.
one-dimensional-minimizer.
one-dimensional-root-solver-f.
one-dimensional-root-solver-fdf.

Direct methods

cbinfo.
dimension-names.
dimensions.
funcallables.
functions.
print-object.
scalarsp.

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

callback-included.lisp.

Source

Direct superclasses

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

Source

combination.lisp.

Direct superclasses

vector-unsigned-byte-64.

Direct methods

copy.
initialize-instance.
print-object.
size.
validp.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

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

Source

Direct superclasses

Direct methods

allocate.
initialize-instance.

Class: histogram-c-tclass ¶

Package

Source

Direct superclasses

foreign-struct-type.
translatable-foreign-type.

Class: mobject ¶

Package

Source

Direct subclasses

acceleration.
basis-spline.
callback-included.
discrete-random.
eigen-gen.
eigen-genherm.
eigen-genhermv.
eigen-gensymm.
eigen-gensymmv.
eigen-genv.
eigen-herm.
eigen-hermv.
eigen-nonsymm.
eigen-nonsymmv.
eigen-symm.
eigen-symmv.
fft-complex-wavetable-double-float.
fft-complex-wavetable-single-float.
fft-complex-workspace-double-float.
fft-complex-workspace-single-float.
fft-half-complex-wavetable-double-float.
fft-half-complex-wavetable-single-float.
fft-real-wavetable-double-float.
fft-real-wavetable-single-float.
fft-real-workspace-double-float.
fft-real-workspace-single-float.
fit-workspace.
hankel.
histogram.
histogram-pdf.
histogram2d.
histogram2d-pdf.
integration-workspace.
interpolation.
levin.
levin-truncated.
mathieu.
monte-carlo-miser.
monte-carlo-plain.
monte-carlo-vegas.
ode-control.
ode-evolution.
permutation.
polynomial-complex-workspace.
qawo-table.
qaws-table.
quasi-random-number-generator.
random-number-generator.
spline.
wavelet.
wavelet-workspace.

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

Source

ntuple.lisp.

Direct superclasses

foreign-struct-type.
translatable-foreign-type.

Class: ode-control ¶

Objects used for control of ordinary differential equation integration.

Package

Source

Direct superclasses

Direct subclasses

scaled-control.
standard-control.
y-control.
yp-control.

Direct methods

name.

Class: simulated-annealing-parameters-tclass ¶

Package