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annotate libinterp/corefcn/kron.cc @ 20939:b17fda023ca6

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maint: Use new C++ archetype in more files. Place input validation first in files. Move declaration of retval down in function to be closer to point of usage. Eliminate else clause after if () error. Use "return ovl()" where it makes sense. * find.cc, gammainc.cc, gcd.cc, getgrent.cc, getpwent.cc, givens.cc, graphics.cc, help.cc, hess.cc, hex2num.cc, input.cc, kron.cc, load-path.cc, load-save.cc, lookup.cc, mappers.cc, matrix_type.cc, mgorth.cc, nproc.cc, ordschur.cc, pager.cc, pinv.cc, pr-output.cc, profiler.cc, psi.cc, quad.cc, rcond.cc, regexp.cc, schur.cc, sighandlers.cc, sparse.cc, str2double.cc, strfind.cc, strfns.cc, sub2ind.cc, svd.cc, sylvester.cc, symtab.cc, syscalls.cc, sysdep.cc, time.cc, toplev.cc, tril.cc, tsearch.cc, typecast.cc, urlwrite.cc, utils.cc, variables.cc, __delaunayn__.cc, __eigs__.cc, __glpk__.cc, __magick_read__.cc, __osmesa_print__.cc, __voronoi__.cc, amd.cc, audiodevinfo.cc, audioread.cc, chol.cc, colamd.cc, dmperm.cc, fftw.cc, qr.cc, symbfact.cc, symrcm.cc, ov-bool-mat.cc, ov-cell.cc, ov-class.cc, ov-classdef.cc, ov-fcn-handle.cc, ov-fcn-inline.cc, ov-flt-re-mat.cc, ov-java.cc, ov-null-mat.cc, ov-oncleanup.cc, ov-re-mat.cc, ov-struct.cc, ov-typeinfo.cc, ov-usr-fcn.cc, ov.cc, octave.cc: Use new C++ archetype in more files.
author Rik <rik@octave.org>
date Fri, 18 Dec 2015 15:37:22 -0800
parents 1142cf6abc0d
children 48b2ad5ee801
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1 /*
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2
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4197fc428c7d maint: Update copyright notices for 2015.
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3 Copyright (C) 2002-2015 John W. Eaton
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4
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5 This file is part of Octave.
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6
79a90a0f0eff [project @ 2002-04-25 05:36:52 by jwe]
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7 Octave is free software; you can redistribute it and/or modify it
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8 under the terms of the GNU General Public License as published by the
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9 Free Software Foundation; either version 3 of the License, or (at your
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10 option) any later version.
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11
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12 Octave is distributed in the hope that it will be useful, but WITHOUT
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13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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15 for more details.
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16
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17 You should have received a copy of the GNU General Public License
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18 along with Octave; see the file COPYING. If not, see
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19 <http://www.gnu.org/licenses/>.
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20
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21 */
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22
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23 // Author: Paul Kienzle <pkienzle@users.sf.net>
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24
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25 #ifdef HAVE_CONFIG_H
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26 #include <config.h>
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27 #endif
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28
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29 #include "dMatrix.h"
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30 #include "fMatrix.h"
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31 #include "CMatrix.h"
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32 #include "fCMatrix.h"
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33
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34 #include "dSparse.h"
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35 #include "CSparse.h"
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36
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37 #include "dDiagMatrix.h"
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38 #include "fDiagMatrix.h"
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39 #include "CDiagMatrix.h"
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40 #include "fCDiagMatrix.h"
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41
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42 #include "PermMatrix.h"
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43
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44 #include "mx-inlines.cc"
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45 #include "quit.h"
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46
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47 #include "defun.h"
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48 #include "error.h"
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49 #include "oct-obj.h"
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50
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51 template <class R, class T>
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52 static MArray<T>
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53 kron (const MArray<R>& a, const MArray<T>& b)
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54 {
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55 assert (a.ndims () == 2);
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56 assert (b.ndims () == 2);
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57
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58 octave_idx_type nra = a.rows ();
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59 octave_idx_type nrb = b.rows ();
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60 octave_idx_type nca = a.cols ();
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61 octave_idx_type ncb = b.cols ();
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62
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63 MArray<T> c (dim_vector (nra*nrb, nca*ncb));
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64 T *cv = c.fortran_vec ();
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65
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66 for (octave_idx_type ja = 0; ja < nca; ja++)
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67 for (octave_idx_type jb = 0; jb < ncb; jb++)
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68 for (octave_idx_type ia = 0; ia < nra; ia++)
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69 {
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70 octave_quit ();
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71 mx_inline_mul (nrb, cv, a(ia, ja), b.data () + nrb*jb);
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72 cv += nrb;
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73 }
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74
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75 return c;
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76 }
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77
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78 template <class R, class T>
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79 static MArray<T>
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80 kron (const MDiagArray2<R>& a, const MArray<T>& b)
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81 {
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82 assert (b.ndims () == 2);
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83
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84 octave_idx_type nra = a.rows ();
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85 octave_idx_type nrb = b.rows ();
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86 octave_idx_type dla = a.diag_length ();
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87 octave_idx_type nca = a.cols ();
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88 octave_idx_type ncb = b.cols ();
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89
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90 MArray<T> c (dim_vector (nra*nrb, nca*ncb), T ());
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91
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92 for (octave_idx_type ja = 0; ja < dla; ja++)
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93 for (octave_idx_type jb = 0; jb < ncb; jb++)
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94 {
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95 octave_quit ();
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96 mx_inline_mul (nrb, &c.xelem (ja*nrb, ja*ncb + jb), a.dgelem (ja),
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97 b.data () + nrb*jb);
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98 }
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99
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100 return c;
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101 }
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102
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103 template <class T>
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104 static MSparse<T>
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105 kron (const MSparse<T>& A, const MSparse<T>& B)
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106 {
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107 octave_idx_type idx = 0;
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108 MSparse<T> C (A.rows () * B.rows (), A.columns () * B.columns (),
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109 A.nnz () * B.nnz ());
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110
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111 C.cidx (0) = 0;
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112
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113 for (octave_idx_type Aj = 0; Aj < A.columns (); Aj++)
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114 for (octave_idx_type Bj = 0; Bj < B.columns (); Bj++)
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115 {
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116 octave_quit ();
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117 for (octave_idx_type Ai = A.cidx (Aj); Ai < A.cidx (Aj+1); Ai++)
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118 {
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119 octave_idx_type Ci = A.ridx (Ai) * B.rows ();
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120 const T v = A.data (Ai);
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121
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122 for (octave_idx_type Bi = B.cidx (Bj); Bi < B.cidx (Bj+1); Bi++)
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123 {
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124 C.data (idx) = v * B.data (Bi);
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125 C.ridx (idx++) = Ci + B.ridx (Bi);
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126 }
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127 }
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128 C.cidx (Aj * B.columns () + Bj + 1) = idx;
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129 }
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130
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131 return C;
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132 }
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133
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134 static PermMatrix
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135 kron (const PermMatrix& a, const PermMatrix& b)
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136 {
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137 octave_idx_type na = a.rows ();
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138 octave_idx_type nb = b.rows ();
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139 const Array<octave_idx_type>& pa = a.col_perm_vec ();
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140 const Array<octave_idx_type>& pb = b.col_perm_vec ();
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141 Array<octave_idx_type> res_perm (dim_vector (na * nb, 1));
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142 octave_idx_type rescol = 0;
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143 for (octave_idx_type i = 0; i < na; i++)
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144 {
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145 octave_idx_type a_add = pa(i) * nb;
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146 for (octave_idx_type j = 0; j < nb; j++)
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147 res_perm.xelem (rescol++) = a_add + pb(j);
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148 }
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149
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150 return PermMatrix (res_perm, true);
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151 }
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152
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153 template <class MTA, class MTB>
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154 octave_value
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155 do_kron (const octave_value& a, const octave_value& b)
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156 {
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157 MTA am = octave_value_extract<MTA> (a);
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158 MTB bm = octave_value_extract<MTB> (b);
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159 return octave_value (kron (am, bm));
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160 }
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161
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162 octave_value
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163 dispatch_kron (const octave_value& a, const octave_value& b)
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164 {
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165 octave_value retval;
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166 if (a.is_perm_matrix () && b.is_perm_matrix ())
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167 retval = do_kron<PermMatrix, PermMatrix> (a, b);
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168 else if (a.is_sparse_type () || b.is_sparse_type ())
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169 {
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170 if (a.is_complex_type () || b.is_complex_type ())
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171 retval = do_kron<SparseComplexMatrix, SparseComplexMatrix> (a, b);
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172 else
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173 retval = do_kron<SparseMatrix, SparseMatrix> (a, b);
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174 }
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175 else if (a.is_diag_matrix ())
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176 {
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177 if (b.is_diag_matrix () && a.rows () == a.columns ()
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178 && b.rows () == b.columns ())
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179 {
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180 // We have two diagonal matrices, the product of those will be
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181 // another diagonal matrix. To do that efficiently, extract
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182 // the diagonals as vectors and compute the product. That
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183 // will be another vector, which we then use to construct a
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184 // diagonal matrix object. Note that this will fail if our
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185 // digaonal matrix object is modified to allow the nonzero
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186 // values to be stored off of the principal diagonal (i.e., if
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187 // diag ([1,2], 3) is modified to return a diagonal matrix
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188 // object instead of a full matrix object).
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189
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190 octave_value tmp = dispatch_kron (a.diag (), b.diag ());
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191 retval = tmp.diag ();
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192 }
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193 else if (a.is_single_type () || b.is_single_type ())
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194 {
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195 if (a.is_complex_type ())
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196 retval = do_kron<FloatComplexDiagMatrix, FloatComplexMatrix> (a, b);
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197 else if (b.is_complex_type ())
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198 retval = do_kron<FloatDiagMatrix, FloatComplexMatrix> (a, b);
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199 else
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200 retval = do_kron<FloatDiagMatrix, FloatMatrix> (a, b);
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201 }
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202 else
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203 {
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204 if (a.is_complex_type ())
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205 retval = do_kron<ComplexDiagMatrix, ComplexMatrix> (a, b);
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206 else if (b.is_complex_type ())
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207 retval = do_kron<DiagMatrix, ComplexMatrix> (a, b);
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208 else
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209 retval = do_kron<DiagMatrix, Matrix> (a, b);
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210 }
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211 }
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212 else if (a.is_single_type () || b.is_single_type ())
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213 {
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214 if (a.is_complex_type ())
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215 retval = do_kron<FloatComplexMatrix, FloatComplexMatrix> (a, b);
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216 else if (b.is_complex_type ())
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217 retval = do_kron<FloatMatrix, FloatComplexMatrix> (a, b);
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218 else
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219 retval = do_kron<FloatMatrix, FloatMatrix> (a, b);
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220 }
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221 else
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222 {
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223 if (a.is_complex_type ())
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224 retval = do_kron<ComplexMatrix, ComplexMatrix> (a, b);
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225 else if (b.is_complex_type ())
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226 retval = do_kron<Matrix, ComplexMatrix> (a, b);
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227 else
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228 retval = do_kron<Matrix, Matrix> (a, b);
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229 }
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230 return retval;
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231 }
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232
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233
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234 DEFUN (kron, args, , "-*- texinfo -*-\n\
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235 @deftypefn {} {} kron (@var{A}, @var{B})\n\
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236 @deftypefnx {} {} kron (@var{A1}, @var{A2}, @dots{})\n\
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237 Form the Kronecker product of two or more matrices.\n\
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238 \n\
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239 This is defined block by block as\n\
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240 \n\
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241 @example\n\
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242 x = [ a(i,j)*b ]\n\
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243 @end example\n\
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244 \n\
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245 For example:\n\
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246 \n\
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247 @example\n\
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248 @group\n\
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249 kron (1:4, ones (3, 1))\n\
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250 @result{} 1 2 3 4\n\
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251 1 2 3 4\n\
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252 1 2 3 4\n\
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253 @end group\n\
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254 @end example\n\
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255 \n\
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256 If there are more than two input arguments @var{A1}, @var{A2}, @dots{},\n\
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257 @var{An} the Kronecker product is computed as\n\
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258 \n\
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259 @example\n\
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260 kron (kron (@var{A1}, @var{A2}), @dots{}, @var{An})\n\
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261 @end example\n\
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262 \n\
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263 @noindent\n\
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264 Since the Kronecker product is associative, this is well-defined.\n\
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265 @end deftypefn")
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266 {
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267 int nargin = args.length ();
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268
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269 if (nargin < 2)
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270 print_usage ();
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271
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272 octave_value retval;
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273
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274 octave_value a = args(0);
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275 octave_value b = args(1);
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276
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277 retval = dispatch_kron (a, b);
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278
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279 for (octave_idx_type i = 2; i < nargin; i++)
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280 retval = dispatch_kron (retval, args(i));
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281
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282 return retval;
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283 }
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284
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285
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286 /*
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287 %!test
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288 %! x = ones (2);
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289 %! assert (kron (x, x), ones (4));
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290
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291 %!shared x, y, z, p1, p2, d1, d2
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292 %! x = [1, 2];
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293 %! y = [-1, -2];
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294 %! z = [1, 2, 3, 4; 1, 2, 3, 4; 1, 2, 3, 4];
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295 %! p1 = eye (3)([2, 3, 1], :); ## Permutation matrix
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296 %! p2 = [0 1 0; 0 0 1; 1 0 0]; ## Non-permutation equivalent
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297 %! d1 = diag ([1 2 3]); ## Diag type matrix
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298 %! d2 = [1 0 0; 0 2 0; 0 0 3]; ## Non-diag equivalent
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299 %!assert (kron (1:4, ones (3, 1)), z)
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300 %!assert (kron (single (1:4), ones (3, 1)), single (z))
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301 %!assert (kron (sparse (1:4), ones (3, 1)), sparse (z))
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302 %!assert (kron (complex (1:4), ones (3, 1)), z)
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303 %!assert (kron (complex (single(1:4)), ones (3, 1)), single(z))
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304 %!assert (kron (x, y, z), kron (kron (x, y), z))
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305 %!assert (kron (x, y, z), kron (x, kron (y, z)))
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306 %!assert (kron (p1, p1), kron (p2, p2))
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307 %!assert (kron (p1, p2), kron (p2, p1))
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308 %!assert (kron (d1, d1), kron (d2, d2))
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309 %!assert (kron (d1, d2), kron (d2, d1))
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310
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311
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312 %!assert (kron (diag ([1, 2]), diag ([3, 4])), diag ([3, 4, 6, 8]))
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313
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314 %% Test for two diag matrices. See the comments above in
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315 %% dispatch_kron for this case.
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316 %%
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317 %!test
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318 %! expected = zeros (16, 16);
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319 %! expected (1, 11) = 3;
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320 %! expected (2, 12) = 4;
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321 %! expected (5, 15) = 6;
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322 %! expected (6, 16) = 8;
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323 %! assert (kron (diag ([1, 2], 2), diag ([3, 4], 2)), expected)
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324 */