%module "Math::GSL::BLAS" %include "typemaps.i" %include "gsl_typemaps.i" %apply float *OUTPUT { float *result }; %apply double *OUTPUT { double *result }; %apply double *OUTPUT { double c[], double s[] }; %{ #include "gsl/gsl_blas.h" #include "gsl/gsl_blas_types.h" %} %include "gsl/gsl_blas.h" %include "gsl/gsl_blas_types.h" %perlcode %{ @EXPORT_OK_level1 = qw/ gsl_blas_sdsdot gsl_blas_dsdot gsl_blas_sdot gsl_blas_ddot gsl_blas_cdotu gsl_blas_cdotc gsl_blas_zdotu gsl_blas_zdotc gsl_blas_snrm2 gsl_blas_sasum gsl_blas_dnrm2 gsl_blas_dasum gsl_blas_scnrm2 gsl_blas_scasum gsl_blas_dznrm2 gsl_blas_dzasum gsl_blas_isamax gsl_blas_idamax gsl_blas_icamax gsl_blas_izamax gsl_blas_sswap gsl_blas_scopy gsl_blas_saxpy gsl_blas_dswap gsl_blas_dcopy gsl_blas_daxpy gsl_blas_cswap gsl_blas_ccopy gsl_blas_caxpy gsl_blas_zswap gsl_blas_zcopy gsl_blas_zaxpy gsl_blas_srotg gsl_blas_srotmg gsl_blas_srot gsl_blas_srotm gsl_blas_drotg gsl_blas_drotmg gsl_blas_drot gsl_blas_drotm gsl_blas_sscal gsl_blas_dscal gsl_blas_cscal gsl_blas_zscal gsl_blas_csscal gsl_blas_zdscal /; @EXPORT_OK_level2 = qw/ gsl_blas_sgemv gsl_blas_strmv gsl_blas_strsv gsl_blas_dgemv gsl_blas_dtrmv gsl_blas_dtrsv gsl_blas_cgemv gsl_blas_ctrmv gsl_blas_ctrsv gsl_blas_zgemv gsl_blas_ztrmv gsl_blas_ztrsv gsl_blas_ssymv gsl_blas_sger gsl_blas_ssyr gsl_blas_ssyr2 gsl_blas_dsymv gsl_blas_dger gsl_blas_dsyr gsl_blas_dsyr2 gsl_blas_chemv gsl_blas_cgeru gsl_blas_cgerc gsl_blas_cher gsl_blas_cher2 gsl_blas_zhemv gsl_blas_zgeru gsl_blas_zgerc gsl_blas_zher gsl_blas_zher2 /; @EXPORT_OK_level3 = qw/ gsl_blas_sgemm gsl_blas_ssymm gsl_blas_ssyrk gsl_blas_ssyr2k gsl_blas_strmm gsl_blas_strsm gsl_blas_dgemm gsl_blas_dsymm gsl_blas_dsyrk gsl_blas_dsyr2k gsl_blas_dtrmm gsl_blas_dtrsm gsl_blas_cgemm gsl_blas_csymm gsl_blas_csyrk gsl_blas_csyr2k gsl_blas_ctrmm gsl_blas_ctrsm gsl_blas_zgemm gsl_blas_zsymm gsl_blas_zsyrk gsl_blas_zsyr2k gsl_blas_ztrmm gsl_blas_ztrsm gsl_blas_chemm gsl_blas_cherk gsl_blas_cher2k gsl_blas_zhemm gsl_blas_zherk gsl_blas_zher2k /; @EXPORT_OK = (@EXPORT_OK_level1, @EXPORT_OK_level2, @EXPORT_OK_level3); %EXPORT_TAGS = ( all => [ @EXPORT_OK ], level1 => [ @EXPORT_OK_level1 ], level2 => [ @EXPORT_OK_level2 ], level3 => [ @EXPORT_OK_level3 ], ); __END__ =head1 NAME Math::GSL::BLAS - Basic Linear Algebra Subprograms =head1 SYNOPSIS use Math::GSL::QRNG qw/:all/; =head1 DESCRIPTION The functions of this module are divised into 3 levels: =head2 Level 1 - Vector operations =over 3 =item C =item C =item C =item C - This function computes the scalar product x^T y for the vectors $x and $y. The function returns two values, the first is 0 if the operation suceeded, 1 otherwise and the second value is the result of the computation. =item C =item C =item C - This function computes the complex scalar product x^T y for the complex vectors $x and $y, returning the result in the complex number $dotu. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the complex conjugate scalar product x^H y for the complex vectors $x and $y, returning the result in the complex number $dotc. The function returns 0 if the operation suceeded, 1 otherwise. =item C =item C =item C - This function computes the Euclidean norm ||x||_2 = \sqrt {\sum x_i^2} of the vector $x. =item C - This function computes the absolute sum \sum |x_i| of the elements of the vector $x. =item C =item C =item C - This function computes the Euclidean norm of the complex vector $x, ||x||_2 = \sqrt {\sum (\Re(x_i)^2 + \Im(x_i)^2)}. =item C - This function computes the sum of the magnitudes of the real and imaginary parts of the complex vector $x, \sum |\Re(x_i)| + |\Im(x_i)|. =item C =item C =item C =item C =item C =item C =item C =item C - This function exchanges the elements of the vectors $x and $y. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function copies the elements of the vector $x into the vector $y. The function returns 0 if the operation suceeded, 1 otherwise. =item C - These functions compute the sum $y = $alpha * $x + $y for the vectors $x and $y. =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C - This function applies a Givens rotation (x', y') = (c x + s y, -s x + c y) to the vectors $x, $y. =item C =item C =item C - This function rescales the vector $x by the multiplicative factor $alpha. =item C =item C =item C =item C =back =head2 Level 2 - Matrix-vector operations =over 3 =item C =item C =item C =item C - This function computes the matrix-vector product and sum y = \alpha op(A) x + \beta y, where op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans (constant values coming from the CBLAS module). $A is a matrix and $x and $y are vectors. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the matrix-vector product x = op(A) x for the triangular matrix $A, where op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans (constant values coming from the CBLAS module). When $Uplo is $CblasUpper then the upper triangle of $A is used, and when $Uplo is $CblasLower then the lower triangle of $A is used. If $Diag is $CblasNonUnit then the diagonal of the matrix is used, but if $Diag is $CblasUnit then the diagonal elements of the matrix $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes inv(op(A)) x for the vector $x, where op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans (constant values coming from the CBLAS module). When $Uplo is $CblasUpper then the upper triangle of $A is used, and when $Uplo is $CblasLower then the lower triangle of $A is used. If $Diag is $CblasNonUnit then the diagonal of the matrix is used, but if $Diag is $CblasUnit then the diagonal elements of the matrix $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise. =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C =item C - This function computes the rank-1 update A = alpha x y^T + A of the matrix $A. $x and $y are vectors. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the symmetric rank-1 update A = \alpha x x^T + A of the symmetric matrix $A and the vector $x. Since the matrix $A is symmetric only its upper half or lower half need to be stored. When $Uplo is $CblasUpper then the upper triangle and diagonal of $A are used, and when $Uplo is $CblasLower then the lower triangle and diagonal of $A are used. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the symmetric rank-2 update A = \alpha x y^T + \alpha y x^T + A of the symmetric matrix $A, the vector $x and vector $y. Since the matrix $A is symmetric only its upper half or lower half need to be stored. When $Uplo is $CblasUpper then the upper triangle and diagonal of $A are used, and when $Uplo is $CblasLower then the lower triangle and diagonal of $A are used. =item C =item C =item C =item C =item C =item C =item C - This function computes the rank-1 update A = alpha x y^T + A of the complex matrix $A. $alpha is a complex number and $x and $y are complex vectors. The function returns 0 if the operation suceeded, 1 otherwise. =item C =item C - This function computes the hermitian rank-1 update A = \alpha x x^H + A of the hermitian matrix $A and of the complex vector $x. Since the matrix $A is hermitian only its upper half or lower half need to be stored. When $Uplo is $CblasUpper then the upper triangle and diagonal of $A are used, and when $Uplo is $CblasLower then the lower triangle and diagonal of $A are used. The imaginary elements of the diagonal are automatically set to zero. The function returns 0 if the operation suceeded, 1 otherwise. =item C =back =head2 Level 3 - Matrix-matrix operations =over 3 =item C =item C =item C =item C =item C =item C =item C - This function computes the matrix-matrix product and sum C = \alpha op(A) op(B) + \beta C where op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans and similarly for the parameter $TransB. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the matrix-matrix product and sum C = \alpha A B + \beta C for $Side is $CblasLeft and C = \alpha B A + \beta C for $Side is $CblasRight, where the matrix $A is symmetric. When $Uplo is $CblasUpper then the upper triangle and diagonal of $A are used, and when $Uplo is $CblasLower then the lower triangle and diagonal of $A are used. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes 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. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes a rank-2k update of the symmetric matrix $C, C = \alpha A B^T + \alpha B A^T + \beta C when $Trans is $CblasNoTrans and C = \alpha A^T B + \alpha B^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. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the matrix-matrix product B = \alpha op(A) B for $Side is $CblasLeft and B = \alpha B op(A) for $Side is $CblasRight. The matrix $A is triangular and op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans. When $Uplo is $CblasUpper then the upper triangle of $A is used, and when $Uplo is $CblasLower then the lower triangle of $A is used. If $Diag is $CblasNonUnit then the diagonal of $A is used, but if $Diag is $CblasUnit then the diagonal elements of the matrix $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes the inverse-matrix matrix product B = \alpha op(inv(A))B for $Side is $CblasLeft and B = \alpha B op(inv(A)) for $Side is $CblasRight. The matrix $A is triangular and op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans. When $Uplo is $CblasUpper then the upper triangle of $A is used, and when $Uplo is $CblasLower then the lower triangle of $A is used. If $Diag is $CblasNonUnit then the diagonal of $A is used, but if $Diag is $CblasUnit then the diagonal elements of the matrix $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise. =item C =item C =item C =item C =item C =item C =item C - This function computes the matrix-matrix product and sum C = \alpha op(A) op(B) + \beta C where op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans and similarly for the parameter $TransB. The function returns 0 if the operation suceeded, 1 otherwise. $A, $B and $C are complex matrices =item C - This function computes the matrix-matrix product and sum C = \alpha A B + \beta C for $Side is $CblasLeft and C = \alpha B A + \beta C for $Side is $CblasRight, where the matrix $A is symmetric. When $Uplo is $CblasUpper then the upper triangle and diagonal of $A are used, and when $Uplo is $CblasLower then the lower triangle and diagonal of $A are used. $A, $B and $C are complex matrices. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes a rank-k update of the symmetric complex 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. The function returns 0 if the operation suceeded, 1 otherwise. =item C - This function computes a rank-2k update of the symmetric matrix $C, C = \alpha A B^T + \alpha B A^T + \beta C when $Trans is $CblasNoTrans and C = \alpha A^T B + \alpha B^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. The function returns 0 if the operation suceeded, 1 otherwise. $A, $B and $C are complex matrices and $beta is a complex number. =item C - This function computes the matrix-matrix product B = \alpha op(A) B for $Side is $CblasLeft and B = \alpha B op(A) for $Side is $CblasRight. The matrix $A is triangular and op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans. When $Uplo is $CblasUpper then the upper triangle of $A is used, and when $Uplo is $CblasLower then the lower triangle of $A is used. If $Diag is $CblasNonUnit then the diagonal of $A is used, but if $Diag is $CblasUnit then the diagonal elements of the matrix $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise. $A and $B are complex matrices and $alpha is a complex number. =item C - This function computes the inverse-matrix matrix product B = \alpha op(inv(A))B for $Side is $CblasLeft and B = \alpha B op(inv(A)) for $Side is $CblasRight. The matrix $A is triangular and op(A) = A, A^T, A^H for $TransA = $CblasNoTrans, $CblasTrans, $CblasConjTrans. When $Uplo is $CblasUpper then the upper triangle of $A is used, and when $Uplo is $CblasLower then the lower triangle of $A is used. If $Diag is $CblasNonUnit then the diagonal of $A is used, but if $Diag is $CblasUnit then the diagonal elements of the matrix $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise. $A and $B are complex matrices and $alpha is a complex number. =item C =item C =item C =item C - This function computes the matrix-matrix product and sum C = \alpha A B + \beta C for $Side is $CblasLeft and C = \alpha B A + \beta C for $Side is $CblasRight, where the matrix $A is hermitian. When Uplo is CblasUpper then the upper triangle and diagonal of A are used, and when Uplo is CblasLower then the lower triangle and diagonal of A are used. The imaginary elements of the diagonal are automatically set to zero. =item C - This function computes a rank-k update of the hermitian matrix $C, C = \alpha A A^H + \beta C when $Trans is $CblasNoTrans and C = \alpha A^H A + \beta C when $Trans is $CblasTrans. Since the matrix $C is hermitian 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. The imaginary elements of the diagonal are automatically set to zero. The function returns 0 if the operation suceeded, 1 otherwise. $A, $B and $C are complex matrices and $alpha and $beta are complex numbers. =item C - This function computes a rank-2k update of the hermitian matrix $C, C = \alpha A B^H + \alpha^* B A^H + \beta C when $Trans is $CblasNoTrans and C = \alpha A^H B + \alpha^* B^H A + \beta C when $Trans is $CblasConjTrans. Since the matrix $C is hermitian 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. The imaginary elements of the diagonal are automatically set to zero. The function returns 0 if the operation suceeded, 1 otherwise. =back You have to add the functions you want to use inside the qw /put_funtion_here /. You can also write use Math::GSL::PowInt qw/:all/ to use all avaible functions of the module. Other tags are also avaible, here is a complete list of all tags for this module : =over 3 =item C =item C =item C =back For more informations on the functions, we refer you to the GSL offcial documentation: L Tip : search on google: site:http://www.gnu.org/software/gsl/manual/html_node/ name_of_the_function_you_want =head1 EXAMPLES This example shows how to do a matrix-matrix product of double numbers : use Math::GSL::Matrix qw/:all/; use Math::GSL::BLAS qw/:all/; my $A = Math::GSL::Matrix->new(2,2); $A->set_row(0, [1, 4]); ->set_row(1, [3, 2]); my $B = Math::GSL::Matrix->new(2,2); $B->set_row(0, [2, 1]); ->set_row(1, [5,3]); my $C = Math::GSL::Matrix->new(2,2); gsl_matrix_set_zero($C->raw); gsl_blas_dgemm($CblasNoTrans, $CblasNoTrans, 1, $A->raw, $B->raw, 1, $C->raw); my @got = $C->row(0)->as_list; print "The resulting matrix is: \n["; print "$got[0] $got[1]\n"; @got = $C->row(1)->as_list; print "$got[0] $got[1] ]\n"; This example shows how to compute the scalar product of two vectors : use Math::GSL::Vector qw/:all/; use Math::GSL::CBLAS qw/:all/; use Math::GSL::BLAS qw/:all/; my $vec1 = Math::GSL::Vector->new([1,2,3,4,5]); my $vec2 = Math::GSL::Vector->new([5,4,3,2,1]); my ($status, $result) = gsl_blas_ddot($vec1->raw, $vec2->raw); if($status == 0) { print "The function has succeeded. \n"; } print "The result of the vector multiplication is $result. \n"; =head1 AUTHORS Jonathan Leto and Thierry Moisan =head1 COPYRIGHT AND LICENSE Copyright (C) 2008 Jonathan Leto and Thierry Moisan This program is free software; you can redistribute it and/or modify it under the same terms as Perl itself. =cut %}