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1 /* |
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2 |
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3 Copyright (C) 2005 David Bateman |
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4 Copyright (C) 1998-2005 Andy Adler |
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5 |
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6 Octave is free software; you can redistribute it and/or modify it |
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7 under the terms of the GNU General Public License as published by the |
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8 Free Software Foundation; either version 2, or (at your option) any |
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9 later version. |
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10 |
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11 Octave is distributed in the hope that it will be useful, but WITHOUT |
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12 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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13 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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14 for more details. |
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15 |
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16 You should have received a copy of the GNU General Public License |
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17 along with this program; see the file COPYING. If not, write to the |
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18 Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, |
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19 Boston, MA 02110-1301, USA. |
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20 |
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21 */ |
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22 |
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23 #ifdef HAVE_CONFIG_H |
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24 #include <config.h> |
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25 #endif |
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26 |
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27 #if HAVE_CXSPARSE |
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28 #include <cxsparse/cxs.h> |
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29 #endif |
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30 |
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31 #include "defun-dld.h" |
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32 #include "error.h" |
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33 #include "gripes.h" |
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34 #include "oct-obj.h" |
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35 #include "utils.h" |
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36 |
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37 #include "ov-re-sparse.h" |
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38 #include "ov-cx-sparse.h" |
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39 #include "SparseQR.h" |
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40 #include "SparseCmplxQR.h" |
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41 |
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42 #ifdef IDX_TYPE_LONG |
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43 #define CSSPARSE_NAME(name) name ## _dl |
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44 #else |
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45 #define CSSPARSE_NAME(name) name ## _di |
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46 #endif |
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47 |
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48 // PKG_ADD: dispatch ("qr", "spqr", "sparse matrix"); |
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49 // PKG_ADD: dispatch ("qr", "spqr", "sparse complex matrix"); |
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50 // PKG_ADD: dispatch ("qr", "spqr", "sparse bool matrix"); |
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51 DEFUN_DLD (spqr, args, nargout, |
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52 "-*- texinfo -*-\n\ |
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53 @deftypefn {Loadable Function} {@var{r} =} spqr (@var{a})\n\ |
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54 @deftypefnx {Loadable Function} {@var{r} =} spqr (@var{a},0)\n\ |
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55 @deftypefnx {Loadable Function} {[@var{c}, @var{r}] =} spqr (@var{a},@var{b})\n\ |
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56 @deftypefnx {Loadable Function} {[@var{c}, @var{r}] =} spqr (@var{a},@var{b},0)\n\ |
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57 @cindex QR factorization\n\ |
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58 Compute the sparse QR factorization of @var{a}, using @sc{CSparse}.\n\ |
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59 As the matrix @var{Q} is in general a full matrix, this function returns\n\ |
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60 the @var{Q}-less factorization @var{r} of @var{a}, such that\n\ |
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61 @code{@var{r} = chol (@var{a}' * @var{a})}.\n\ |
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62 \n\ |
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63 If the final argument is the scalar @code{0} and the number of rows is\n\ |
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64 larger than the number of columns, then an economy factorization is\n\ |
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65 returned. That is @var{r} will have only @code{size (@var{a},1)} rows.\n\ |
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66 \n\ |
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67 If an additional matrix @var{b} is supplied, then @code{spqr} returns\n\ |
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68 @var{c}, where @code{@var{c} = @var{q}' * @var{b}}. This allows the\n\ |
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69 least squares approximation of @code{@var{a} \\ @var{b}} to be calculated\n\ |
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70 as\n\ |
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71 \n\ |
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72 @example\n\ |
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73 [@var{c},@var{r}] = spqr (@var{a},@var{b})\n\ |
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74 @var{x} = @var{r} \\ @var{c}\n\ |
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75 @end example\n\ |
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76 \n\ |
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77 @end deftypefn\n\ |
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78 @seealso{spchol, qr}") |
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79 { |
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80 int nargin = args.length (); |
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81 octave_value_list retval; |
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82 bool economy = false; |
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83 bool is_cmplx = false; |
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84 bool have_b = false; |
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85 |
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86 if (nargin < 1 || nargin > 3) |
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87 print_usage ("spqr"); |
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88 else |
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89 { |
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90 if (args(0).is_complex_type ()) |
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91 is_cmplx = true; |
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92 if (nargin > 1) |
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93 { |
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94 have_b = true; |
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95 if (args(nargin-1).is_scalar_type ()) |
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96 { |
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97 int val = args(nargin-1).int_value (); |
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98 if (val == 0) |
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99 { |
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100 economy = true; |
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101 have_b = (nargin > 2); |
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102 } |
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103 } |
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104 if (have_b && args(1).is_complex_type ()) |
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105 is_cmplx = true; |
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106 } |
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107 |
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108 if (!error_state) |
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109 { |
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110 if (have_b && nargout < 2) |
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111 error ("spqr: incorrect number of output arguments"); |
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112 else if (is_cmplx) |
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113 { |
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114 SparseComplexQR q (args(0).sparse_complex_matrix_value ()); |
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115 if (!error_state) |
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116 { |
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117 if (have_b) |
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118 { |
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119 retval(1) = q.R (economy); |
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120 retval(0) = q.C (args(1).complex_matrix_value ()); |
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121 } |
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122 else |
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123 retval(0) = q.R (economy); |
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124 } |
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125 } |
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126 else |
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127 { |
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128 SparseQR q (args(0).sparse_matrix_value ()); |
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129 if (!error_state) |
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130 { |
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131 if (have_b) |
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132 { |
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133 retval(1) = q.R (economy); |
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134 retval(0) = q.C (args(1).matrix_value ()); |
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135 } |
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136 else |
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137 retval(0) = q.R (economy); |
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138 } |
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139 } |
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140 } |
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141 } |
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142 return retval; |
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143 } |
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144 |
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145 /* |
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146 |
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147 The deactivated tests below can't be tested till rectangular back-subs is |
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148 implemented for sparse matrices. |
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149 |
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150 %!test |
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151 %! n = 20; d= 0.2; |
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152 %! a = sprandn(n,n,d)+speye(n,n); |
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153 %! r = spqr(a); |
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154 %! assert(r'*r,a'*a,1e-10) |
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155 |
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156 %!test |
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157 %! n = 20; d= 0.2; |
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158 %! a = sprandn(n,n,d)+speye(n,n); |
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159 %! q = symamd(a); |
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160 %! a = a(q,q); |
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161 %! r = spqr(a); |
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162 %! assert(r'*r,a'*a,1e-10) |
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163 |
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164 %!test |
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165 %! n = 20; d= 0.2; |
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166 %! a = sprandn(n,n,d)+speye(n,n); |
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167 %! [c,r] = spqr(a,ones(n,1)); |
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168 %! assert (r\c,full(a)\ones(n,1),10e-10) |
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169 |
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170 %!test |
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171 %! n = 20; d= 0.2; |
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172 %! a = sprandn(n,n,d)+speye(n,n); |
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173 %! b = randn(n,2); |
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174 %! [c,r] = spqr(a,b); |
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175 %! assert (r\c,full(a)\b,10e-10) |
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176 |
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177 %% Test under-determined systems!! |
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178 %!#test |
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179 %! n = 20; d= 0.2; |
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180 %! a = sprandn(n,n+1,d)+speye(n,n+1); |
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181 %! b = randn(n,2); |
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182 %! [c,r] = spqr(a,b); |
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183 %! assert (r\c,full(a)\b,10e-10) |
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184 |
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185 %!test |
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186 %! n = 20; d= 0.2; |
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187 %! a = 1i*sprandn(n,n,d)+speye(n,n); |
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188 %! r = spqr(a); |
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189 %! assert(r'*r,a'*a,1e-10) |
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190 |
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191 %!test |
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192 %! n = 20; d= 0.2; |
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193 %! a = 1i*sprandn(n,n,d)+speye(n,n); |
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194 %! q = symamd(a); |
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195 %! a = a(q,q); |
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196 %! r = spqr(a); |
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197 %! assert(r'*r,a'*a,1e-10) |
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198 |
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199 %!test |
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200 %! n = 20; d= 0.2; |
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201 %! a = 1i*sprandn(n,n,d)+speye(n,n); |
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202 %! [c,r] = spqr(a,ones(n,1)); |
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203 %! assert (r\c,full(a)\ones(n,1),10e-10) |
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204 |
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205 %!test |
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206 %! n = 20; d= 0.2; |
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207 %! a = 1i*sprandn(n,n,d)+speye(n,n); |
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208 %! b = randn(n,2); |
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209 %! [c,r] = spqr(a,b); |
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210 %! assert (r\c,full(a)\b,10e-10) |
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211 |
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212 %% Test under-determined systems!! |
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213 %!#test |
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214 %! n = 20; d= 0.2; |
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215 %! a = 1i*sprandn(n,n+1,d)+speye(n,n+1); |
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216 %! b = randn(n,2); |
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217 %! [c,r] = spqr(a,b); |
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218 %! assert (r\c,full(a)\b,10e-10) |
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219 |
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220 %!error spqr(sprandn(10,10,0.2),ones(10,1)); |
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221 |
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222 */ |
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223 |
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224 static RowVector |
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225 put_int (octave_idx_type *p, octave_idx_type n) |
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226 { |
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227 RowVector ret (n); |
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228 for (octave_idx_type i = 0; i < n; i++) |
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229 ret.xelem(i) = p[i] + 1; |
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230 return ret; |
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231 } |
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232 |
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233 DEFUN_DLD (dmperm, args, nargout, |
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234 "-*- texinfo -*-\n\ |
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235 @deftypefn {Loadable Function} {@var{p} =} dmperm (@var{s})\n\ |
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236 @deftypefnx {Loadable Function} {[@var{p}. @var{q}. @var{r}, @var{s}] =} dmperm (@var{s})\n\ |
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237 \n\ |
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238 @cindex Dulmage-Mendelsohn decomposition\n\ |
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239 Perform a Deulmage-Mendelsohn permutation on the sparse matrix @var{s}.\n\ |
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240 With a single output argument @dfn{dmperm} performs the row permutations\n\ |
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241 @var{p} such that @code{@var{s} (@var{p},:)} has no zero elements on the\n\ |
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242 diagonal.\n\ |
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243 \n\ |
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244 Called with two or more output arguments, returns the row and column\n\ |
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245 permutations, such that @code{@var{s} (@var{p}, @var{q})} is in block\n\ |
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246 triangular form. The values of @var{r} and @var{s} define the boundaries\n\ |
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247 of the blocks. If @var{s} is square then @code{@var{r} == @var{s}}.\n\ |
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248 \n\ |
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249 The method used is described in: A. Pothen & C.-J. Fan. Computing the block\n\ |
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250 triangular form of a sparse matrix. ACM Trans. Math. Software,\n\ |
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251 16(4):303-324, 1990.\n\ |
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252 @end deftypefn\n\ |
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253 @seealso{colamd,ccolamd}") |
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254 { |
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255 int nargin = args.length(); |
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256 octave_value_list retval; |
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257 |
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258 #if HAVE_CXSPARSE |
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259 if (nargin != 1) |
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260 { |
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261 print_usage ("dmperm"); |
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262 return retval; |
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263 } |
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264 |
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265 octave_value arg = args(0); |
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266 octave_idx_type nr = arg.rows (); |
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267 octave_idx_type nc = arg.columns (); |
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268 SparseMatrix m; |
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269 SparseComplexMatrix cm; |
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270 CSSPARSE_NAME (cs) csm; |
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271 csm.m = nr; |
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272 csm.n = nc; |
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273 csm.x = NULL; |
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274 csm.nz = -1; |
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275 |
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276 if (arg.is_real_type ()) |
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277 { |
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278 m = arg.sparse_matrix_value (); |
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279 csm.nzmax = m.nnz(); |
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280 csm.p = m.xcidx (); |
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281 csm.i = m.xridx (); |
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282 } |
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283 else |
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284 { |
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285 cm = arg.sparse_complex_matrix_value (); |
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286 csm.nzmax = cm.nnz(); |
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287 csm.p = cm.xcidx (); |
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288 csm.i = cm.xridx (); |
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289 } |
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290 |
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291 if (!error_state) |
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292 { |
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293 if (nargout <= 1) |
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294 { |
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295 octave_idx_type *jmatch = CSSPARSE_NAME (cs_maxtrans) (&csm); |
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296 retval(0) = put_int (jmatch + nr, nc); |
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297 CSSPARSE_NAME (cs_free) (jmatch); |
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298 } |
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299 else |
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300 { |
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301 CSSPARSE_NAME (csd) *dm = CSSPARSE_NAME(cs_dmperm) (&csm); |
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302 //retval(5) = put_int (dm->rr, 5); |
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303 //retval(4) = put_int (dm->cc, 5); |
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304 retval(3) = put_int (dm->S, dm->nb+1); |
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305 retval(2) = put_int (dm->R, dm->nb+1); |
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306 retval(1) = put_int (dm->Q, nc); |
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307 retval(0) = put_int (dm->P, nr); |
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308 CSSPARSE_NAME (cs_dfree) (dm); |
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309 } |
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310 } |
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311 #else |
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312 error ("dmperm: not available in this version of Octave"); |
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313 #endif |
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314 |
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315 return retval; |
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316 } |
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317 |
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318 /* |
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319 |
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320 %!test |
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321 %! n=20; |
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322 %! a=speye(n,n);a=a(randperm(n),:); |
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323 %! assert(a(dmperm(a),:),speye(n)) |
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324 |
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325 %!test |
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326 %! n=20; |
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327 %! d=0.2; |
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328 %! a=tril(sprandn(n,n,d),-1)+speye(n,n); |
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329 %! a=a(randperm(n),randperm(n)); |
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330 %! [p,q,r,s]=dmperm(a); |
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331 %! assert(tril(a(p,q),-1),sparse(n,n)) |
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332 |
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333 */ |
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334 |
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335 /* |
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336 ;;; Local Variables: *** |
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337 ;;; mode: C++ *** |
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338 ;;; End: *** |
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339 */ |
