Mercurial > octave-libtiff
annotate libinterp/corefcn/inv.cc @ 31173:0abc9779f751
Tiff: modified readRGBAImage to use the orientation tag correctly
* __tiff__.cc (F__tiff_read_rgba_image__): modified the way the image
is read to use the orientation tag in the correct way.
author | magedrifaat <magedrifaat@gmail.com> |
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date | Tue, 16 Aug 2022 16:10:10 +0200 |
parents | 09012191bb0c |
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rev | line source |
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1 //////////////////////////////////////////////////////////////////////// |
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2 // |
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3 // Copyright (C) 1996-2022 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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26 #if defined (HAVE_CONFIG_H) |
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27 # include "config.h" |
2928 | 28 #endif |
29 | |
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30 #include "defun.h" |
2928 | 31 #include "error.h" |
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32 #include "errwarn.h" |
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33 #include "ovl.h" |
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34 #include "ops.h" |
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35 #include "ov-re-diag.h" |
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36 #include "ov-cx-diag.h" |
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37 #include "ov-flt-re-diag.h" |
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38 #include "ov-flt-cx-diag.h" |
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39 #include "ov-perm.h" |
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41 OCTAVE_NAMESPACE_BEGIN |
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42 |
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43 DEFUN (inv, args, nargout, |
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44 doc: /* -*- texinfo -*- |
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45 @deftypefn {} {@var{x} =} inv (@var{A}) |
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46 @deftypefnx {} {[@var{x}, @var{rcond}] =} inv (@var{A}) |
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47 @deftypefnx {} {[@dots{}] =} inverse (@dots{}) |
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48 Compute the inverse of the square matrix @var{A}. |
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49 |
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50 Return an estimate of the reciprocal condition number if requested, |
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51 otherwise warn of an ill-conditioned matrix if the reciprocal condition |
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52 number is small. |
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53 |
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54 In general it is best to avoid calculating the inverse of a matrix directly. |
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55 For example, it is both faster and more accurate to solve systems of |
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56 equations (@var{A}*@math{x} = @math{b}) with |
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57 @code{@var{y} = @var{A} \ @math{b}}, rather than |
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58 @code{@var{y} = inv (@var{A}) * @math{b}}. |
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59 |
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60 If called with a sparse matrix, then in general @var{x} will be a full |
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61 matrix requiring significantly more storage. Avoid forming the inverse of a |
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62 sparse matrix if possible. |
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63 |
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64 @code{inverse} is an alias and may be used identically in place of @code{inv}. |
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65 @seealso{ldivide, rdivide, pinv} |
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66 @end deftypefn */) |
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68 if (args.length () != 1) |
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69 print_usage (); |
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71 octave_value arg = args(0); | |
72 | |
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73 if (! arg.isnumeric ()) |
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74 err_wrong_type_arg ("inv", arg); |
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75 |
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76 if (arg.isempty ()) |
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77 return ovl (Matrix ()); |
2928 | 78 |
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79 if (arg.rows () != arg.columns ()) |
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80 err_square_matrix_required ("inv", "A"); |
2928 | 81 |
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82 octave_value result; |
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83 octave_idx_type info; |
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84 double rcond = 0.0; |
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85 float frcond = 0.0; |
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86 bool isfloat = arg.is_single_type (); |
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87 |
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88 if (arg.is_diag_matrix ()) |
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89 { |
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90 rcond = 1.0; |
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91 frcond = 1.0f; |
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92 if (arg.iscomplex ()) |
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93 { |
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94 if (isfloat) |
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95 { |
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96 result = arg.float_complex_diag_matrix_value ().inverse (info); |
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97 if (info == -1) |
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98 frcond = 0.0f; |
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99 else if (nargout > 1) |
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100 frcond = arg.float_complex_diag_matrix_value ().rcond (); |
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101 } |
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102 else |
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103 { |
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104 result = arg.complex_diag_matrix_value ().inverse (info); |
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105 if (info == -1) |
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106 rcond = 0.0; |
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107 else if (nargout > 1) |
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108 rcond = arg.complex_diag_matrix_value ().rcond (); |
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109 } |
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110 } |
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111 else |
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112 { |
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113 if (isfloat) |
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114 { |
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115 result = arg.float_diag_matrix_value ().inverse (info); |
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116 if (info == -1) |
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117 frcond = 0.0f; |
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118 else if (nargout > 1) |
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119 frcond = arg.float_diag_matrix_value ().rcond (); |
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120 } |
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121 else |
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122 { |
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123 result = arg.diag_matrix_value ().inverse (info); |
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124 if (info == -1) |
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125 rcond = 0.0; |
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126 else if (nargout > 1) |
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127 rcond = arg.diag_matrix_value ().rcond (); |
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128 } |
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129 } |
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130 } |
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131 else if (arg.is_perm_matrix ()) |
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132 { |
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133 info = 0; |
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134 rcond = 1.0; |
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135 result = arg.perm_matrix_value ().inverse (); |
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136 } |
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137 else if (isfloat) |
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139 if (arg.isreal ()) |
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140 { |
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141 FloatMatrix m = arg.float_matrix_value (); |
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142 |
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143 MatrixType mattyp = args(0).matrix_type (); |
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144 result = m.inverse (mattyp, info, frcond, true, true); |
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145 args(0).matrix_type (mattyp); |
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146 } |
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147 else if (arg.iscomplex ()) |
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148 { |
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149 FloatComplexMatrix m = arg.float_complex_matrix_value (); |
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150 |
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151 MatrixType mattyp = args(0).matrix_type (); |
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152 result = m.inverse (mattyp, info, frcond, true, true); |
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153 args(0).matrix_type (mattyp); |
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154 } |
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156 else |
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158 if (arg.isreal ()) |
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159 { |
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160 if (arg.issparse ()) |
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161 { |
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162 SparseMatrix m = arg.sparse_matrix_value (); |
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163 |
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164 MatrixType mattyp = args(0).matrix_type (); |
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165 result = m.inverse (mattyp, info, rcond, true, true); |
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166 args(0).matrix_type (mattyp); |
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167 } |
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168 else |
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169 { |
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170 Matrix m = arg.matrix_value (); |
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171 |
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172 MatrixType mattyp = args(0).matrix_type (); |
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173 result = m.inverse (mattyp, info, rcond, true, true); |
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174 args(0).matrix_type (mattyp); |
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175 } |
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176 } |
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177 else if (arg.iscomplex ()) |
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178 { |
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179 if (arg.issparse ()) |
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180 { |
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181 SparseComplexMatrix m = arg.sparse_complex_matrix_value (); |
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182 |
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183 MatrixType mattyp = args(0).matrix_type (); |
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184 result = m.inverse (mattyp, info, rcond, true, true); |
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185 args(0).matrix_type (mattyp); |
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186 } |
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187 else |
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188 { |
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189 ComplexMatrix m = arg.complex_matrix_value (); |
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190 |
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191 MatrixType mattyp = args(0).matrix_type (); |
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192 result = m.inverse (mattyp, info, rcond, true, true); |
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193 args(0).matrix_type (mattyp); |
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194 } |
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195 } |
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196 else |
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197 // Shouldn't get here since we checked for suitable arg earlier. |
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198 // Maybe for some user-defined classes? |
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199 err_wrong_type_arg ("inv", arg); |
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201 |
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202 octave_value_list retval (nargout > 1 ? 2 : 1); |
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203 |
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204 retval(0) = result; |
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205 if (nargout > 1) |
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206 retval(1) = (isfloat ? octave_value (frcond) : octave_value (rcond)); |
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207 |
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208 if (nargout < 2) |
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209 { |
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210 bool is_singular; |
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211 |
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212 if (isfloat) |
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213 is_singular = ((frcond + 1.0f == 1.0f) || octave::math::isnan (frcond)) |
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214 && ! arg.is_scalar_type (); |
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215 else |
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216 is_singular = ((rcond + 1.0 == 1.0) || octave::math::isnan (rcond)) |
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217 && ! arg.is_scalar_type (); |
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218 |
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219 if (info == -1 || is_singular) |
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220 warn_singular_matrix (isfloat ? frcond : rcond); |
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221 } |
2928 | 222 |
223 return retval; | |
224 } | |
225 | |
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226 /* |
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227 ## Basic test for double/single matrices |
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228 %!assert (inv ([1, 2; 3, 4]), [-2, 1; 1.5, -0.5], 5*eps) |
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229 %!test |
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230 %! [xinv, rcond] = inv ([1,2;3,4]); |
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231 %! assert (xinv, [-2, 1; 1.5, -0.5], 5*eps); |
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232 %! assert (isa (rcond, "double")); |
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233 |
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234 %!assert (inv (single ([1, 2; 3, 4])), single ([-2, 1; 1.5, -0.5]), |
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235 %! 5*eps ("single")) |
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236 %!test |
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237 %! [xinv, rcond] = inv (single ([1,2;3,4])); |
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238 %! assert (xinv, single ([-2, 1; 1.5, -0.5]), 5*eps ("single")); |
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239 %! assert (isa (rcond, "single")); |
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240 |
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241 ## Basic test for integer inputs |
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242 %!assert (inv (int32 (2)), 0.5) |
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243 %!assert (inv (uint32 (2)), 0.5) |
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244 %!assert (inv (int64 (2)), 0.5) |
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245 %!assert (inv (uint64 (2)), 0.5) |
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246 |
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247 ## Normal scalar cases |
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248 %!assert (inv (2), 0.5) |
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249 %!test |
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250 %! [xinv, rcond] = inv (2); |
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251 %! assert (xinv, 0.5); |
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252 %! assert (rcond, 1); |
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253 %!assert (inv (single (2)), single (0.5)) |
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254 %!test |
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255 %! [xinv, rcond] = inv (single (2)); |
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256 %! assert (xinv, single (0.5)); |
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257 %! assert (rcond, single (1)); |
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258 %!assert (inv (complex (1, -1)), 0.5+0.5i) |
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259 %!test |
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260 %! [xinv, rcond] = inv (complex (1, -1)); |
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261 %! assert (xinv, 0.5+0.5i); |
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262 %! assert (rcond, 1); |
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263 %!assert (inv (complex (single (1), -1)), single (0.5+0.5i)) |
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264 %!test |
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265 %! [xinv, rcond] = inv (complex (single (1), -1)); |
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266 %! assert (xinv, single (0.5+0.5i)); |
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267 %! assert (rcond, single (1)); |
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268 |
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269 ## Test special inputs |
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270 ## Empty matrix |
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271 %!assert (inv (zeros (2,0)), []) |
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272 |
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273 ## Scalar "0" |
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274 %!assert (inv (0), Inf) |
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275 %!test |
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276 %! [xinv, rcond] = inv (0); |
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277 %! assert (xinv, Inf); |
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278 %! assert (rcond, 0); |
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279 %!assert (inv (single (0)), single (Inf)) |
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280 %!test |
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281 %! [xinv, rcond] = inv (single (0)); |
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282 %! assert (xinv, single (Inf)); |
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283 %! assert (rcond, single (0)); |
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284 %!assert (inv (complex (0, 0)), Inf) |
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285 %!test |
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286 %! [xinv, rcond] = inv (complex (0, 0)); |
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287 %! assert (xinv, Inf); |
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288 %! assert (rcond, 0); |
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289 %!assert (inv (complex (single (0), 0)), single (Inf)) |
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290 %!test |
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291 %! [xinv, rcond] = inv (complex (single (0), 0)); |
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292 %! assert (xinv, single (Inf)); |
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293 %! assert (rcond, single (0)); |
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294 ## NOTE: Matlab returns +Inf for -0 input, but it returns -Inf for 1/-0. |
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295 ## These should be the same, and in Octave they are. |
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296 %!assert (inv (-0), -Inf) |
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297 %!test |
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298 %! [xinv, rcond] = inv (-0); |
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299 %! assert (xinv, -Inf); |
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300 %! assert (rcond, 0); |
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301 |
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302 ## Scalar "Inf" |
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303 %!assert (inv (Inf), 0) |
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304 %!test |
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305 %! [xinv, rcond] = inv (Inf); |
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306 %! assert (xinv, 0); |
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307 %! assert (rcond, 0); |
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308 %!assert (inv (single (Inf)), single (0)) |
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309 %!test |
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310 %! [xinv, rcond] = inv (single (Inf)); |
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311 %! assert (xinv, single (0)); |
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312 %! assert (rcond, single (0)); |
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313 %!assert (inv (complex (1, Inf)), 0) |
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314 %!test |
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315 %! [xinv, rcond] = inv (complex (1, Inf)); |
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316 %! assert (xinv, 0); |
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317 %! assert (rcond, 0); |
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318 %!assert (inv (complex (single (1), Inf)), single (0)) |
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319 %!test |
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320 %! [xinv, rcond] = inv (complex (single (1), Inf)); |
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321 %! assert (xinv, single (0)); |
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322 %! assert (rcond, single (0)); |
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323 |
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324 ## Scalar "NaN" |
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325 %!assert (inv (NaN), NaN) |
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326 %!test |
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327 %! [xinv, rcond] = inv (NaN); |
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328 %! assert (xinv, NaN); |
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329 %! assert (rcond, NaN); |
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330 %!assert (inv (single (NaN)), single (NaN)) |
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331 %!test |
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332 %! [xinv, rcond] = inv (single (NaN)); |
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333 %! assert (xinv, single (NaN)); |
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334 %! assert (rcond, single (NaN)); |
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335 %!assert (inv (complex (1, NaN)), complex (NaN, NaN)) |
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336 %!test |
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337 %! [xinv, rcond] = inv (complex (1, NaN)); |
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338 %! assert (xinv, complex (NaN, NaN)); |
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339 %! assert (rcond, NaN); |
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340 %!assert (inv (complex (single (1), NaN)), complex (single (NaN), NaN)) |
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341 %!test |
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342 %! [xinv, rcond] = inv (complex (single (1), NaN)); |
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343 %! assert (xinv, complex (single (NaN), NaN)); |
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344 %! assert (rcond, single (NaN)); |
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345 |
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346 ## Matrix special values |
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347 ## Matrix of all zeroes |
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348 %!warning <matrix singular> assert (inv (zeros (2,2)), Inf (2,2)) |
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349 %!test |
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350 %! [xinv, rcond] = inv (zeros (2,2)); |
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351 %! assert (xinv, Inf (2,2)); |
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352 %! assert (rcond, 0); |
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353 ## Matrix of all Inf |
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354 %!warning <rcond = > assert (inv (Inf (2,2)), NaN (2,2)) |
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355 %!test |
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356 %! [xinv, rcond] = inv (Inf (2,2)); |
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357 %! assert (xinv, NaN (2,2)); |
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358 %! assert (rcond, NaN); |
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359 ## Matrix of all NaN |
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360 %!warning <rcond = > assert (inv (NaN (2,2)), NaN (2,2)) |
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361 %!test |
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362 %! [xinv, rcond] = inv (NaN (2,2)); |
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363 %! assert (xinv, NaN (2,2)); |
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364 %! assert (rcond, NaN); |
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365 |
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366 ## Special diagonal matrices |
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367 %!test |
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368 %! fail ("A = inv (diag ([1, 0, 1]))", "warning", "matrix singular"); |
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369 %! assert (A, diag ([Inf, Inf, Inf])); |
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370 |
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371 ## Special sparse matrices |
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372 %!testif HAVE_UMFPACK <*56232> |
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373 %! fail ("A = inv (sparse ([1, 2;0 ,0]))", "warning", "matrix singular"); |
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374 %! assert (A, sparse ([Inf, Inf; 0, 0])); |
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375 |
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376 %!testif HAVE_UMFPACK <*56232> |
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377 %! fail ("A = inv (sparse ([1i, 2;0 ,0]))", "warning", "matrix singular"); |
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378 %! assert (A, sparse ([Inf, Inf; 0, 0])); |
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379 |
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380 %!testif HAVE_UMFPACK <*56232> |
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381 %! fail ("A = inv (sparse ([1, 0, 0; 0, 0, 0; 0, 0, 1]))", |
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382 %! "warning", "matrix singular"); |
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383 %! assert (A, sparse ([Inf, 0, 0; 0, 0, 0; 0, 0, Inf])); |
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384 |
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385 %!error <Invalid call> inv () |
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386 %!error <Invalid call> inv ([1, 2; 3, 4], 2) |
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387 %!error <wrong type argument> inv ("Hello World") |
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388 %!error <wrong type argument> inv ({1}) |
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389 %!error <wrong type argument> inv (true) |
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390 %!error <must be a square matrix> inv ([1, 2; 3, 4; 5, 6]) |
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391 %!error <inverse of the null matrix not defined> inv (sparse (2, 2, 0)) |
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392 %!error <inverse of the null matrix not defined> inv (diag ([0, 0])) |
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393 %!error <inverse of the null matrix not defined> inv (diag (complex ([0, 0]))) |
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394 */ |
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395 |
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396 DEFALIAS (inverse, inv); |
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397 |
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398 OCTAVE_NAMESPACE_END |