Mercurial > hg > octave-nkf
annotate libinterp/corefcn/sparse.cc @ 18099:6a71e5030df5
Follow coding convention of defining and initializing only 1 variable per line in liboctinterp.
* libinterp/corefcn/balance.cc, libinterp/corefcn/bsxfun.cc,
libinterp/corefcn/cellfun.cc, libinterp/corefcn/data.cc,
libinterp/corefcn/dlmread.cc, libinterp/corefcn/dot.cc,
libinterp/corefcn/eig.cc, libinterp/corefcn/find.cc, libinterp/corefcn/gcd.cc,
libinterp/corefcn/gl-render.cc, libinterp/corefcn/gl2ps-renderer.cc,
libinterp/corefcn/graphics.cc, libinterp/corefcn/kron.cc,
libinterp/corefcn/load-save.cc, libinterp/corefcn/lookup.cc,
libinterp/corefcn/ls-hdf5.cc, libinterp/corefcn/ls-mat5.cc,
libinterp/corefcn/lu.cc, libinterp/corefcn/max.cc,
libinterp/corefcn/oct-map.cc, libinterp/corefcn/oct-obj.cc,
libinterp/corefcn/oct-stream.cc, libinterp/corefcn/sparse.cc,
libinterp/corefcn/sqrtm.cc, libinterp/corefcn/str2double.cc,
libinterp/corefcn/strfind.cc, libinterp/corefcn/strfns.cc,
libinterp/corefcn/tril.cc, libinterp/corefcn/txt-eng-ft.cc,
libinterp/corefcn/variables.cc, libinterp/corefcn/xdiv.cc,
libinterp/dldfcn/__delaunayn__.cc, libinterp/dldfcn/qr.cc,
libinterp/dldfcn/symrcm.cc, libinterp/dldfcn/tsearch.cc,
libinterp/octave-value/ov-base-diag.cc, libinterp/octave-value/ov-base-int.cc,
libinterp/octave-value/ov-base-mat.cc, libinterp/octave-value/ov-bool-mat.cc,
libinterp/octave-value/ov-bool-sparse.cc, libinterp/octave-value/ov-bool.cc,
libinterp/octave-value/ov-cell.cc, libinterp/octave-value/ov-class.cc,
libinterp/octave-value/ov-complex.cc, libinterp/octave-value/ov-cx-diag.cc,
libinterp/octave-value/ov-cx-mat.cc, libinterp/octave-value/ov-cx-sparse.cc,
libinterp/octave-value/ov-fcn-handle.cc,
libinterp/octave-value/ov-fcn-inline.cc, libinterp/octave-value/ov-float.cc,
libinterp/octave-value/ov-flt-complex.cc,
libinterp/octave-value/ov-flt-cx-diag.cc,
libinterp/octave-value/ov-flt-cx-mat.cc,
libinterp/octave-value/ov-flt-re-diag.cc,
libinterp/octave-value/ov-flt-re-mat.cc, libinterp/octave-value/ov-java.cc,
libinterp/octave-value/ov-range.cc, libinterp/octave-value/ov-re-diag.cc,
libinterp/octave-value/ov-re-mat.cc, libinterp/octave-value/ov-re-sparse.cc,
libinterp/octave-value/ov-scalar.cc, libinterp/octave-value/ov-str-mat.cc,
libinterp/octave-value/ov-usr-fcn.cc, libinterp/parse-tree/pt-cbinop.cc,
libinterp/parse-tree/pt-eval.cc, libinterp/parse-tree/pt-mat.cc:
Follow coding convention of defining and initializing only 1 variable per line
in liboctinterp.
author | Rik <rik@octave.org> |
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date | Thu, 05 Dec 2013 10:50:17 -0800 |
parents | 175b392e91fe |
children | b560bac0fca2 |
rev | line source |
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5164 | 1 /* |
2 | |
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3 Copyright (C) 2004-2013 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 | |
10 under the terms of the GNU General Public License as published by the | |
7016 | 11 Free Software Foundation; either version 3 of the License, or (at your |
12 option) any later version. | |
5164 | 13 |
14 Octave is distributed in the hope that it will be useful, but WITHOUT | |
15 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
16 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
17 for more details. | |
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 | |
25 #ifdef HAVE_CONFIG_H | |
26 #include <config.h> | |
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" |
5164 | 36 #include "gripes.h" |
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 "-*- texinfo -*-\n\ |
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46 @deftypefn {Built-in Function} {} issparse (@var{x})\n\ |
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47 Return true if @var{x} is a sparse matrix.\n\ |
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48 @seealso{ismatrix}\n\ |
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49 @end deftypefn") |
5164 | 50 { |
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51 if (args.length () != 1) |
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52 { |
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53 print_usage (); |
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54 return octave_value (); |
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55 } |
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56 else |
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57 return octave_value (args(0).is_sparse_type ()); |
5164 | 58 } |
59 | |
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60 DEFUN (sparse, args, , |
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61 "-*- texinfo -*-\n\ |
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62 @deftypefn {Built-in Function} {@var{s} =} sparse (@var{a})\n\ |
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63 @deftypefnx {Built-in Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv}, @var{m}, @var{n}, @var{nzmax})\n\ |
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64 @deftypefnx {Built-in Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv})\n\ |
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65 @deftypefnx {Built-in Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{s}, @var{m}, @var{n}, \"unique\")\n\ |
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66 @deftypefnx {Built-in Function} {@var{s} =} sparse (@var{m}, @var{n})\n\ |
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67 Create a sparse matrix from the full matrix or row, column, value triplets.\n\ |
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68 If @var{a} is a full matrix, convert it to a sparse matrix representation,\n\ |
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69 removing all zero values in the process.\n\ |
5164 | 70 \n\ |
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71 Given the integer index vectors @var{i} and @var{j}, a 1-by-@code{nnz} vector\n\ |
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72 of real of complex values @var{sv}, overall dimensions @var{m} and @var{n}\n\ |
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73 of the sparse matrix. The argument @code{nzmax} is ignored but accepted for\n\ |
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74 compatibility with @sc{matlab}. If @var{m} or @var{n} are not specified\n\ |
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75 their values are derived from the maximum index in the vectors @var{i} and\n\ |
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76 @var{j} as given by @code{@var{m} = max (@var{i})},\n\ |
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77 @code{@var{n} = max (@var{j})}.\n\ |
5164 | 78 \n\ |
6556 | 79 @strong{Note}: if multiple values are specified with the same\n\ |
80 @var{i}, @var{j} indices, the corresponding values in @var{s} will\n\ | |
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81 be added. See @code{accumarray} for an example of how to produce different\n\ |
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82 behavior, such as taking the minimum instead.\n\ |
6556 | 83 \n\ |
6557 | 84 The following are all equivalent:\n\ |
5164 | 85 \n\ |
6556 | 86 @example\n\ |
87 @group\n\ | |
88 s = sparse (i, j, s, m, n)\n\ | |
89 s = sparse (i, j, s, m, n, \"summation\")\n\ | |
90 s = sparse (i, j, s, m, n, \"sum\")\n\ | |
91 @end group\n\ | |
92 @end example\n\ | |
5164 | 93 \n\ |
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94 Given the option @qcode{\"unique\"}, if more than two values are specified\n\ |
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95 for the same @var{i}, @var{j} indices, the last specified value will be\n\ |
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96 used.\n\ |
5164 | 97 \n\ |
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98 @code{sparse (@var{m}, @var{n})} is equivalent to\n\ |
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99 @code{sparse ([], [], [], @var{m}, @var{n}, 0)}\n\ |
6556 | 100 \n\ |
101 If any of @var{sv}, @var{i} or @var{j} are scalars, they are expanded\n\ | |
102 to have a common size.\n\ | |
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103 @seealso{full, accumarray}\n\ |
5164 | 104 @end deftypefn") |
105 { | |
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106 octave_value retval; |
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107 int nargin = args.length (); |
5164 | 108 |
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109 // Temporarily disable sparse_auto_mutate if set (it's obsolete anyway). |
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110 unwind_protect frame; |
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111 frame.protect_var (Vsparse_auto_mutate); |
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112 Vsparse_auto_mutate = false; |
5164 | 113 |
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114 if (nargin == 1) |
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115 { |
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116 octave_value arg = args (0); |
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117 if (arg.is_bool_type ()) |
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118 retval = arg.sparse_bool_matrix_value (); |
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119 else if (arg.is_complex_type ()) |
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120 retval = arg.sparse_complex_matrix_value (); |
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121 else if (arg.is_numeric_type ()) |
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122 retval = arg.sparse_matrix_value (); |
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123 else |
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124 gripe_wrong_type_arg ("sparse", arg); |
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125 } |
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126 else if (nargin == 2) |
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127 { |
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128 octave_idx_type m = 0; |
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129 octave_idx_type n = 0; |
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130 if (args(0).is_scalar_type () && args(1).is_scalar_type ()) |
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131 { |
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132 m = args(0).idx_type_value (); |
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133 n = args(1).idx_type_value (); |
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134 } |
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135 else |
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136 error ("sparse: dimensions M,N must be scalar"); |
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137 |
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138 if (! error_state) |
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139 { |
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140 if (m >= 0 && n >= 0) |
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141 retval = SparseMatrix (m, n); |
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142 else |
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143 error ("sparse: dimensions M,N must be positive or zero"); |
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144 } |
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145 } |
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146 else if (nargin >= 3) |
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147 { |
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148 bool summation = true; |
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149 if (nargin > 3 && args(nargin-1).is_string ()) |
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150 { |
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151 std::string opt = args(nargin-1).string_value (); |
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152 if (opt == "unique") |
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153 summation = false; |
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154 else if (opt == "sum" || opt == "summation") |
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155 summation = true; |
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156 else |
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157 error ("sparse: invalid option: %s", opt.c_str ()); |
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159 nargin -= 1; |
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160 } |
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162 if (! error_state) |
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163 { |
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164 octave_idx_type m, n, nzmax; |
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165 m = n = nzmax = -1; |
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166 if (nargin == 6) |
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167 { |
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168 nzmax = args(5).idx_type_value (); |
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169 nargin --; |
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170 } |
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171 |
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172 if (nargin == 5) |
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173 { |
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174 if (args(3).is_scalar_type () && args(4).is_scalar_type ()) |
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175 { |
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176 m = args(3).idx_type_value (); |
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177 n = args(4).idx_type_value (); |
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178 } |
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179 else |
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180 error ("sparse: expecting scalar dimensions"); |
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182 | |
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183 if (! error_state && (m < 0 || n < 0)) |
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184 error ("sparse: dimensions must be non-negative"); |
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185 } |
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186 else if (nargin != 3) |
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187 print_usage (); |
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188 |
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189 if (! error_state) |
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190 { |
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191 idx_vector i = args(0).index_vector (); |
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192 idx_vector j = args(1).index_vector (); |
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194 if (args(2).is_bool_type ()) |
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195 retval = SparseBoolMatrix (args(2).bool_array_value (), i, j, |
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196 m, n, summation, nzmax); |
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197 else if (args(2).is_complex_type ()) |
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198 retval = SparseComplexMatrix (args(2).complex_array_value (), |
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199 i, j, m, n, summation, nzmax); |
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200 else if (args(2).is_numeric_type ()) |
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201 retval = SparseMatrix (args(2).array_value (), i, j, |
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202 m, n, summation, nzmax); |
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203 else |
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204 gripe_wrong_type_arg ("sparse", args(2)); |
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205 } |
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207 } |
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208 } |
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210 return retval; |
5164 | 211 } |
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212 |
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213 DEFUN (spalloc, args, , |
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214 "-*- texinfo -*-\n\ |
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215 @deftypefn {Built-in Function} {@var{s} =} spalloc (@var{m}, @var{n}, @var{nz})\n\ |
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216 Create an @var{m}-by-@var{n} sparse matrix with pre-allocated space for at\n\ |
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217 most @var{nz} nonzero elements. This is useful for building the matrix\n\ |
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218 incrementally by a sequence of indexed assignments. Subsequent indexed\n\ |
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219 assignments will reuse the pre-allocated memory, provided they are of one of\n\ |
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220 the simple forms\n\ |
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221 \n\ |
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222 @itemize\n\ |
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223 @item @code{@var{s}(I:J) = @var{x}}\n\ |
10840 | 224 \n\ |
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225 @item @code{@var{s}(:,I:J) = @var{x}}\n\ |
10840 | 226 \n\ |
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227 @item @code{@var{s}(K:L,I:J) = @var{x}}\n\ |
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228 @end itemize\n\ |
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229 \n\ |
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230 @b{and} that the following conditions are met:\n\ |
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231 \n\ |
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232 @itemize\n\ |
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233 @item the assignment does not decrease nnz (@var{S}).\n\ |
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235 @item after the assignment, nnz (@var{S}) does not exceed @var{nz}.\n\ |
10840 | 236 \n\ |
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237 @item no index is out of bounds.\n\ |
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238 @end itemize\n\ |
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239 \n\ |
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240 Partial movement of data may still occur, but in general the assignment will\n\ |
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241 be more memory and time-efficient under these circumstances. In particular,\n\ |
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242 it is possible to efficiently build a pre-allocated sparse matrix from\n\ |
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243 contiguous block of columns.\n\ |
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244 \n\ |
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245 The amount of pre-allocated memory for a given matrix may be queried using\n\ |
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246 the function @code{nzmax}.\n\ |
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247 @seealso{nzmax, sparse}\n\ |
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248 @end deftypefn") |
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249 { |
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250 octave_value retval; |
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251 int nargin = args.length (); |
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252 |
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253 if (nargin == 2 || nargin == 3) |
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254 { |
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255 octave_idx_type m = args(0).idx_type_value (); |
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256 octave_idx_type n = args(1).idx_type_value (); |
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257 octave_idx_type nz = 0; |
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258 if (nargin == 3) |
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259 nz = args(2).idx_type_value (); |
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260 if (error_state) |
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261 ; |
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262 else if (m >= 0 && n >= 0 && nz >= 0) |
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263 retval = SparseMatrix (dim_vector (m, n), nz); |
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264 else |
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265 error ("spalloc: M,N,NZ must be non-negative"); |
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266 } |
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267 else |
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268 print_usage (); |
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269 |
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270 return retval; |
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271 } |