BLAS.i

   1 %module "Math::GSL::BLAS"
   2
   3 %include "typemaps.i"
   4 %include "gsl_typemaps.i"
   5
   6 %apply float *OUTPUT { float *result };
   7 %apply double *OUTPUT { double *result };
   8 %apply double *OUTPUT { double c[], double s[] };
   9
  10
  11 %{
  12     #include "gsl/gsl_blas.h"
  13     #include "gsl/gsl_blas_types.h"
  14 %}
  15
  16 %include "gsl/gsl_blas.h"
  17 %include "gsl/gsl_blas_types.h"
  18
  19 %perlcode %{
  20
  21 @EXPORT_OK_level1 = qw/
  22                         gsl_blas_sdsdot gsl_blas_dsdot gsl_blas_sdot gsl_blas_ddot
  23                         gsl_blas_cdotu gsl_blas_cdotc gsl_blas_zdotu gsl_blas_zdotc
  24                         gsl_blas_snrm2 gsl_blas_sasum gsl_blas_dnrm2 gsl_blas_dasum
  25                         gsl_blas_scnrm2 gsl_blas_scasum gsl_blas_dznrm2 gsl_blas_dzasum
  26                         gsl_blas_isamax gsl_blas_idamax gsl_blas_icamax gsl_blas_izamax
  27                         gsl_blas_sswap gsl_blas_scopy gsl_blas_saxpy gsl_blas_dswap
  28                         gsl_blas_dcopy gsl_blas_daxpy gsl_blas_cswap gsl_blas_ccopy
  29                         gsl_blas_caxpy gsl_blas_zswap gsl_blas_zcopy gsl_blas_zaxpy
  30                         gsl_blas_srotg gsl_blas_srotmg gsl_blas_srot gsl_blas_srotm
  31                         gsl_blas_drotg gsl_blas_drotmg gsl_blas_drot gsl_blas_drotm
  32                         gsl_blas_sscal gsl_blas_dscal gsl_blas_cscal gsl_blas_zscal
  33                         gsl_blas_csscal gsl_blas_zdscal
  34                     /;
  35 @EXPORT_OK_level2 = qw/
  36                         gsl_blas_sgemv gsl_blas_strmv
  37                         gsl_blas_strsv gsl_blas_dgemv gsl_blas_dtrmv gsl_blas_dtrsv
  38                         gsl_blas_cgemv gsl_blas_ctrmv gsl_blas_ctrsv gsl_blas_zgemv
  39                         gsl_blas_ztrmv gsl_blas_ztrsv gsl_blas_ssymv gsl_blas_sger
  40                         gsl_blas_ssyr gsl_blas_ssyr2 gsl_blas_dsymv gsl_blas_dger
  41                         gsl_blas_dsyr gsl_blas_dsyr2 gsl_blas_chemv gsl_blas_cgeru
  42                         gsl_blas_cgerc gsl_blas_cher gsl_blas_cher2 gsl_blas_zhemv
  43                         gsl_blas_zgeru gsl_blas_zgerc gsl_blas_zher gsl_blas_zher2
  44                     /;
  45
  46 @EXPORT_OK_level3 = qw/
  47                         gsl_blas_sgemm gsl_blas_ssymm gsl_blas_ssyrk gsl_blas_ssyr2k
  48                         gsl_blas_strmm gsl_blas_strsm gsl_blas_dgemm gsl_blas_dsymm
  49                         gsl_blas_dsyrk gsl_blas_dsyr2k gsl_blas_dtrmm gsl_blas_dtrsm
  50                         gsl_blas_cgemm gsl_blas_csymm gsl_blas_csyrk gsl_blas_csyr2k
  51                         gsl_blas_ctrmm gsl_blas_ctrsm gsl_blas_zgemm gsl_blas_zsymm
  52                         gsl_blas_zsyrk gsl_blas_zsyr2k gsl_blas_ztrmm gsl_blas_ztrsm
  53                         gsl_blas_chemm gsl_blas_cherk gsl_blas_cher2k gsl_blas_zhemm
  54                         gsl_blas_zherk gsl_blas_zher2k
  55                     /;
  56 @EXPORT_OK = (@EXPORT_OK_level1, @EXPORT_OK_level2, @EXPORT_OK_level3);
  57 %EXPORT_TAGS = (
  58                 all    => [ @EXPORT_OK ],
  59                 level1 => [ @EXPORT_OK_level1 ],
  60                 level2 => [ @EXPORT_OK_level2 ],
  61                 level3 => [ @EXPORT_OK_level3 ],
  62                );
  63 __END__
  64
  65 =head1 NAME
  66
  67 Math::GSL::BLAS - Basic Linear Algebra Subprograms
  68
  69 =head1 SYNOPSIS
  70
  71 use Math::GSL::QRNG qw/:all/;
  72
  73 =head1 DESCRIPTION
  74
  75 The functions of this module are divised into 3 levels:
  76
  77 =head2 Level 1 - Vector operations
  78
  79 =over 3
  80
  81 =item C<gsl_blas_sdsdot>
  82
  83 =item C<gsl_blas_dsdot>
  84
  85 =item C<gsl_blas_sdot>
  86
  87 =item C<gsl_blas_ddot($x, $y)> - This function computes the scalar product x^T y for the vectors $x and $y. The function returns two values, the first is 0 if the operation suceeded, 1 otherwise and the second value is the result of the computation.
  88
  89 =item C<gsl_blas_cdotu>
  90
  91 =item C<gsl_blas_cdotc>
  92
  93 =item C<gsl_blas_zdotu($x, $y, $dotu)> - This function computes the complex scalar product x^T y for the complex vectors $x and $y, returning the result in the complex number $dotu. The function returns 0 if the operation suceeded, 1 otherwise.
  94
  95 =item C<gsl_blas_zdotc($x, $y, $dotc)> - 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 $dotc. The function returns 0 if the operation suceeded, 1 otherwise.
  96
  97 =item C<gsl_blas_snrm2>
  98 =item C<gsl_blas_sasum>
  99
 100 =item C<gsl_blas_dnrm2($x)> - This function computes the Euclidean norm ||x||_2 = \sqrt {\sum x_i^2} of the vector $x.
 101
 102 =item C<gsl_blas_dasum($x)> - This function computes the absolute sum \sum |x_i| of the elements of the vector $x.
 103
 104 =item C<gsl_blas_scnrm2>
 105
 106 =item C<gsl_blas_scasum>
 107
 108 =item C<gsl_blas_dznrm2($x)> - This function computes the Euclidean norm of the complex vector $x, ||x||_2 = \sqrt {\sum (\Re(x_i)^2 + \Im(x_i)^2)}.
 109
 110 =item C<gsl_blas_dzasum($x)> - This function computes the sum of the magnitudes of the real and imaginary parts of the complex vector $x, \sum |\Re(x_i)| + |\Im(x_i)|.
 111
 112 =item C<gsl_blas_isamax>
 113
 114 =item C<gsl_blas_idamax>
 115
 116 =item C<gsl_blas_icamax>
 117
 118 =item C<gsl_blas_izamax >
 119
 120 =item C<gsl_blas_sswap>
 121
 122 =item C<gsl_blas_scopy>
 123
 124 =item C<gsl_blas_saxpy>
 125
 126 =item C<gsl_blas_dswap($x, $y)> - This function exchanges the elements of the vectors $x and $y. The function returns 0 if the operation suceeded, 1 otherwise.
 127
 128 =item C<gsl_blas_dcopy($x, $y)> - This function copies the elements of the vector $x into the vector $y. The function returns 0 if the operation suceeded, 1 otherwise.
 129
 130 =item C<gsl_blas_daxpy($alpha, $x, $y)> - These functions compute the sum $y = $alpha * $x + $y for the vectors $x and $y.
 131
 132 =item C<gsl_blas_cswap>
 133
 134 =item C<gsl_blas_ccopy >
 135
 136 =item C<gsl_blas_caxpy>
 137
 138 =item C<gsl_blas_zswap>
 139
 140 =item C<gsl_blas_zcopy>
 141
 142 =item C<gsl_blas_zaxpy >
 143
 144 =item C<gsl_blas_srotg>
 145
 146 =item C<gsl_blas_srotmg>
 147
 148 =item C<gsl_blas_srot>
 149
 150 =item C<gsl_blas_srotm >
 151
 152 =item C<gsl_blas_drotg>
 153
 154 =item C<gsl_blas_drotmg>
 155
 156 =item C<gsl_blas_drot($x, $y, $c, $s)> - This function applies a Givens rotation (x', y') = (c x + s y, -s x + c y) to the vectors $x, $y.
 157
 158 =item C<gsl_blas_drotm >
 159
 160 =item C<gsl_blas_sscal>
 161
 162 =item C<gsl_blas_dscal($alpha, $x)> - This function rescales the vector $x by the multiplicative factor $alpha.
 163
 164 =item C<gsl_blas_cscal>
 165
 166 =item C<gsl_blas_zscal >
 167
 168 =item C<gsl_blas_csscal>
 169
 170 =item C<gsl_blas_zdscal>
 171
 172 =back
 173
 174 =head2 Level 2 - Matrix-vector operations
 175
 176 =over 3
 177
 178 =item C<gsl_blas_sgemv>
 179
 180 =item C<gsl_blas_strmv >
 181
 182 =item C<gsl_blas_strsv>
 183
 184 =item C<gsl_blas_dgemv($TransA, $alpha, $A, $x, $beta, $y)> - 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 $y are vectors. The function returns 0 if the operation suceeded, 1 otherwise.
 185
 186 =item C<gsl_blas_dtrmv($Uplo, $TransA, $Diag, $A, $x)> - 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 $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise.
 187
 188 =item C<gsl_blas_dtrsv($Uplo, $TransA, $Diag, $A, $x)> - 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 $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise.
 189
 190 =item C<gsl_blas_cgemv >
 191
 192 =item C<gsl_blas_ctrmv>
 193
 194 =item C<gsl_blas_ctrsv>
 195
 196 =item C<gsl_blas_zgemv >
 197
 198 =item C<gsl_blas_ztrmv>
 199
 200 =item C<gsl_blas_ztrsv>
 201
 202 =item C<gsl_blas_ssymv>
 203
 204 =item C<gsl_blas_sger >
 205
 206 =item C<gsl_blas_ssyr>
 207
 208 =item C<gsl_blas_ssyr2>
 209
 210 =item C<gsl_blas_dsymv>
 211
 212 =item C<gsl_blas_dger($alpha, $x, $y, $A)> - This function computes the rank-1 update A = alpha x y^T + A of the matrix $A. $x and $y are vectors. The function returns 0 if the operation suceeded, 1 otherwise.
 213
 214 =item C<gsl_blas_dsyr($Uplo, $alpha, $x, $A)> - 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 $A are used. The function returns 0 if the operation suceeded, 1 otherwise.
 215
 216 =item C<gsl_blas_dsyr2($Uplo, $alpha, $x, $y, $A)> - 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 $A are used.
 217
 218 =item C<gsl_blas_chemv>
 219
 220 =item C<gsl_blas_cgeru >
 221
 222 =item C<gsl_blas_cgerc>
 223
 224 =item C<gsl_blas_cher>
 225
 226 =item C<gsl_blas_cher2>
 227
 228 =item C<gsl_blas_zhemv >
 229
 230 =item C<gsl_blas_zgeru($alpha, $x, $y, $A)> - 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 $y are complex vectors. The function returns 0 if the operation suceeded, 1 otherwise.
 231
 232 =item C<gsl_blas_zgerc>
 233
 234 =item C<gsl_blas_zher($Uplo, $alpha, $x, $A)> - 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 $A are used. The imaginary elements of the diagonal are automatically set to zero. The function returns 0 if the operation suceeded, 1 otherwise.
 235
 236
 237 =item C<gsl_blas_zher2 >
 238
 239 =back
 240
 241 =head2 Level 3 - Matrix-matrix operations
 242
 243 =over 3
 244
 245 =item C<gsl_blas_sgemm>
 246
 247 =item C<gsl_blas_ssymm>
 248
 249 =item C<gsl_blas_ssyrk>
 250
 251 =item C<gsl_blas_ssyr2k >
 252
 253 =item C<gsl_blas_strmm>
 254
 255 =item C<gsl_blas_strsm>
 256
 257 =item C<gsl_blas_dgemm($TransA, $TransB, $alpha, $A, $B, $beta, $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 $TransB. The function returns 0 if the operation suceeded, 1 otherwise.
 258
 259 =item C<gsl_blas_dsymm($Side, $Uplo, $alpha, $A, $B, $beta, $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 $A are used. The function returns 0 if the operation suceeded, 1 otherwise.
 260
 261 =item C<gsl_blas_dsyrk($Uplo, $Trans, $alpha, $A, $beta, $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 $C are used. The function returns 0 if the operation suceeded, 1 otherwise.
 262
 263 =item C<gsl_blas_dsyr2k($Uplo, $Trans, $alpha, $A, $B, $beta, $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 $C are used. The function returns 0 if the operation suceeded, 1 otherwise.
 264
 265 =item C<gsl_blas_dtrmm($Side, $Uplo, $TransA, $Diag, $alpha, $A, $B)> - 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 $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise.
 266
 267 =item C<gsl_blas_dtrsm($Side, $Uplo, $TransA, $Diag, $alpha, $A, $B)> - 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 $A are taken as unity and are not referenced. The function returns 0 if the operation suceeded, 1 otherwise.
 268
 269 =item C<gsl_blas_cgemm>
 270
 271 =item C<gsl_blas_csymm>
 272
 273 =item C<gsl_blas_csyrk>
 274
 275 =item C<gsl_blas_csyr2k >
 276
 277 =item C<gsl_blas_ctrmm>
 278
 279 =item C<gsl_blas_ctrsm>
 280
 281 =item C<gsl_blas_zgemm($TransA, $TransB, $alpha, $A, $B, $beta, $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 $C are complex matrices
 282
 283 =item C<gsl_blas_zsymm($Side, $Uplo, $alpha, $A, $B, $beta, $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 $C are complex matrices. The function returns 0 if the operation suceeded, 1 otherwise.
 284
 285 =item C<gsl_blas_zsyrk($Uplo, $Trans, $alpha, $A, $beta, $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 $C are used. The function returns 0 if the operation suceeded, 1 otherwise.
 286
 287 =item C<gsl_blas_zsyr2k($Uplo, $Trans, $alpha, $A, $B, $beta, $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 $beta is a complex number.
 288
 289 =item C<gsl_blas_ztrmm($Side, $Uplo, $TransA, $Diag, $alpha, $A, $B)> - 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 $alpha is a complex number.
 290
 291 =item C<gsl_blas_ztrsm($Side, $Uplo, $TransA, $Diag, $alpha, $A, $B)> - 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 $alpha is a complex number.
 292
 293 =item C<gsl_blas_chemm>
 294
 295 =item C<gsl_blas_cherk>
 296
 297 =item C<gsl_blas_cher2k>
 298
 299 =item C<gsl_blas_zhemm($Side, $Uplo, $alpha, $A, $B, $beta, $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 $A is hermitian. When Uplo is CblasUpper then the upper triangle and diagonal of A are used, and when Uplo is CblasLower then the lower triangle and diagonal of A are used. The imaginary elements of the diagonal are automatically set to zero.
 300
 301 =item C<gsl_blas_zherk($Uplo, $Trans, $alpha, $A, $beta, $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 $beta are complex numbers.
 302
 303 =item C<gsl_blas_zher2k($Uplo, $Trans, $alpha, $A, $B, $beta, $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.
 304
 305 =back
 306
 307 You have to add the functions you want to use inside the qw /put_funtion_here /.
 308 You can also write use Math::GSL::PowInt qw/:all/ to use all avaible functions of the module.
 309 Other tags are also avaible, here is a complete list of all tags for this module :
 310
 311 =over 3
 312
 313 =item C<level1>
 314
 315 =item C<level2>
 316
 317 =item C<level3>
 318
 319 =back
 320
 321 For more informations on the functions, we refer you to the GSL offcial documentation: L<http://www.gnu.org/software/gsl/manual/html_node/>
 322
 323 Tip : search on google: site:http://www.gnu.org/software/gsl/manual/html_node/ name_of_the_function_you_want
 324
 325
 326 =head1 EXAMPLES
 327
 328  This example shows how to do a matrix-matrix product of double numbers :
 329
 330  use Math::GSL::Matrix qw/:all/;
 331  use Math::GSL::BLAS qw/:all/;
 332  my $A = Math::GSL::Matrix->new(2,2);
 333  $A->set_row(0, [1, 4]);
 334    ->set_row(1, [3, 2]);
 335  my $B = Math::GSL::Matrix->new(2,2);
 336  $B->set_row(0, [2, 1]);
 337    ->set_row(1, [5,3]);
 338  my $C = Math::GSL::Matrix->new(2,2);
 339  gsl_matrix_set_zero($C->raw);
 340  gsl_blas_dgemm($CblasNoTrans, $CblasNoTrans, 1, $A->raw, $B->raw, 1, $C->raw);
 341  my @got = $C->row(0)->as_list;
 342  print "The resulting matrix is: \n[";
 343  print "$got[0]  $got[1]\n";
 344  @got = $C->row(1)->as_list;
 345  print "$got[0]  $got[1] ]\n";
 346
 347
 348  This example shows how to compute the scalar product of two vectors :
 349
 350  use Math::GSL::Vector qw/:all/;
 351  use Math::GSL::CBLAS qw/:all/;
 352  use Math::GSL::BLAS qw/:all/;
 353  my $vec1 = Math::GSL::Vector->new([1,2,3,4,5]);
 354  my $vec2 = Math::GSL::Vector->new([5,4,3,2,1]);
 355  my ($status, $result) = gsl_blas_ddot($vec1->raw, $vec2->raw);
 356  if($status == 0) {
 357  print "The function has succeeded. \n";
 358  }
 359  print "The result of the vector multiplication is $result. \n";
 360
 361 =head1 AUTHORS
 362
 363 Jonathan Leto <jonathan@leto.net> and Thierry Moisan <thierry.moisan@gmail.com>
 364
 365 =head1 COPYRIGHT AND LICENSE
 366
 367 Copyright (C) 2008 Jonathan Leto and Thierry Moisan
 368
 369 This program is free software; you can redistribute it and/or modify it
 370 under the same terms as Perl itself.
 371
 372 =cut
 373
 374 %}