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optimize sparse matrix assembly
author Jaroslav Hajek <highegg@gmail.com>
date Wed, 31 Mar 2010 10:03:55 +0200
parents d0ce5e973937
children c5005bc2b7a9
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1 /*
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2
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3 Copyright (C) 2004, 2005, 2006, 2007, 2008, 2009 David Bateman
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4 Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004 Andy Adler
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5
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6 This file is part of Octave.
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7
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8 Octave is free software; you can redistribute it and/or modify it
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9 under the terms of the GNU General Public License as published by the
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10 Free Software Foundation; either version 3 of the License, or (at your
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11 option) any later version.
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12
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13 Octave is distributed in the hope that it will be useful, but WITHOUT
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14 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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15 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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16 for more details.
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17
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18 You should have received a copy of the GNU General Public License
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19 along with Octave; see the file COPYING. If not, see
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20 <http://www.gnu.org/licenses/>.
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21
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22 */
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23
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24 #ifdef HAVE_CONFIG_H
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25 #include <config.h>
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26 #endif
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27
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28 #include <cstdlib>
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29 #include <string>
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30
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31 #include "variables.h"
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32 #include "utils.h"
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33 #include "pager.h"
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34 #include "defun-dld.h"
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35 #include "gripes.h"
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36 #include "quit.h"
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37 #include "unwind-prot.h"
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38
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39 #include "ov-re-sparse.h"
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40 #include "ov-cx-sparse.h"
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41 #include "ov-bool-sparse.h"
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42
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43 DEFUN_DLD (issparse, args, ,
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44 "-*- texinfo -*-\n\
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45 @deftypefn {Loadable Function} {} issparse (@var{expr})\n\
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46 Return 1 if the value of the expression @var{expr} is a sparse matrix.\n\
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47 @end deftypefn")
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48 {
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49 if (args.length() != 1)
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50 {
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51 print_usage ();
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52 return octave_value ();
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53 }
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54 else
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55 return octave_value (args(0).is_sparse_type ());
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56 }
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57
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58 DEFUN_DLD (sparse, args, ,
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59 "-*- texinfo -*-\n\
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60 @deftypefn {Loadable Function} {@var{s} =} sparse (@var{a})\n\
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61 @deftypefnx {Loadable Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv}, @var{m}, @var{n}, @var{nzmax})\n\
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62 @deftypefnx {Loadable Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv})\n\
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63 @deftypefnx {Loadable Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{s}, @var{m}, @var{n}, \"unique\")\n\
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64 @deftypefnx {Loadable Function} {@var{s} =} sparse (@var{m}, @var{n})\n\
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65 Create a sparse matrix from the full matrix or row, column, value triplets.\n\
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66 If @var{a} is a full matrix, convert it to a sparse matrix representation,\n\
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67 removing all zero values in the process.\n\
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68 \n\
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69 Given the integer index vectors @var{i} and @var{j}, a 1-by-@code{nnz} vector\n\
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70 of real of complex values @var{sv}, overall dimensions @var{m} and @var{n}\n\
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71 of the sparse matrix. The argument @code{nzmax} is ignored but accepted for\n\
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72 compatibility with @sc{matlab}. If @var{m} or @var{n} are not specified their\n\
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73 values are derived from the maximum index in the vectors @var{i} and @var{j}\n\
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74 as given by @code{@var{m} = max (@var{i})}, @code{@var{n} = max (@var{j})}.\n\
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75 \n\
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76 @strong{Note}: if multiple values are specified with the same\n\
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77 @var{i}, @var{j} indices, the corresponding values in @var{s} will\n\
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78 be added.\n\
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79 \n\
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80 The following are all equivalent:\n\
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81 \n\
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82 @example\n\
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83 @group\n\
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84 s = sparse (i, j, s, m, n)\n\
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85 s = sparse (i, j, s, m, n, \"summation\")\n\
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86 s = sparse (i, j, s, m, n, \"sum\")\n\
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87 @end group\n\
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88 @end example\n\
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89 \n\
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90 Given the option \"unique\". if more than two values are specified for the\n\
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91 same @var{i}, @var{j} indices, the last specified value will be used.\n\
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92 \n\
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93 @code{sparse(@var{m}, @var{n})} is equivalent to\n\
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94 @code{sparse ([], [], [], @var{m}, @var{n}, 0)}\n\
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95 \n\
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96 If any of @var{sv}, @var{i} or @var{j} are scalars, they are expanded\n\
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97 to have a common size.\n\
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98 @seealso{full}\n\
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99 @end deftypefn")
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100 {
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101 octave_value retval;
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102 int nargin = args.length ();
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103
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104 // Temporarily disable sparse_auto_mutate if set (it's obsolete anyway).
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105 unwind_protect frame;
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106 frame.protect_var (Vsparse_auto_mutate);
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107 Vsparse_auto_mutate = false;
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108
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109 if (nargin == 1)
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110 {
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111 octave_value arg = args (0);
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112 if (arg.is_bool_type ())
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113 retval = arg.sparse_bool_matrix_value ();
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114 else if (arg.is_complex_type ())
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115 retval = arg.sparse_complex_matrix_value ();
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116 else if (arg.is_numeric_type ())
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117 retval = arg.sparse_matrix_value ();
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118 else
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119 gripe_wrong_type_arg ("sparse", arg);
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120 }
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121 else if (nargin == 2)
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122 {
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123 octave_idx_type m = 0, n = 0;
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124 if (args(0).is_scalar_type () && args(1).is_scalar_type ())
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125 {
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126 m = args(0).idx_type_value ();
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127 n = args(1).idx_type_value ();
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128 }
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129 else
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130 error ("sparse: expecting scalar dimensions");
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131
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132 if (! error_state)
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133 {
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134 if (m >= 0 && n >= 0)
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135 retval = SparseMatrix (m, n);
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136 else
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137 error ("sparse: dimensions must be nonnegative");
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138 }
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139 }
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140 else if (nargin >= 3)
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141 {
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142 bool summation = true;
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143 if (nargin > 3 && args(nargin-1).is_string ())
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144 {
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145 std::string opt = args(nargin-1).string_value ();
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146 if (opt == "unique")
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147 summation = false;
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148 else if (opt == "sum" || opt == "summation")
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149 summation = true;
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150 else
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151 error ("sparse: invalid option: %s", opt.c_str ());
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152
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153 nargin -= 1;
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154 }
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155
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156 if (! error_state)
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157 {
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158 octave_idx_type m = -1, n = -1;
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159 if (nargin == 5)
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160 {
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161 if (args(3).is_scalar_type () && args(4).is_scalar_type ())
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162 {
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163 m = args(3).idx_type_value ();
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164 n = args(4).idx_type_value ();
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165 }
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166 else
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167 error ("sparse: expecting scalar dimensions");
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168
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169
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170 if (! error_state && (m < 0 || n < 0))
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171 error ("sparse: dimensions must be nonnegative");
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172 }
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173 else if (nargin != 3)
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174 print_usage ();
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175
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176 if (! error_state)
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177 {
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178 idx_vector i = args(0).index_vector ();
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179 idx_vector j = args(1).index_vector ();
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180
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181 if (args(2).is_bool_type ())
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182 retval = SparseBoolMatrix (args(2).bool_array_value (), i, j,
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183 m, n, summation);
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184 else if (args(2).is_complex_type ())
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185 retval = SparseComplexMatrix (args(2).complex_array_value (), i, j,
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186 m, n, summation);
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187 else if (args(2).is_numeric_type ())
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188 retval = SparseMatrix (args(2).array_value (), i, j,
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189 m, n, summation);
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190 else
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191 gripe_wrong_type_arg ("sparse", args(2));
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192 }
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193
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194 }
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195 }
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196
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197 return retval;
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198 }