Mercurial > octave
annotate libinterp/corefcn/sparse.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 | c20a0fa91c0c |
children | b7747a2c88b2 |
rev | line source |
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5164 | 1 /* |
2 | |
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3 Copyright (C) 2004-2017 David Bateman |
11523 | 4 Copyright (C) 1998-2004 Andy Adler |
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5 Copyright (C) 2010 VZLU Prague |
7016 | 6 |
7 This file is part of Octave. | |
5164 | 8 |
9 Octave is free software; you can redistribute it and/or modify it | |
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10 under the terms of the GNU General Public License as published by |
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11 the Free Software Foundation; either version 3 of the License, or |
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12 (at your option) any later version. |
5164 | 13 |
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14 Octave is distributed in the hope that it will be useful, but |
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15 WITHOUT ANY WARRANTY; without even the implied warranty of |
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16 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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17 GNU General Public License for more details. |
5164 | 18 |
19 You should have received a copy of the GNU General Public License | |
7016 | 20 along with Octave; see the file COPYING. If not, see |
21 <http://www.gnu.org/licenses/>. | |
5164 | 22 |
23 */ | |
24 | |
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25 #if defined (HAVE_CONFIG_H) |
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26 # include "config.h" |
5164 | 27 #endif |
28 | |
29 #include <cstdlib> | |
30 #include <string> | |
31 | |
32 #include "variables.h" | |
33 #include "utils.h" | |
34 #include "pager.h" | |
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35 #include "defun.h" |
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36 #include "errwarn.h" |
5164 | 37 #include "quit.h" |
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38 #include "unwind-prot.h" |
5164 | 39 |
40 #include "ov-re-sparse.h" | |
41 #include "ov-cx-sparse.h" | |
42 #include "ov-bool-sparse.h" | |
43 | |
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44 DEFUN (issparse, args, , |
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45 doc: /* -*- texinfo -*- |
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46 @deftypefn {} {} issparse (@var{x}) |
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47 Return true if @var{x} is a sparse matrix. |
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48 @seealso{ismatrix} |
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49 @end deftypefn */) |
5164 | 50 { |
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51 if (args.length () != 1) |
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52 print_usage (); |
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53 |
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54 return ovl (args(0).is_sparse_type ()); |
5164 | 55 } |
56 | |
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57 DEFUN (sparse, args, , |
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58 doc: /* -*- texinfo -*- |
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59 @deftypefn {} {@var{s} =} sparse (@var{a}) |
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60 @deftypefnx {} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv}, @var{m}, @var{n}) |
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61 @deftypefnx {} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv}) |
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62 @deftypefnx {} {@var{s} =} sparse (@var{m}, @var{n}) |
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63 @deftypefnx {} {@var{s} =} sparse (@var{i}, @var{j}, @var{s}, @var{m}, @var{n}, "unique") |
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64 @deftypefnx {} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv}, @var{m}, @var{n}, @var{nzmax}) |
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65 Create a sparse matrix from a full matrix, or row, column, value triplets. |
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66 |
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67 If @var{a} is a full matrix, convert it to a sparse matrix representation, |
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68 removing all zero values in the process. |
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69 |
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70 Given the integer index vectors @var{i} and @var{j}, and a 1-by-@code{nnz} |
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71 vector of real or complex values @var{sv}, construct the sparse matrix |
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72 @code{S(@var{i}(@var{k}),@var{j}(@var{k})) = @var{sv}(@var{k})} with overall |
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73 dimensions @var{m} and @var{n}. If any of @var{sv}, @var{i} or @var{j} are |
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74 scalars, they are expanded to have a common size. |
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75 |
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76 If @var{m} or @var{n} are not specified their values are derived from the |
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77 maximum index in the vectors @var{i} and @var{j} as given by |
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78 @code{@var{m} = max (@var{i})}, @code{@var{n} = max (@var{j})}. |
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79 |
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80 @strong{Note}: if multiple values are specified with the same @var{i}, |
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81 @var{j} indices, the corresponding value in @var{s} will be the sum of the |
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82 values at the repeated location. See @code{accumarray} for an example of |
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83 how to produce different behavior, such as taking the minimum instead. |
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84 |
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85 If the option @qcode{"unique"} is given, and more than one value is |
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86 specified at the same @var{i}, @var{j} indices, then the last specified |
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87 value will be used. |
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88 |
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89 @code{sparse (@var{m}, @var{n})} will create an empty @var{m}x@var{n} sparse |
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90 matrix and is equivalent to @code{sparse ([], [], [], @var{m}, @var{n})} |
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91 |
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92 The argument @code{nzmax} is ignored but accepted for compatibility with |
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93 @sc{matlab}. |
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94 |
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95 Example 1 (sum at repeated indices): |
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96 |
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97 @example |
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98 @group |
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99 @var{i} = [1 1 2]; @var{j} = [1 1 2]; @var{sv} = [3 4 5]; |
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100 sparse (@var{i}, @var{j}, @var{sv}, 3, 4) |
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101 @result{} |
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102 Compressed Column Sparse (rows = 3, cols = 4, nnz = 2 [17%]) |
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103 |
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104 (1, 1) -> 7 |
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105 (2, 2) -> 5 |
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106 @end group |
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107 @end example |
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108 |
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109 Example 2 ("unique" option): |
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110 |
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111 @example |
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112 @group |
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113 @var{i} = [1 1 2]; @var{j} = [1 1 2]; @var{sv} = [3 4 5]; |
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114 sparse (@var{i}, @var{j}, @var{sv}, 3, 4, "unique") |
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115 @result{} |
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116 Compressed Column Sparse (rows = 3, cols = 4, nnz = 2 [17%]) |
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117 |
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118 (1, 1) -> 4 |
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119 (2, 2) -> 5 |
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120 @end group |
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121 @end example |
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122 @seealso{full, accumarray, spalloc, spdiags, speye, spones, sprand, sprandn, sprandsym, spconvert, spfun} |
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123 @end deftypefn */) |
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125 int nargin = args.length (); |
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127 if (nargin == 0 || nargin > 6) |
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128 print_usage (); |
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129 |
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130 octave_value retval; |
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131 |
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132 // Temporarily disable sparse_auto_mutate if set (it's obsolete anyway). |
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133 octave::unwind_protect frame; |
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134 frame.protect_var (Vsparse_auto_mutate); |
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135 Vsparse_auto_mutate = false; |
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137 if (nargin == 1) |
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138 { |
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139 octave_value arg = args(0); |
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140 if (arg.islogical ()) |
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141 retval = arg.sparse_bool_matrix_value (); |
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142 else if (arg.iscomplex ()) |
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143 retval = arg.sparse_complex_matrix_value (); |
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144 else if (arg.is_numeric_type ()) |
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145 retval = arg.sparse_matrix_value (); |
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146 else |
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147 err_wrong_type_arg ("sparse", arg); |
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148 } |
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149 else if (nargin == 2) |
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150 { |
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151 octave_idx_type m = 0; |
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152 octave_idx_type n = 0; |
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153 |
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154 get_dimensions (args(0), args(1), "sparse", m, n); |
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155 |
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156 if (m >= 0 && n >= 0) |
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157 retval = SparseMatrix (m, n); |
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158 else |
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159 error ("sparse: dimensions must be non-negative"); |
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160 } |
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161 else if (nargin >= 3) |
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162 { |
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163 bool summation = true; |
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164 if (nargin > 3 && args(nargin-1).is_string ()) |
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165 { |
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166 std::string opt = args(nargin-1).string_value (); |
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167 if (opt == "unique") |
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168 summation = false; |
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169 else if (opt == "sum" || opt == "summation") |
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170 summation = true; |
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171 else |
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172 error ("sparse: invalid option: %s", opt.c_str ()); |
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174 nargin -= 1; |
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175 } |
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177 octave_idx_type m, n, nzmax; |
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178 m = n = nzmax = -1; |
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179 if (nargin == 6) |
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180 { |
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181 nzmax = args(5).idx_type_value (); |
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182 nargin--; |
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183 } |
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184 |
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185 if (nargin == 5) |
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186 { |
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187 get_dimensions (args(3), args(4), "sparse", m, n); |
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189 if (m < 0 || n < 0) |
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190 error ("sparse: dimensions must be non-negative"); |
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191 } |
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192 |
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193 int k = 0; // index we're checking when index_vector throws |
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194 try |
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195 { |
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196 idx_vector i = args(0).index_vector (); |
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197 k = 1; |
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198 idx_vector j = args(1).index_vector (); |
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200 if (args(2).islogical ()) |
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201 retval = SparseBoolMatrix (args(2).bool_array_value (), i,j, |
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202 m, n, summation, nzmax); |
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203 else if (args(2).iscomplex ()) |
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204 retval = SparseComplexMatrix (args(2).complex_array_value(), |
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205 i, j, m, n, summation, nzmax); |
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206 else if (args(2).is_numeric_type ()) |
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207 retval = SparseMatrix (args(2).array_value (), i, j, |
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208 m, n, summation, nzmax); |
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209 else |
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210 err_wrong_type_arg ("sparse", args(2)); |
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211 } |
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212 catch (octave::index_exception& e) |
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213 { |
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214 // Rethrow to allow more info to be reported later. |
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215 e.set_pos_if_unset (2, k+1); |
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216 throw; |
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217 } |
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218 } |
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220 return retval; |
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222 |
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223 DEFUN (spalloc, args, , |
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224 doc: /* -*- texinfo -*- |
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225 @deftypefn {} {@var{s} =} spalloc (@var{m}, @var{n}, @var{nz}) |
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226 Create an @var{m}-by-@var{n} sparse matrix with pre-allocated space for at |
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227 most @var{nz} nonzero elements. |
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228 |
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229 This is useful for building a matrix incrementally by a sequence of indexed |
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230 assignments. Subsequent indexed assignments after @code{spalloc} will reuse |
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231 the pre-allocated memory, provided they are of one of the simple forms |
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232 |
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233 @itemize |
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234 @item @code{@var{s}(I:J) = @var{x}} |
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235 |
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236 @item @code{@var{s}(:,I:J) = @var{x}} |
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237 |
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238 @item @code{@var{s}(K:L,I:J) = @var{x}} |
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239 @end itemize |
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240 |
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241 @b{and} that the following conditions are met: |
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242 |
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243 @itemize |
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244 @item the assignment does not decrease nnz (@var{S}). |
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245 |
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246 @item after the assignment, nnz (@var{S}) does not exceed @var{nz}. |
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247 |
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248 @item no index is out of bounds. |
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249 @end itemize |
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250 |
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251 Partial movement of data may still occur, but in general the assignment will |
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252 be more memory and time efficient under these circumstances. In particular, |
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253 it is possible to efficiently build a pre-allocated sparse matrix from a |
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254 contiguous block of columns. |
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255 |
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256 The amount of pre-allocated memory for a given matrix may be queried using |
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257 the function @code{nzmax}. |
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258 @seealso{nzmax, sparse} |
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259 @end deftypefn */) |
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260 { |
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261 int nargin = args.length (); |
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262 |
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263 if (nargin < 2 || nargin > 3) |
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264 print_usage (); |
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265 |
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266 octave_idx_type m = args(0).idx_type_value (); |
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267 octave_idx_type n = args(1).idx_type_value (); |
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268 |
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269 octave_idx_type nz = 0; |
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270 if (nargin == 3) |
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271 nz = args(2).idx_type_value (); |
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272 |
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273 if (m >= 0 && n >= 0 && nz >= 0) |
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274 return ovl (SparseMatrix (dim_vector (m, n), nz)); |
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275 else |
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276 error ("spalloc: M,N,NZ must be non-negative"); |
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277 } |