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Fix conversion from PermMatrix to SparseMatrix. From 76c98628f1943d583d5813321ec0a3c684d7ac84 Mon Sep 17 00:00:00 2001 Date: Tue, 10 Mar 2009 14:12:59 -0400 The result was transposed and missing its values. Also add a test case. Signed-off-by: Jason Riedy <jason@acm.org> --- liboctave/ChangeLog | 6 ++++++ liboctave/dSparse.cc | 7 +++++-- test/ChangeLog | 4 ++++ test/test_diag_perm.m | 9 +++++++++ 4 files changed, 24 insertions(+), 2 deletions(-)
author Jason Riedy <jason@acm.org>
date Tue, 10 Mar 2009 15:44:11 -0400
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children 43aec7c168eb
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1 ## Copyright (C) 2009 E. Jason Riedy
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2 ##
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3 ## This file is part of Octave.
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4 ##
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5 ## Octave is free software; you can redistribute it and/or modify it
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6 ## under the terms of the GNU General Public License as published by
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7 ## the Free Software Foundation; either version 3 of the License, or (at
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8 ## your option) any later version.
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9 ##
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10 ## Octave is distributed in the hope that it will be useful, but
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11 ## WITHOUT ANY WARRANTY; without even the implied warranty of
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12 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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13 ## General Public License for more details.
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14 ##
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15 ## You should have received a copy of the GNU General Public License
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16 ## along with Octave; see the file COPYING. If not, see
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17 ## <http://www.gnu.org/licenses/>.
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18
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19 ########################################
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20 ## Permutation matrices
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21
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22 ## row permutation
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23 %!test
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24 %! n = 5;
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25 %! A = rand (n);
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26 %! perm = randperm (n);
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27 %! Prow = eye (n) (perm, :);
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28 %! assert (A(perm, :), Prow * A);
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29 %! invperm(perm) = 1:n;
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30 %! assert (Prow \ A, A(invperm, :));
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31 %! assert (Prow' * A, A(invperm, :));
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32
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33 ## column permutation
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34 %!test
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35 %! n = 7;
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36 %! A = rand (n);
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37 %! perm = randperm (n);
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38 %! Pcol = eye (n) (:, perm);
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39 %! assert (A(:, perm), A * Pcol);
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40 %! invperm(perm) = 1:n;
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41 %! assert (A / Pcol, A(:, invperm));
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42 %! assert (A * Pcol.', A(:, invperm));
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43
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44 ## fall back to a matrix in addition
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45 %!test
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46 %! n = 4;
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47 %! P1 = eye (n) (:, randperm (n));
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48 %! A = zeros (n) + P1;
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49 %! assert (sum (A), ones (1, n));
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50 %! assert (sum (A, 2), ones (n, 1));
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51
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52 ## preserve dense matrix structure
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53 %!test
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54 %! n = 7;
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55 %! Pc = eye (n) (:, randperm (n));
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56 %! Pr = eye (n) (randperm (n), :);
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57 %! assert (typeinfo (rand (n) * Pc), "matrix");
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58 %! assert (typeinfo (Pr * rand (n)), "matrix");
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59
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60 ## permuting a matrix with exceptional values does not introduce new ones.
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61 %!test
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62 %! n = 5;
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63 %! pc = randperm (n);
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64 %! Pc = eye (n) (:, pc);
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65 %! pr = randperm (n);
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66 %! Pr = eye (n) (pr, :);
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67 %! A = rand (n);
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68 %! A(n, n-2) = NaN;
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69 %! A(3, 1) = Inf;
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70 %! assert (Pr * A * Pc, A(pr, pc));
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71
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72 ## conversion to sparse form
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73 %!test
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74 %! n = 7;
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75 %! P = eye (n) (:, randperm (n));
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76 %! sP = sparse (P);
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77 %! assert (full (sP), full (P));
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78 %! assert (size (find (sP), 1), n);
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79
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80 ########################################
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81 ## Diagonal matrices
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82
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83 ## square row scaling
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84 %!test
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85 %! m = 7;
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86 %! n = 11;
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87 %! A = rand (m, n);
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88 %! scalefact = rand (m, 1);
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89 %! Dr = diag (scalefact);
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90 %! assert (Dr * A, repmat (scalefact, 1, n) .* A);
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91 %! assert (Dr \ A, A ./ repmat (scalefact, 1, n));
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92 %! scalefact(m-1) = Inf;
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93 %! Dr(m-1, m-1) = 0;
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94 %! assert (Dr \ A, A ./ repmat (scalefact, 1, n));
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95
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96 ## square column scaling
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97 %!test
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98 %! m = 13;
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99 %! n = 11;
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100 %! A = rand (m, n);
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101 %! scalefact = rand (1, n);
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102 %! Dc = diag (scalefact);
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103 %! assert (A * Dc, repmat (scalefact, m, 1) .* A);
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104 %! assert (A / Dc, A ./ repmat (scalefact, m, 1));
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105 %! scalefact(n-1) = Inf;
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106 %! Dc(n-1, n-1) = 0;
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107 %! assert (A / Dc, A ./ repmat (scalefact, m, 1));
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108
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109 ## arithmetic
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110 %!test
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111 %! m = 9;
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112 %! n = 7;
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113 %! mn = min (m, n);
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114 %! d1 = rand (mn, 1) + I () * rand (mn, 1);
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115 %! D1 = diag (d1, m, n);
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116 %! d2 = rand (mn, 1);
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117 %! D2 = diag (d2, m, n);
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118 %! D1D2 = D1 + D2;
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119 %! assert (typeinfo (D1D2), "complex diagonal matrix");
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120 %! assert (diag (D1D2), d1 + d2);
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121 %! D1D2 = D2.' * D1;
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122 %! assert (typeinfo (D1D2), "complex diagonal matrix");
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123 %! assert (diag (D1D2), d1 .* d2);
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124
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125 ## slicing
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126 %!test
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127 %! m = 13;
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128 %! n = 6;
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129 %! mn = min (m, n);
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130 %! d = rand (mn, 1);
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131 %! D = diag (d, m, n);
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132 %! Dslice = D (1:(m-3), 1:(n-2));
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133 %! assert (typeinfo (Dslice), "diagonal matrix");
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134
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135 ## preserve dense matrix structure
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136 %!assert (typeinfo (rand (8) * (3 * eye (8))), "matrix");
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137 %!assert (typeinfo ((3 * eye (8)) * rand (8)), "matrix");
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138
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139 ## scaling a matrix with exceptional values does not introduce new ones.
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140 %!test
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141 %! n = 6;
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142 %! dr = rand (n, 1);
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143 %! Dr = diag (dr);
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144 %! dc = rand (1, n);
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Jason Riedy <jason@acm.org>
parents:
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145 %! Dc = diag (dc);
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Jason Riedy <jason@acm.org>
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146 %! A = rand (n);
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147 %! A(n, n-2) = NaN;
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148 %! A(4, 1) = Inf;
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149 %! assert (Dr * A * Dc, A .* kron (dr, dc), eps);
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150