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update Octave Project Developers copyright for the new year In files that have the "Octave Project Developers" copyright notice, update for 2021. In all .txi and .texi files except gpl.txi and gpl.texi in the doc/liboctave and doc/interpreter directories, change the copyright to "Octave Project Developers", the same as used for other source files. Update copyright notices for 2022 (not done since 2019). For gpl.txi and gpl.texi, change the copyright notice to be "Free Software Foundation, Inc." and leave the date at 2007 only because this file only contains the text of the GPL, not anything created by the Octave Project Developers. Add Paul Thomas to contributors.in.
author John W. Eaton <jwe@octave.org>
date Tue, 28 Dec 2021 18:22:40 -0500
parents 32c3a5805893
children 08b08b7f05b2
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1 ////////////////////////////////////////////////////////////////////////
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2 //
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3 // Copyright (C) 2002-2022 The Octave Project Developers
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4 //
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5 // See the file COPYRIGHT.md in the top-level directory of this
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6 // distribution or <https://octave.org/copyright/>.
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7 //
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8 // This file is part of Octave.
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9 //
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10 // Octave is free software: you can redistribute it and/or modify it
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11 // under the terms of the GNU General Public License as published by
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12 // the Free Software Foundation, either version 3 of the License, or
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13 // (at your option) any later version.
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14 //
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15 // Octave is distributed in the hope that it will be useful, but
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16 // WITHOUT ANY WARRANTY; without even the implied warranty of
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17 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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18 // GNU General Public License for more details.
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19 //
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20 // You should have received a copy of the GNU General Public License
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21 // along with Octave; see the file COPYING. If not, see
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22 // <https://www.gnu.org/licenses/>.
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23 //
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24 ////////////////////////////////////////////////////////////////////////
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25
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26 #if defined (HAVE_CONFIG_H)
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27 # include "config.h"
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28 #endif
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29
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30 #include "dMatrix.h"
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31 #include "fMatrix.h"
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32 #include "CMatrix.h"
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33 #include "fCMatrix.h"
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34
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35 #include "dSparse.h"
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36 #include "CSparse.h"
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37
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38 #include "dDiagMatrix.h"
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39 #include "fDiagMatrix.h"
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40 #include "CDiagMatrix.h"
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41 #include "fCDiagMatrix.h"
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42
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43 #include "PermMatrix.h"
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44
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45 #include "mx-inlines.cc"
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46 #include "quit.h"
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47
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48 #include "defun.h"
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49 #include "error.h"
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50 #include "ovl.h"
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51
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52 OCTAVE_NAMESPACE_BEGIN
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53
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54 template <typename R, typename T>
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55 static MArray<T>
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56 kron (const MArray<R>& a, const MArray<T>& b)
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57 {
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58 assert (a.ndims () == 2);
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59 assert (b.ndims () == 2);
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60
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61 octave_idx_type nra = a.rows ();
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62 octave_idx_type nrb = b.rows ();
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63 octave_idx_type nca = a.cols ();
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64 octave_idx_type ncb = b.cols ();
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65
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66 MArray<T> c (dim_vector (nra*nrb, nca*ncb));
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67 T *cv = c.fortran_vec ();
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68
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69 for (octave_idx_type ja = 0; ja < nca; ja++)
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70 {
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71 octave_quit ();
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72 for (octave_idx_type jb = 0; jb < ncb; jb++)
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73 {
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74 for (octave_idx_type ia = 0; ia < nra; ia++)
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75 {
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76 mx_inline_mul (nrb, cv, a(ia, ja), b.data () + nrb*jb);
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77 cv += nrb;
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78 }
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79 }
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80 }
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81
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82 return c;
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83 }
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84
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85 template <typename R, typename T>
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86 static MArray<T>
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87 kron (const MDiagArray2<R>& a, const MArray<T>& b)
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88 {
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89 assert (b.ndims () == 2);
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90
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91 octave_idx_type nra = a.rows ();
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92 octave_idx_type nrb = b.rows ();
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93 octave_idx_type dla = a.diag_length ();
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94 octave_idx_type nca = a.cols ();
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95 octave_idx_type ncb = b.cols ();
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96
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97 MArray<T> c (dim_vector (nra*nrb, nca*ncb), T ());
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98
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99 for (octave_idx_type ja = 0; ja < dla; ja++)
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100 {
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101 octave_quit ();
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102 for (octave_idx_type jb = 0; jb < ncb; jb++)
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103 {
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104 mx_inline_mul (nrb, &c.xelem (ja*nrb, ja*ncb + jb), a.dgelem (ja),
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105 b.data () + nrb*jb);
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106 }
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107 }
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108
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109 return c;
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110 }
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111
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112 template <typename T>
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113 static MSparse<T>
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114 kron (const MSparse<T>& A, const MSparse<T>& B)
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115 {
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116 octave_idx_type idx = 0;
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117 MSparse<T> C (A.rows () * B.rows (), A.columns () * B.columns (),
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118 A.nnz () * B.nnz ());
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119
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120 C.cidx (0) = 0;
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121
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122 for (octave_idx_type Aj = 0; Aj < A.columns (); Aj++)
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123 {
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124 octave_quit ();
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125 for (octave_idx_type Bj = 0; Bj < B.columns (); Bj++)
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126 {
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127 for (octave_idx_type Ai = A.cidx (Aj); Ai < A.cidx (Aj+1); Ai++)
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128 {
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129 octave_idx_type Ci = A.ridx (Ai) * B.rows ();
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130 const T v = A.data (Ai);
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131
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132 for (octave_idx_type Bi = B.cidx (Bj); Bi < B.cidx (Bj+1); Bi++)
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133 {
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134 C.data (idx) = v * B.data (Bi);
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135 C.ridx (idx++) = Ci + B.ridx (Bi);
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136 }
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137 }
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138 C.cidx (Aj * B.columns () + Bj + 1) = idx;
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139 }
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140 }
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141
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142 return C;
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143 }
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144
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145 static PermMatrix
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146 kron (const PermMatrix& a, const PermMatrix& b)
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147 {
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148 octave_idx_type na = a.rows ();
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149 octave_idx_type nb = b.rows ();
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150 const Array<octave_idx_type>& pa = a.col_perm_vec ();
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151 const Array<octave_idx_type>& pb = b.col_perm_vec ();
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152 Array<octave_idx_type> res_perm (dim_vector (na * nb, 1));
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153 octave_idx_type rescol = 0;
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154 for (octave_idx_type i = 0; i < na; i++)
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155 {
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156 octave_idx_type a_add = pa(i) * nb;
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157 for (octave_idx_type j = 0; j < nb; j++)
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158 res_perm.xelem (rescol++) = a_add + pb(j);
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159 }
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160
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161 return PermMatrix (res_perm, true);
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162 }
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163
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164 template <typename MTA, typename MTB>
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165 octave_value
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166 do_kron (const octave_value& a, const octave_value& b)
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167 {
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168 MTA am = octave_value_extract<MTA> (a);
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169 MTB bm = octave_value_extract<MTB> (b);
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170
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171 return octave_value (kron (am, bm));
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172 }
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173
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174 octave_value
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175 dispatch_kron (const octave_value& a, const octave_value& b)
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176 {
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177 octave_value retval;
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178 if (a.is_perm_matrix () && b.is_perm_matrix ())
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179 retval = do_kron<PermMatrix, PermMatrix> (a, b);
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180 else if (a.issparse () || b.issparse ())
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181 {
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182 if (a.iscomplex () || b.iscomplex ())
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183 retval = do_kron<SparseComplexMatrix, SparseComplexMatrix> (a, b);
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184 else
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185 retval = do_kron<SparseMatrix, SparseMatrix> (a, b);
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186 }
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187 else if (a.is_diag_matrix ())
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188 {
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189 if (b.is_diag_matrix () && a.rows () == a.columns ()
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190 && b.rows () == b.columns ())
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191 {
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192 // We have two diagonal matrices, the product of those will be
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193 // another diagonal matrix. To do that efficiently, extract
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194 // the diagonals as vectors and compute the product. That
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195 // will be another vector, which we then use to construct a
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196 // diagonal matrix object. Note that this will fail if our
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197 // digaonal matrix object is modified to allow the nonzero
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198 // values to be stored off of the principal diagonal (i.e., if
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199 // diag ([1,2], 3) is modified to return a diagonal matrix
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200 // object instead of a full matrix object).
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201
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202 octave_value tmp = dispatch_kron (a.diag (), b.diag ());
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203 retval = tmp.diag ();
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204 }
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205 else if (a.is_single_type () || b.is_single_type ())
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206 {
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207 if (a.iscomplex ())
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208 retval = do_kron<FloatComplexDiagMatrix, FloatComplexMatrix> (a, b);
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209 else if (b.iscomplex ())
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210 retval = do_kron<FloatDiagMatrix, FloatComplexMatrix> (a, b);
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211 else
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212 retval = do_kron<FloatDiagMatrix, FloatMatrix> (a, b);
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213 }
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214 else
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215 {
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216 if (a.iscomplex ())
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217 retval = do_kron<ComplexDiagMatrix, ComplexMatrix> (a, b);
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218 else if (b.iscomplex ())
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219 retval = do_kron<DiagMatrix, ComplexMatrix> (a, b);
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220 else
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221 retval = do_kron<DiagMatrix, Matrix> (a, b);
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222 }
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223 }
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224 else if (a.is_single_type () || b.is_single_type ())
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225 {
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226 if (a.iscomplex ())
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227 retval = do_kron<FloatComplexMatrix, FloatComplexMatrix> (a, b);
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228 else if (b.iscomplex ())
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229 retval = do_kron<FloatMatrix, FloatComplexMatrix> (a, b);
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230 else
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231 retval = do_kron<FloatMatrix, FloatMatrix> (a, b);
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232 }
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233 else
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234 {
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235 if (a.iscomplex ())
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236 retval = do_kron<ComplexMatrix, ComplexMatrix> (a, b);
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237 else if (b.iscomplex ())
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238 retval = do_kron<Matrix, ComplexMatrix> (a, b);
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239 else
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240 retval = do_kron<Matrix, Matrix> (a, b);
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241 }
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242 return retval;
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243 }
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244
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245
21966
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246 DEFUN (kron, args, ,
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247 doc: /* -*- texinfo -*-
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248 @deftypefn {} {} kron (@var{A}, @var{B})
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249 @deftypefnx {} {} kron (@var{A1}, @var{A2}, @dots{})
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250 Form the Kronecker product of two or more matrices.
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251
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252 This is defined block by block as
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253
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254 @example
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255 x = [ a(i,j)*b ]
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256 @end example
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257
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258 For example:
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259
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260 @example
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261 @group
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262 kron (1:4, ones (3, 1))
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263 @result{} 1 2 3 4
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264 1 2 3 4
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265 1 2 3 4
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266 @end group
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267 @end example
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268
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269 If there are more than two input arguments @var{A1}, @var{A2}, @dots{},
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270 @var{An} the Kronecker product is computed as
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271
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272 @example
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273 kron (kron (@var{A1}, @var{A2}), @dots{}, @var{An})
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274 @end example
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275
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276 @noindent
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277 Since the Kronecker product is associative, this is well-defined.
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278 @end deftypefn */)
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279 {
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280 int nargin = args.length ();
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281
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282 if (nargin < 2)
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283 print_usage ();
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284
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285 octave_value retval;
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286
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287 octave_value a = args(0);
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288 octave_value b = args(1);
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289
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290 retval = dispatch_kron (a, b);
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291
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292 for (octave_idx_type i = 2; i < nargin; i++)
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293 retval = dispatch_kron (retval, args(i));
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294
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295 return retval;
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296 }
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297
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298 /*
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299 %!test
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300 %! x = ones (2);
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301 %! assert (kron (x, x), ones (4));
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302
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303 %!shared x, y, z, p1, p2, d1, d2
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304 %! x = [1, 2];
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305 %! y = [-1, -2];
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306 %! z = [1, 2, 3, 4; 1, 2, 3, 4; 1, 2, 3, 4];
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307 %! p1 = eye (3)([2, 3, 1], :); ## Permutation matrix
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308 %! p2 = [0 1 0; 0 0 1; 1 0 0]; ## Non-permutation equivalent
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309 %! d1 = diag ([1 2 3]); ## Diag type matrix
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310 %! d2 = [1 0 0; 0 2 0; 0 0 3]; ## Non-diag equivalent
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311 %!assert (kron (1:4, ones (3, 1)), z)
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312 %!assert (kron (single (1:4), ones (3, 1)), single (z))
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313 %!assert (kron (sparse (1:4), ones (3, 1)), sparse (z))
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314 %!assert (kron (complex (1:4), ones (3, 1)), z)
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315 %!assert (kron (complex (single (1:4)), ones (3, 1)), single (z))
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316 %!assert (kron (x, y, z), kron (kron (x, y), z))
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317 %!assert (kron (x, y, z), kron (x, kron (y, z)))
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318 %!assert (kron (p1, p1), kron (p2, p2))
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319 %!assert (kron (p1, p2), kron (p2, p1))
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320 %!assert (kron (d1, d1), kron (d2, d2))
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321 %!assert (kron (d1, d2), kron (d2, d1))
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322
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323 %!assert (kron (diag ([1, 2]), diag ([3, 4])), diag ([3, 4, 6, 8]))
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324
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325 ## Test for two diag matrices.
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326 ## See the comments above in dispatch_kron for this case.
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327 %!test
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328 %! expected = zeros (16, 16);
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329 %! expected (1, 11) = 3;
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330 %! expected (2, 12) = 4;
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331 %! expected (5, 15) = 6;
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332 %! expected (6, 16) = 8;
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333 %! assert (kron (diag ([1, 2], 2), diag ([3, 4], 2)), expected);
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334 */
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335
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336 OCTAVE_NAMESPACE_END