Mercurial > octave
annotate libinterp/corefcn/matrix_type.cc @ 23581:c3075ae020e1
maint: Deprecate is_complex_type and replace with iscomplex.
* ov.h (is_complex_type): Use OCTAVE_DEPRECATED macro around function.
* ov.h (iscomplex): New function.
* __ichol__.cc, __ilu__.cc, balance.cc, bsxfun.cc, cellfun.cc, conv2.cc,
daspk.cc, dasrt.cc, dassl.cc, data.cc, det.cc, dot.cc, fft.cc, fft2.cc,
fftn.cc, filter.cc, find.cc, givens.cc, graphics.cc, gsvd.cc, hess.cc,
hex2num.cc, inv.cc, kron.cc, lookup.cc, ls-mat-ascii.cc, ls-mat4.cc,
ls-mat5.cc, lsode.cc, lu.cc, matrix_type.cc, mex.cc, mgorth.cc, ordschur.cc,
pinv.cc, psi.cc, quad.cc, qz.cc, rcond.cc, schur.cc, sparse-xpow.cc, sparse.cc,
sqrtm.cc, svd.cc, sylvester.cc, symtab.cc, typecast.cc, variables.cc, xnorm.cc,
__eigs__.cc, amd.cc, ccolamd.cc, chol.cc, colamd.cc, qr.cc, symbfact.cc,
ov-base.h, ov-complex.h, ov-cx-diag.h, ov-cx-mat.h, ov-cx-sparse.h,
ov-flt-complex.h, ov-flt-cx-diag.h, ov-flt-cx-mat.h, jit-typeinfo.cc,
pt-tm-const.cc: Replace instances of is_complex_type with iscomplex.
author | Rik <rik@octave.org> |
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date | Mon, 12 Jun 2017 21:18:23 -0700 |
parents | 092078913d54 |
children | b7747a2c88b2 |
rev | line source |
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5323 | 1 /* |
2 | |
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3 Copyright (C) 2005-2017 David Bateman |
5323 | 4 |
5720 | 5 This file is part of Octave. |
6 | |
5323 | 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 |
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9 the Free Software Foundation; either version 3 of the License, or |
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10 (at your option) any later version. |
5323 | 11 |
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12 Octave is distributed in the hope that it will be useful, but |
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13 WITHOUT ANY WARRANTY; without even the implied warranty of |
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14 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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15 GNU General Public License for more details. |
5323 | 16 |
17 You should have received a copy of the GNU General Public License | |
7016 | 18 along with Octave; see the file COPYING. If not, see |
19 <http://www.gnu.org/licenses/>. | |
5323 | 20 |
21 */ | |
22 | |
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23 #if defined (HAVE_CONFIG_H) |
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24 # include "config.h" |
5323 | 25 #endif |
26 | |
5403 | 27 #include <algorithm> |
28 | |
5323 | 29 #include "ov.h" |
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30 #include "defun.h" |
5323 | 31 #include "error.h" |
5785 | 32 #include "ov-re-mat.h" |
33 #include "ov-cx-mat.h" | |
5323 | 34 #include "ov-re-sparse.h" |
35 #include "ov-cx-sparse.h" | |
5785 | 36 #include "MatrixType.h" |
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37 #include "oct-locbuf.h" |
5323 | 38 |
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39 DEFUN (matrix_type, args, , |
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40 doc: /* -*- texinfo -*- |
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41 @deftypefn {} {@var{type} =} matrix_type (@var{A}) |
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42 @deftypefnx {} {@var{type} =} matrix_type (@var{A}, "nocompute") |
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43 @deftypefnx {} {@var{A} =} matrix_type (@var{A}, @var{type}) |
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44 @deftypefnx {} {@var{A} =} matrix_type (@var{A}, "upper", @var{perm}) |
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45 @deftypefnx {} {@var{A} =} matrix_type (@var{A}, "lower", @var{perm}) |
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46 @deftypefnx {} {@var{A} =} matrix_type (@var{A}, "banded", @var{nl}, @var{nu}) |
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47 Identify the matrix type or mark a matrix as a particular type. |
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48 |
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49 This allows more rapid solutions of linear equations involving @var{A} to be |
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50 performed. |
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51 |
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52 Called with a single argument, @code{matrix_type} returns the type of the |
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53 matrix and caches it for future use. |
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54 |
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55 Called with more than one argument, @code{matrix_type} allows the type of |
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56 the matrix to be defined. |
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57 |
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58 If the option @qcode{"nocompute"} is given, the function will not attempt |
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59 to guess the type if it is still unknown. This is useful for debugging |
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60 purposes. |
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61 |
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62 The possible matrix types depend on whether the matrix is full or sparse, |
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63 and can be one of the following |
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64 |
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65 @table @asis |
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66 @item @qcode{"unknown"} |
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67 Remove any previously cached matrix type, and mark type as unknown. |
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68 |
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69 @item @qcode{"full"} |
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70 Mark the matrix as full. |
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71 |
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72 @item @qcode{"positive definite"} |
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73 Probable full positive definite matrix. |
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74 |
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75 @item @qcode{"diagonal"} |
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76 Diagonal matrix. (Sparse matrices only) |
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77 |
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78 @item @qcode{"permuted diagonal"} |
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79 Permuted Diagonal matrix. The permutation does not need to be specifically |
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80 indicated, as the structure of the matrix explicitly gives this. (Sparse |
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81 matrices only) |
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82 |
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83 @item @qcode{"upper"} |
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84 Upper triangular. If the optional third argument @var{perm} is given, the |
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85 matrix is assumed to be a permuted upper triangular with the permutations |
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86 defined by the vector @var{perm}. |
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87 |
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88 @item @qcode{"lower"} |
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89 Lower triangular. If the optional third argument @var{perm} is given, the |
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90 matrix is assumed to be a permuted lower triangular with the permutations |
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91 defined by the vector @var{perm}. |
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92 |
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93 @item @qcode{"banded"} |
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94 @itemx @qcode{"banded positive definite"} |
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95 Banded matrix with the band size of @var{nl} below the diagonal and @var{nu} |
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96 above it. If @var{nl} and @var{nu} are 1, then the matrix is tridiagonal |
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97 and treated with specialized code. In addition the matrix can be marked as |
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98 probably a positive definite. (Sparse matrices only) |
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99 |
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100 @item @qcode{"singular"} |
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101 The matrix is assumed to be singular and will be treated with a minimum norm |
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102 solution. |
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103 |
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104 @end table |
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105 |
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106 Note that the matrix type will be discovered automatically on the first |
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107 attempt to solve a linear equation involving @var{A}. Therefore |
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108 @code{matrix_type} is only useful to give Octave hints of the matrix type. |
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109 Incorrectly defining the matrix type will result in incorrect results from |
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110 solutions of linear equations; it is entirely @strong{the responsibility of |
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111 the user} to correctly identify the matrix type. |
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112 |
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113 Also, the test for positive definiteness is a low-cost test for a Hermitian |
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114 matrix with a real positive diagonal. This does not guarantee that the |
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115 matrix is positive definite, but only that it is a probable candidate. When |
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116 such a matrix is factorized, a Cholesky@tie{}factorization is first |
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117 attempted, and if that fails the matrix is then treated with an |
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118 LU@tie{}factorization. Once the matrix has been factorized, |
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119 @code{matrix_type} will return the correct classification of the matrix. |
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120 @end deftypefn */) |
5323 | 121 { |
122 int nargin = args.length (); | |
123 | |
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124 if (nargin == 0 || nargin > 4) |
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126 |
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127 bool autocomp = true; |
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128 if (nargin == 2 && args(1).is_string () |
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129 && args(1).string_value () == "nocompute") |
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130 { |
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131 nargin = 1; |
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132 autocomp = false; |
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133 } |
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134 |
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135 octave_value retval; |
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136 |
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137 if (args(0).is_scalar_type ()) |
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138 { |
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139 if (nargin == 1) |
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140 retval = octave_value ("Diagonal"); |
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141 else |
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142 retval = args(0); |
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143 } |
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144 else if (args(0).is_sparse_type ()) |
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145 { |
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146 if (nargin == 1) |
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147 { |
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148 MatrixType mattyp; |
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149 |
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150 if (args(0).iscomplex ()) |
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151 { |
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152 mattyp = args(0).matrix_type (); |
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153 |
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154 if (mattyp.is_unknown () && autocomp) |
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155 { |
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156 SparseComplexMatrix m = |
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157 args(0).sparse_complex_matrix_value (); |
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158 |
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159 mattyp = MatrixType (m); |
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160 args(0).matrix_type (mattyp); |
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161 } |
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162 } |
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163 else |
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164 { |
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165 mattyp = args(0).matrix_type (); |
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166 |
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167 if (mattyp.is_unknown () && autocomp) |
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168 { |
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169 SparseMatrix m = args(0).sparse_matrix_value (); |
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170 |
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171 mattyp = MatrixType (m); |
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172 args(0).matrix_type (mattyp); |
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173 } |
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174 } |
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175 |
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176 int typ = mattyp.type (); |
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177 |
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178 if (typ == MatrixType::Diagonal) |
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179 retval = octave_value ("Diagonal"); |
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180 else if (typ == MatrixType::Permuted_Diagonal) |
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181 retval = octave_value ("Permuted Diagonal"); |
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182 else if (typ == MatrixType::Upper) |
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183 retval = octave_value ("Upper"); |
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184 else if (typ == MatrixType::Permuted_Upper) |
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185 retval = octave_value ("Permuted Upper"); |
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186 else if (typ == MatrixType::Lower) |
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187 retval = octave_value ("Lower"); |
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188 else if (typ == MatrixType::Permuted_Lower) |
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189 retval = octave_value ("Permuted Lower"); |
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190 else if (typ == MatrixType::Banded) |
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191 retval = octave_value ("Banded"); |
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192 else if (typ == MatrixType::Banded_Hermitian) |
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193 retval = octave_value ("Banded Positive Definite"); |
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194 else if (typ == MatrixType::Tridiagonal) |
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195 retval = octave_value ("Tridiagonal"); |
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196 else if (typ == MatrixType::Tridiagonal_Hermitian) |
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197 retval = octave_value ("Tridiagonal Positive Definite"); |
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198 else if (typ == MatrixType::Hermitian) |
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199 retval = octave_value ("Positive Definite"); |
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200 else if (typ == MatrixType::Rectangular) |
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201 { |
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202 if (args(0).rows () == args(0).columns ()) |
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203 retval = octave_value ("Singular"); |
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204 else |
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205 retval = octave_value ("Rectangular"); |
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206 } |
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207 else if (typ == MatrixType::Full) |
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208 retval = octave_value ("Full"); |
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209 else |
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210 retval = octave_value ("Unknown"); |
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211 } |
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212 else |
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213 { |
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214 // Ok, we're changing the matrix type |
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215 std::string str_typ = args(1).xstring_value ("matrix_type: TYPE must be a string"); |
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216 |
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217 // FIXME: why do I have to explicitly call the constructor? |
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218 MatrixType mattyp = MatrixType (); |
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219 |
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220 octave_idx_type nl = 0; |
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221 octave_idx_type nu = 0; |
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222 |
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223 // Use STL function to convert to lower case |
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224 std::transform (str_typ.begin (), str_typ.end (), |
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225 str_typ.begin (), tolower); |
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226 |
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227 if (str_typ == "diagonal") |
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228 mattyp.mark_as_diagonal (); |
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229 if (str_typ == "permuted diagonal") |
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230 mattyp.mark_as_permuted_diagonal (); |
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231 else if (str_typ == "upper") |
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232 mattyp.mark_as_upper_triangular (); |
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233 else if (str_typ == "lower") |
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234 mattyp.mark_as_lower_triangular (); |
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235 else if (str_typ == "banded" |
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236 || str_typ == "banded positive definite") |
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237 { |
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238 if (nargin != 4) |
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239 error ("matrix_type: banded matrix type requires 4 arguments"); |
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240 |
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241 nl = args(2).xnint_value ("matrix_type: band size NL, NU must be integers"); |
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242 nu = args(3).xnint_value ("matrix_type: band size NL, NU must be integers"); |
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243 |
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244 if (nl == 1 && nu == 1) |
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245 mattyp.mark_as_tridiagonal (); |
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246 else |
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247 mattyp.mark_as_banded (nu, nl); |
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248 |
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249 if (str_typ == "banded positive definite") |
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250 mattyp.mark_as_symmetric (); |
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251 } |
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252 else if (str_typ == "positive definite") |
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253 { |
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254 mattyp.mark_as_full (); |
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255 mattyp.mark_as_symmetric (); |
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256 } |
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257 else if (str_typ == "singular") |
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258 mattyp.mark_as_rectangular (); |
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259 else if (str_typ == "full") |
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260 mattyp.mark_as_full (); |
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261 else if (str_typ == "unknown") |
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262 mattyp.invalidate_type (); |
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263 else |
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264 error ("matrix_type: Unknown matrix type %s", str_typ.c_str ()); |
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265 |
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266 if (nargin == 3 |
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267 && (str_typ == "upper" || str_typ == "lower")) |
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268 { |
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269 const ColumnVector perm = args(2).vector_value ("matrix_type: Invalid permutation vector PERM"); |
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270 |
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271 octave_idx_type len = perm.numel (); |
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272 dim_vector dv = args(0).dims (); |
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273 |
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274 if (len != dv(0)) |
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275 error ("matrix_type: Invalid permutation vector PERM"); |
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276 |
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277 OCTAVE_LOCAL_BUFFER (octave_idx_type, p, len); |
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278 |
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279 for (octave_idx_type i = 0; i < len; i++) |
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280 p[i] = static_cast<octave_idx_type> (perm (i)) - 1; |
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281 |
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282 mattyp.mark_as_permuted (len, p); |
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283 } |
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284 else if (nargin != 2 |
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285 && str_typ != "banded positive definite" |
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286 && str_typ != "banded") |
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287 error ("matrix_type: Invalid number of arguments"); |
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288 |
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289 // Set the matrix type |
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290 if (args(0).iscomplex ()) |
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291 retval = octave_value (args(0).sparse_complex_matrix_value (), |
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292 mattyp); |
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293 else |
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294 retval = octave_value (args(0).sparse_matrix_value (), |
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295 mattyp); |
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296 } |
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297 } |
5323 | 298 else |
299 { | |
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300 if (nargin == 1) |
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301 { |
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302 MatrixType mattyp; |
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303 |
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304 if (args(0).iscomplex ()) |
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305 { |
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306 mattyp = args(0).matrix_type (); |
5323 | 307 |
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308 if (mattyp.is_unknown () && autocomp) |
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309 { |
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310 if (args(0).is_single_type ()) |
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311 { |
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312 FloatComplexMatrix m; |
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313 m = args(0).float_complex_matrix_value (); |
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314 |
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315 mattyp = MatrixType (m); |
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316 args(0).matrix_type (mattyp); |
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317 } |
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318 else |
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319 { |
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320 ComplexMatrix m = args(0).complex_matrix_value (); |
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321 |
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322 mattyp = MatrixType (m); |
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323 args(0).matrix_type (mattyp); |
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324 } |
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325 } |
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326 } |
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327 else |
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328 { |
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329 mattyp = args(0).matrix_type (); |
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330 |
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331 if (mattyp.is_unknown () && autocomp) |
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332 { |
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333 if (args(0).is_single_type ()) |
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334 { |
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335 FloatMatrix m = args(0).float_matrix_value (); |
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336 |
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337 mattyp = MatrixType (m); |
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338 args(0).matrix_type (mattyp); |
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339 } |
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340 else |
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341 { |
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342 Matrix m = args(0).matrix_value (); |
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344 mattyp = MatrixType (m); |
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345 args(0).matrix_type (mattyp); |
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346 } |
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347 } |
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348 } |
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349 |
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350 int typ = mattyp.type (); |
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351 |
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352 if (typ == MatrixType::Upper) |
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353 retval = octave_value ("Upper"); |
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354 else if (typ == MatrixType::Permuted_Upper) |
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355 retval = octave_value ("Permuted Upper"); |
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356 else if (typ == MatrixType::Lower) |
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357 retval = octave_value ("Lower"); |
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358 else if (typ == MatrixType::Permuted_Lower) |
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359 retval = octave_value ("Permuted Lower"); |
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360 else if (typ == MatrixType::Hermitian) |
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361 retval = octave_value ("Positive Definite"); |
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362 else if (typ == MatrixType::Rectangular) |
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363 { |
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364 if (args(0).rows () == args(0).columns ()) |
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365 retval = octave_value ("Singular"); |
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366 else |
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367 retval = octave_value ("Rectangular"); |
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368 } |
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369 else if (typ == MatrixType::Full) |
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370 retval = octave_value ("Full"); |
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371 else |
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372 retval = octave_value ("Unknown"); |
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373 } |
5323 | 374 else |
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375 { |
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376 // Ok, we're changing the matrix type |
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377 std::string str_typ = args(1).xstring_value ("matrix_type: TYPE must be a string"); |
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379 // FIXME: why do I have to explicitly call the constructor? |
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380 MatrixType mattyp = MatrixType (MatrixType::Unknown, true); |
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381 |
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382 // Use STL function to convert to lower case |
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383 std::transform (str_typ.begin (), str_typ.end (), |
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384 str_typ.begin (), tolower); |
5785 | 385 |
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386 if (str_typ == "upper") |
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387 mattyp.mark_as_upper_triangular (); |
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388 else if (str_typ == "lower") |
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389 mattyp.mark_as_lower_triangular (); |
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390 else if (str_typ == "positive definite") |
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391 { |
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392 mattyp.mark_as_full (); |
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393 mattyp.mark_as_symmetric (); |
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394 } |
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395 else if (str_typ == "singular") |
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396 mattyp.mark_as_rectangular (); |
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397 else if (str_typ == "full") |
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398 mattyp.mark_as_full (); |
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399 else if (str_typ == "unknown") |
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400 mattyp.invalidate_type (); |
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401 else |
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402 error ("matrix_type: Unknown matrix type %s", str_typ.c_str ()); |
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403 |
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404 if (nargin == 3 && (str_typ == "upper" || str_typ == "lower")) |
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405 { |
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406 const ColumnVector perm = args(2).vector_value ("matrix_type: Invalid permutation vector PERM"); |
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407 |
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408 octave_idx_type len = perm.numel (); |
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409 dim_vector dv = args(0).dims (); |
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410 |
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411 if (len != dv(0)) |
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412 error ("matrix_type: Invalid permutation vector PERM"); |
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413 |
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414 OCTAVE_LOCAL_BUFFER (octave_idx_type, p, len); |
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415 |
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416 for (octave_idx_type i = 0; i < len; i++) |
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417 p[i] = static_cast<octave_idx_type> (perm (i)) - 1; |
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419 mattyp.mark_as_permuted (len, p); |
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420 } |
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421 else if (nargin != 2) |
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422 error ("matrix_type: Invalid number of arguments"); |
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424 // Set the matrix type |
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425 if (args(0).is_single_type ()) |
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426 { |
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427 if (args(0).iscomplex ()) |
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428 retval = octave_value (args(0).float_complex_matrix_value (), |
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429 mattyp); |
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430 else |
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431 retval = octave_value (args(0).float_matrix_value (), |
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432 mattyp); |
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433 } |
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434 else |
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435 { |
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436 if (args(0).iscomplex ()) |
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437 retval = octave_value (args(0).complex_matrix_value (), |
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438 mattyp); |
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439 else |
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440 retval = octave_value (args(0).matrix_value (), mattyp); |
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441 } |
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442 } |
5323 | 443 } |
444 | |
445 return retval; | |
446 } | |
447 | |
448 /* | |
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449 ## FIXME: |
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450 ## Disable tests for lower under-determined and upper over-determined |
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451 ## matrices as this detection is disabled in MatrixType due to issues |
5681 | 452 ## of non minimum norm solution being found. |
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453 |
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454 %!assert (matrix_type (speye (10,10)), "Diagonal") |
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455 %!assert (matrix_type (speye (10,10)([2:10,1],:)), "Permuted Diagonal") |
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456 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1;sparse(9,1);1]]), "Upper") |
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457 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1;sparse(9,1);1]](:,[2,1,3:11])), "Permuted Upper") |
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458 %!assert (matrix_type ([speye(10,10),sparse(10,1);1,sparse(1,9),1]), "Lower") |
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459 %!assert (matrix_type ([speye(10,10),sparse(10,1);1,sparse(1,9),1]([2,1,3:11],:)), "Permuted Lower") |
5610 | 460 |
461 %!test | |
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462 %! bnd = spparms ("bandden"); |
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463 %! spparms ("bandden", 0.5); |
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464 %! a = spdiags (rand (10,3)-0.5,[-1,0,1],10,10); |
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465 %! assert (matrix_type (a), "Tridiagonal"); |
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466 %! assert (matrix_type (a'+a+2*speye (10)), "Tridiagonal Positive Definite"); |
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467 %! spparms ("bandden", bnd); |
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468 %!test |
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469 %! bnd=spparms ("bandden"); |
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470 %! spparms ("bandden", 0.5); |
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471 %! a = spdiags (randn (10,4),[-2:1],10,10); |
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472 %! assert (matrix_type (a), "Banded"); |
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473 %! assert (matrix_type (a'*a), "Banded Positive Definite"); |
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474 %! spparms ("bandden", bnd); |
5610 | 475 %!test |
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476 %! a = [speye(10,10),[sparse(9,1);1];-1,sparse(1,9),1]; |
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477 %! assert (matrix_type (a), "Full"); |
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478 %! assert (matrix_type (a'*a), "Positive Definite"); |
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479 |
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480 %!assert (matrix_type (speye (10,11)), "Diagonal") |
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481 %!assert (matrix_type (speye (10,11)([2:10,1],:)), "Permuted Diagonal") |
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482 %!assert (matrix_type (speye (11,10)), "Diagonal") |
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483 %!assert (matrix_type (speye (11,10)([2:11,1],:)), "Permuted Diagonal") |
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484 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1,1];sparse(9,2);[1,1]]]), "Upper") |
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485 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1,1];sparse(9,2);[1,1]]](:,[2,1,3:12])), "Permuted Upper") |
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486 %!assert (matrix_type ([speye(11,9),[1;sparse(8,1);1;0]]), "Upper") |
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487 %!assert (matrix_type ([speye(11,9),[1;sparse(8,1);1;0]](:,[2,1,3:10])), "Permuted Upper") |
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488 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1;1],sparse(2,9),[1;1]]), "Lower") |
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489 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1;1],sparse(2,9),[1;1]]([2,1,3:12],:)), "Permuted Lower") |
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490 %!assert (matrix_type ([speye(9,11);[1,sparse(1,8),1,0]]), "Lower") |
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491 %!assert (matrix_type ([speye(9,11);[1,sparse(1,8),1,0]]([2,1,3:10],:)), "Permuted Lower") |
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492 %!assert (matrix_type (spdiags (randn (10,4),[-2:1],10,9)), "Rectangular") |
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493 |
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494 %!assert (matrix_type (1i*speye (10,10)), "Diagonal") |
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495 %!assert (matrix_type (1i*speye (10,10)([2:10,1],:)), "Permuted Diagonal") |
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496 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1i;sparse(9,1);1]]), "Upper") |
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497 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1i;sparse(9,1);1]](:,[2,1,3:11])), "Permuted Upper") |
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498 %!assert (matrix_type ([speye(10,10),sparse(10,1);1i,sparse(1,9),1]), "Lower") |
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499 %!assert (matrix_type ([speye(10,10),sparse(10,1);1i,sparse(1,9),1]([2,1,3:11],:)), "Permuted Lower") |
5610 | 500 |
501 %!test | |
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502 %! bnd = spparms ("bandden"); |
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503 %! spparms ("bandden", 0.5); |
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504 %! assert (matrix_type (spdiags (1i*randn (10,3),[-1,0,1],10,10)), "Tridiagonal"); |
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505 %! a = 1i*(rand (9,1)-0.5); |
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506 %! a = [[a;0],ones(10,1),[0;-a]]; |
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507 %! assert (matrix_type (spdiags (a,[-1,0,1],10,10)), "Tridiagonal Positive Definite"); |
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508 %! spparms ("bandden", bnd); |
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509 %!test |
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510 %! bnd = spparms ("bandden"); |
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511 %! spparms ("bandden", 0.5); |
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512 %! assert (matrix_type (spdiags (1i*randn (10,4),[-2:1],10,10)), "Banded"); |
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513 %! a = 1i*(rand (9,2)-0.5); |
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514 %! a = [[a;[0,0]],ones(10,1),[[0;-a(:,2)],[0;0;-a(1:8,1)]]]; |
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515 %! assert (matrix_type (spdiags (a,[-2:2],10,10)), "Banded Positive Definite"); |
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516 %! spparms ("bandden", bnd); |
5785 | 517 %!test |
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518 %! a = [speye(10,10),[sparse(9,1);1i];-1,sparse(1,9),1]; |
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519 %! assert (matrix_type (a), "Full"); |
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520 %! assert (matrix_type (a'*a), "Positive Definite"); |
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521 |
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522 %!assert (matrix_type (1i*speye (10,11)), "Diagonal") |
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523 %!assert (matrix_type (1i*speye (10,11)([2:10,1],:)), "Permuted Diagonal") |
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524 %!assert (matrix_type (1i*speye (11,10)), "Diagonal") |
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525 %!assert (matrix_type (1i*speye (11,10)([2:11,1],:)), "Permuted Diagonal") |
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526 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1i,1i];sparse(9,2);[1i,1i]]]), "Upper") |
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527 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1i,1i];sparse(9,2);[1i,1i]]](:,[2,1,3:12])), "Permuted Upper") |
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528 %!assert (matrix_type ([speye(11,9),[1i;sparse(8,1);1i;0]]), "Upper") |
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529 %!assert (matrix_type ([speye(11,9),[1i;sparse(8,1);1i;0]](:,[2,1,3:10])), "Permuted Upper") |
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530 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1i;1i],sparse(2,9),[1i;1i]]), "Lower") |
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531 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1i;1i],sparse(2,9),[1i;1i]]([2,1,3:12],:)), "Permuted Lower") |
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532 %!assert (matrix_type ([speye(9,11);[1i,sparse(1,8),1i,0]]), "Lower") |
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533 %!assert (matrix_type ([speye(9,11);[1i,sparse(1,8),1i,0]]([2,1,3:10],:)), "Permuted Lower") |
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534 %!assert (matrix_type (1i*spdiags(randn(10,4),[-2:1],10,9)), "Rectangular") |
5785 | 535 |
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536 %!test |
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537 %! a = matrix_type (spdiags (randn (10,3),[-1,0,1],10,10), "Singular"); |
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538 %! assert (matrix_type (a), "Singular"); |
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539 |
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540 %!assert (matrix_type (triu (ones(10,10))), "Upper") |
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541 %!assert (matrix_type (triu (ones(10,10),-1)), "Full") |
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542 %!assert (matrix_type (tril (ones(10,10))), "Lower") |
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543 %!assert (matrix_type (tril (ones(10,10),1)), "Full") |
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544 %!assert (matrix_type (10*eye (10,10) + ones (10,10)), "Positive Definite") |
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545 %!assert (matrix_type (ones (11,10)), "Rectangular") |
5785 | 546 %!test |
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547 %! a = matrix_type (ones (10,10), "Singular"); |
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548 %! assert (matrix_type (a), "Singular"); |
5785 | 549 |
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550 %!assert (matrix_type (triu (1i*ones (10,10))), "Upper") |
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551 %!assert (matrix_type (triu (1i*ones (10,10),-1)), "Full") |
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552 %!assert (matrix_type (tril (1i*ones (10,10))), "Lower") |
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553 %!assert (matrix_type (tril (1i*ones (10,10),1)), "Full") |
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554 %!assert (matrix_type (10*eye (10,10) + 1i*triu (ones (10,10),1) -1i*tril (ones (10,10),-1)), "Positive Definite") |
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555 %!assert (matrix_type (ones (11,10)), "Rectangular") |
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556 %!test |
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557 %! a = matrix_type (ones (10,10), "Singular"); |
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558 %! assert (matrix_type (a), "Singular"); |
5610 | 559 */ |