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1 /* |
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2 |
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2847
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3 Copyright (C) 1996, 1997 John W. Eaton |
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4 |
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5 This file is part of Octave. |
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6 |
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7 Octave is free software; you can redistribute it and/or modify it |
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8 under the terms of the GNU General Public License as published by the |
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9 Free Software Foundation; either version 3 of the License, or (at your |
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10 option) any later version. |
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11 |
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12 Octave is distributed in the hope that it will be useful, but WITHOUT |
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13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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15 for more details. |
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16 |
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17 You should have received a copy of the GNU General Public License |
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18 along with Octave; see the file COPYING. If not, see |
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19 <http://www.gnu.org/licenses/>. |
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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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4100
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27 #include <climits> |
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28 |
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3503
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29 #include <iostream> |
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4726
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30 #include <vector> |
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31 |
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4944
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32 #include "data-conv.h" |
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33 #include "lo-ieee.h" |
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34 #include "lo-utils.h" |
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4944
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35 #include "mach-info.h" |
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36 #include "mx-base.h" |
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4153
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37 #include "quit.h" |
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38 |
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4901
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39 #include "defun.h" |
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40 #include "gripes.h" |
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41 #include "oct-obj.h" |
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2979
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42 #include "oct-lvalue.h" |
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4944
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43 #include "oct-stream.h" |
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2410
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44 #include "ops.h" |
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3219
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45 #include "ov-base.h" |
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46 #include "ov-base-mat.h" |
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47 #include "ov-base-mat.cc" |
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2410
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48 #include "ov-scalar.h" |
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49 #include "ov-re-mat.h" |
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50 #include "ov-re-sparse.h" |
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4901
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51 #include "ov-type-conv.h" |
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52 #include "pr-output.h" |
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2948
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53 #include "variables.h" |
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54 |
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55 #include "byte-swap.h" |
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56 #include "ls-oct-ascii.h" |
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57 #include "ls-utils.h" |
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4805
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58 #include "ls-hdf5.h" |
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59 |
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4100
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60 #if ! defined (UCHAR_MAX) |
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61 #define UCHAR_MAX 255 |
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62 #endif |
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63 |
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64 template class octave_base_matrix<NDArray>; |
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65 |
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66 DEFINE_OCTAVE_ALLOCATOR (octave_matrix); |
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67 |
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68 DEFINE_OV_TYPEID_FUNCTIONS_AND_DATA (octave_matrix, "matrix", "double"); |
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69 |
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70 octave_base_value * |
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71 octave_matrix::try_narrowing_conversion (void) |
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72 { |
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73 octave_base_value *retval = 0; |
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74 |
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75 if (matrix.nelem () == 1) |
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76 retval = new octave_scalar (matrix (0)); |
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77 |
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78 return retval; |
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79 } |
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80 |
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81 bool |
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82 octave_matrix::valid_as_scalar_index (void) const |
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83 { |
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84 // FIXME |
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85 return false; |
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86 } |
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87 |
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88 double |
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89 octave_matrix::double_value (bool) const |
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90 { |
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91 double retval = lo_ieee_nan_value (); |
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92 |
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93 if (numel () > 0) |
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94 { |
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95 gripe_implicit_conversion ("Octave:array-as-scalar", |
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96 "real matrix", "real scalar"); |
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97 |
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98 retval = matrix (0, 0); |
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99 } |
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100 else |
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101 gripe_invalid_conversion ("real matrix", "real scalar"); |
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102 |
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103 return retval; |
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104 } |
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105 |
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106 // FIXME |
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107 |
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108 Matrix |
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109 octave_matrix::matrix_value (bool) const |
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110 { |
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111 return matrix.matrix_value (); |
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112 } |
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113 |
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114 Complex |
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115 octave_matrix::complex_value (bool) const |
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116 { |
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117 double tmp = lo_ieee_nan_value (); |
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118 |
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119 Complex retval (tmp, tmp); |
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120 |
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121 if (rows () > 0 && columns () > 0) |
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122 { |
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123 gripe_implicit_conversion ("Octave:array-as-scalar", |
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124 "real matrix", "complex scalar"); |
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125 |
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126 retval = matrix (0, 0); |
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127 } |
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128 else |
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129 gripe_invalid_conversion ("real matrix", "complex scalar"); |
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130 |
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131 return retval; |
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132 } |
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133 |
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134 // FIXME |
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135 |
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136 ComplexMatrix |
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137 octave_matrix::complex_matrix_value (bool) const |
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138 { |
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139 return ComplexMatrix (matrix.matrix_value ()); |
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140 } |
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141 |
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142 ComplexNDArray |
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143 octave_matrix::complex_array_value (bool) const |
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144 { |
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145 return ComplexNDArray (matrix); |
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146 } |
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147 |
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148 boolNDArray |
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149 octave_matrix::bool_array_value (bool warn) const |
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5898
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150 { |
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151 if (warn && matrix.any_element_not_one_or_zero ()) |
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152 gripe_logical_conversion (); |
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153 |
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154 return boolNDArray (matrix); |
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155 } |
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156 |
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157 charNDArray |
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158 octave_matrix::char_array_value (bool) const |
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159 { |
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160 charNDArray retval (dims ()); |
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161 |
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162 octave_idx_type nel = numel (); |
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163 |
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164 for (octave_idx_type i = 0; i < nel; i++) |
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165 retval.elem (i) = static_cast<char>(matrix.elem (i)); |
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166 |
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167 return retval; |
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168 } |
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169 |
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170 SparseMatrix |
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171 octave_matrix::sparse_matrix_value (bool) const |
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172 { |
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173 return SparseMatrix (matrix.matrix_value ()); |
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174 } |
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175 |
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176 SparseComplexMatrix |
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177 octave_matrix::sparse_complex_matrix_value (bool) const |
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178 { |
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179 // FIXME Need a SparseComplexMatrix (Matrix) constructor to make |
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180 // this function more efficient. Then this should become |
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181 // return SparseComplexMatrix (matrix.matrix_value ()); |
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182 return SparseComplexMatrix (sparse_matrix_value ()); |
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183 } |
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184 |
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185 streamoff_array |
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186 octave_matrix::streamoff_array_value (void) const |
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187 { |
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188 streamoff_array retval (dims ()); |
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189 |
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190 octave_idx_type nel = numel (); |
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191 |
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192 for (octave_idx_type i = 0; i < nel; i++) |
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193 { |
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194 double d = matrix(i); |
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195 |
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196 if (D_NINT (d) == d) |
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197 retval(i) = std::streamoff (static_cast<long> (d)); |
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198 else |
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199 { |
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200 error ("conversion to streamoff_array value failed"); |
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201 break; |
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202 } |
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203 } |
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204 |
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205 return retval; |
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206 } |
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207 |
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208 octave_value |
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209 octave_matrix::convert_to_str_internal (bool, bool, char type) const |
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210 { |
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211 octave_value retval; |
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212 dim_vector dv = dims (); |
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213 octave_idx_type nel = dv.numel (); |
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214 |
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215 charNDArray chm (dv); |
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216 |
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217 bool warned = false; |
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218 |
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219 for (octave_idx_type i = 0; i < nel; i++) |
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220 { |
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221 OCTAVE_QUIT; |
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222 |
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223 double d = matrix (i); |
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224 |
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225 if (xisnan (d)) |
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226 { |
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227 ::error ("invalid conversion from NaN to character"); |
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228 return retval; |
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229 } |
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230 else |
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231 { |
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232 int ival = NINT (d); |
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233 |
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234 if (ival < 0 || ival > UCHAR_MAX) |
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235 { |
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236 // FIXME -- is there something |
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237 // better we could do? |
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238 |
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239 ival = 0; |
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240 |
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241 if (! warned) |
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242 { |
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243 ::warning ("range error for conversion to character value"); |
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244 warned = true; |
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245 } |
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246 } |
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247 |
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248 chm (i) = static_cast<char> (ival); |
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249 } |
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250 } |
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251 |
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252 retval = octave_value (chm, true, type); |
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253 |
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254 return retval; |
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255 } |
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256 |
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257 bool |
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6974
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258 octave_matrix::save_ascii (std::ostream& os) |
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259 { |
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260 dim_vector d = dims (); |
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261 |
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262 if (d.length () > 2) |
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263 { |
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264 NDArray tmp = array_value (); |
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265 |
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266 os << "# ndims: " << d.length () << "\n"; |
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267 |
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268 for (int i=0; i < d.length (); i++) |
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269 os << " " << d (i); |
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270 |
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271 os << "\n" << tmp; |
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272 } |
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273 else |
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274 { |
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275 // Keep this case, rather than use generic code above for backward |
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276 // compatiability. Makes load_ascii much more complex!! |
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277 os << "# rows: " << rows () << "\n" |
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278 << "# columns: " << columns () << "\n"; |
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279 |
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280 os << matrix_value (); |
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281 } |
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282 |
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283 return true; |
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284 } |
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285 |
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286 bool |
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287 octave_matrix::load_ascii (std::istream& is) |
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288 { |
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289 bool success = true; |
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5099
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290 |
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291 string_vector keywords(2); |
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292 |
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293 keywords[0] = "ndims"; |
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294 keywords[1] = "rows"; |
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4687
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295 |
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5099
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296 std::string kw; |
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5275
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297 octave_idx_type val = 0; |
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5099
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298 |
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299 if (extract_keyword (is, keywords, kw, val, true)) |
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300 { |
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5099
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301 if (kw == "ndims") |
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4687
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302 { |
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5275
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303 int mdims = static_cast<int> (val); |
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304 |
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5099
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305 if (mdims >= 0) |
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4687
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306 { |
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5099
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307 dim_vector dv; |
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308 dv.resize (mdims); |
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309 |
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5099
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310 for (int i = 0; i < mdims; i++) |
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311 is >> dv(i); |
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312 |
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6717
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313 if (is) |
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314 { |
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315 NDArray tmp(dv); |
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316 |
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317 if (tmp.is_empty ()) |
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318 matrix = tmp; |
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319 else |
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320 { |
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321 is >> tmp; |
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5099
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322 |
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6717
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323 if (is) |
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324 matrix = tmp; |
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325 else |
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326 { |
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327 error ("load: failed to load matrix constant"); |
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328 success = false; |
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329 } |
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330 } |
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331 } |
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332 else |
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4687
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333 { |
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6717
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334 error ("load: failed to read dimensions"); |
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4687
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335 success = false; |
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336 } |
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337 } |
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338 else |
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5099
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339 { |
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6717
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340 error ("load: failed to extract number of dimensions"); |
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5099
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341 success = false; |
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342 } |
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4687
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343 } |
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5099
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344 else if (kw == "rows") |
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4687
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345 { |
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5275
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346 octave_idx_type nr = val; |
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347 octave_idx_type nc = 0; |
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5099
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348 |
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349 if (nr >= 0 && extract_keyword (is, "columns", nc) && nc >= 0) |
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350 { |
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351 if (nr > 0 && nc > 0) |
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352 { |
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353 Matrix tmp (nr, nc); |
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354 is >> tmp; |
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355 if (is) |
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356 matrix = tmp; |
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357 else |
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358 { |
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359 error ("load: failed to load matrix constant"); |
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360 success = false; |
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361 } |
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362 } |
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363 else if (nr == 0 || nc == 0) |
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364 matrix = Matrix (nr, nc); |
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365 else |
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366 panic_impossible (); |
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367 } |
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368 else |
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369 { |
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370 error ("load: failed to extract number of rows and columns"); |
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371 success = false; |
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372 } |
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4687
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373 } |
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5099
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374 else |
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375 panic_impossible (); |
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376 } |
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377 else |
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378 { |
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379 error ("load: failed to extract number of rows and columns"); |
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380 success = false; |
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4687
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381 } |
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382 |
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383 return success; |
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384 } |
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385 |
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386 bool |
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387 octave_matrix::save_binary (std::ostream& os, bool& save_as_floats) |
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388 { |
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389 |
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390 dim_vector d = dims (); |
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391 if (d.length() < 1) |
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392 return false; |
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393 |
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394 // Use negative value for ndims to differentiate with old format!! |
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5828
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395 int32_t tmp = - d.length(); |
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5760
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396 os.write (reinterpret_cast<char *> (&tmp), 4); |
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5275
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397 for (int i = 0; i < d.length (); i++) |
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4687
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398 { |
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399 tmp = d(i); |
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5760
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400 os.write (reinterpret_cast<char *> (&tmp), 4); |
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4687
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401 } |
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402 |
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403 NDArray m = array_value (); |
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404 save_type st = LS_DOUBLE; |
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405 if (save_as_floats) |
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406 { |
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407 if (m.too_large_for_float ()) |
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408 { |
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409 warning ("save: some values too large to save as floats --"); |
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410 warning ("save: saving as doubles instead"); |
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411 } |
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412 else |
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413 st = LS_FLOAT; |
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414 } |
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5775
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415 else if (d.numel () > 8192) // FIXME -- make this configurable. |
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4687
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416 { |
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417 double max_val, min_val; |
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418 if (m.all_integers (max_val, min_val)) |
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419 st = get_save_type (max_val, min_val); |
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420 } |
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421 |
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422 const double *mtmp = m.data (); |
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423 write_doubles (os, mtmp, st, d.numel ()); |
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424 |
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425 return true; |
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426 } |
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427 |
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428 bool |
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429 octave_matrix::load_binary (std::istream& is, bool swap, |
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|
430 oct_mach_info::float_format fmt) |
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431 { |
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432 char tmp; |
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5828
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433 int32_t mdims; |
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5760
|
434 if (! is.read (reinterpret_cast<char *> (&mdims), 4)) |
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4687
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435 return false; |
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436 if (swap) |
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4944
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437 swap_bytes<4> (&mdims); |
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4687
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438 if (mdims < 0) |
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439 { |
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440 mdims = - mdims; |
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5828
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441 int32_t di; |
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4687
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442 dim_vector dv; |
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443 dv.resize (mdims); |
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444 |
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445 for (int i = 0; i < mdims; i++) |
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446 { |
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5760
|
447 if (! is.read (reinterpret_cast<char *> (&di), 4)) |
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4687
|
448 return false; |
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|
449 if (swap) |
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4944
|
450 swap_bytes<4> (&di); |
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4687
|
451 dv(i) = di; |
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452 } |
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453 |
|
5157
|
454 // Convert an array with a single dimension to be a row vector. |
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|
455 // Octave should never write files like this, other software |
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|
456 // might. |
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457 |
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|
458 if (mdims == 1) |
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459 { |
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|
460 mdims = 2; |
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|
461 dv.resize (mdims); |
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|
462 dv(1) = dv(0); |
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|
463 dv(0) = 1; |
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|
464 } |
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465 |
|
5760
|
466 if (! is.read (reinterpret_cast<char *> (&tmp), 1)) |
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4687
|
467 return false; |
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|
468 |
|
|
469 NDArray m(dv); |
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|
470 double *re = m.fortran_vec (); |
|
5760
|
471 read_doubles (is, re, static_cast<save_type> (tmp), dv.numel (), swap, fmt); |
|
4687
|
472 if (error_state || ! is) |
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|
473 return false; |
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|
474 matrix = m; |
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|
475 } |
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|
476 else |
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|
477 { |
|
5828
|
478 int32_t nr, nc; |
|
4687
|
479 nr = mdims; |
|
5760
|
480 if (! is.read (reinterpret_cast<char *> (&nc), 4)) |
|
4687
|
481 return false; |
|
|
482 if (swap) |
|
4944
|
483 swap_bytes<4> (&nc); |
|
5760
|
484 if (! is.read (reinterpret_cast<char *> (&tmp), 1)) |
|
4687
|
485 return false; |
|
|
486 Matrix m (nr, nc); |
|
|
487 double *re = m.fortran_vec (); |
|
5275
|
488 octave_idx_type len = nr * nc; |
|
5760
|
489 read_doubles (is, re, static_cast<save_type> (tmp), len, swap, fmt); |
|
4687
|
490 if (error_state || ! is) |
|
|
491 return false; |
|
|
492 matrix = m; |
|
|
493 } |
|
|
494 return true; |
|
|
495 } |
|
|
496 |
|
|
497 #if defined (HAVE_HDF5) |
|
4944
|
498 |
|
4687
|
499 bool |
|
|
500 octave_matrix::save_hdf5 (hid_t loc_id, const char *name, bool save_as_floats) |
|
|
501 { |
|
4837
|
502 dim_vector dv = dims (); |
|
|
503 int empty = save_hdf5_empty (loc_id, name, dv); |
|
|
504 if (empty) |
|
4805
|
505 return (empty > 0); |
|
|
506 |
|
4837
|
507 int rank = dv.length (); |
|
4687
|
508 hid_t space_hid = -1, data_hid = -1; |
|
|
509 bool retval = true; |
|
|
510 NDArray m = array_value (); |
|
|
511 |
|
4805
|
512 OCTAVE_LOCAL_BUFFER (hsize_t, hdims, rank); |
|
|
513 |
|
4687
|
514 // Octave uses column-major, while HDF5 uses row-major ordering |
|
4805
|
515 for (int i = 0; i < rank; i++) |
|
4837
|
516 hdims[i] = dv (rank-i-1); |
|
4805
|
517 |
|
4815
|
518 space_hid = H5Screate_simple (rank, hdims, 0); |
|
4687
|
519 |
|
|
520 if (space_hid < 0) return false; |
|
|
521 |
|
|
522 hid_t save_type_hid = H5T_NATIVE_DOUBLE; |
|
|
523 |
|
|
524 if (save_as_floats) |
|
|
525 { |
|
|
526 if (m.too_large_for_float ()) |
|
|
527 { |
|
|
528 warning ("save: some values too large to save as floats --"); |
|
|
529 warning ("save: saving as doubles instead"); |
|
|
530 } |
|
|
531 else |
|
|
532 save_type_hid = H5T_NATIVE_FLOAT; |
|
|
533 } |
|
|
534 #if HAVE_HDF5_INT2FLOAT_CONVERSIONS |
|
|
535 // hdf5 currently doesn't support float/integer conversions |
|
|
536 else |
|
|
537 { |
|
|
538 double max_val, min_val; |
|
|
539 |
|
|
540 if (m.all_integers (max_val, min_val)) |
|
|
541 save_type_hid |
|
|
542 = save_type_to_hdf5 (get_save_type (max_val, min_val)); |
|
|
543 } |
|
|
544 #endif /* HAVE_HDF5_INT2FLOAT_CONVERSIONS */ |
|
|
545 |
|
|
546 data_hid = H5Dcreate (loc_id, name, save_type_hid, space_hid, |
|
|
547 H5P_DEFAULT); |
|
|
548 if (data_hid < 0) |
|
|
549 { |
|
|
550 H5Sclose (space_hid); |
|
|
551 return false; |
|
|
552 } |
|
|
553 |
|
|
554 double *mtmp = m.fortran_vec (); |
|
|
555 retval = H5Dwrite (data_hid, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, |
|
4815
|
556 H5P_DEFAULT, mtmp) >= 0; |
|
4687
|
557 |
|
|
558 H5Dclose (data_hid); |
|
|
559 H5Sclose (space_hid); |
|
4837
|
560 |
|
4687
|
561 return retval; |
|
|
562 } |
|
|
563 |
|
|
564 bool |
|
|
565 octave_matrix::load_hdf5 (hid_t loc_id, const char *name, |
|
|
566 bool /* have_h5giterate_bug */) |
|
|
567 { |
|
4837
|
568 bool retval = false; |
|
|
569 |
|
4805
|
570 dim_vector dv; |
|
|
571 int empty = load_hdf5_empty (loc_id, name, dv); |
|
|
572 if (empty > 0) |
|
|
573 matrix.resize(dv); |
|
4837
|
574 if (empty) |
|
4805
|
575 return (empty > 0); |
|
|
576 |
|
4687
|
577 hid_t data_hid = H5Dopen (loc_id, name); |
|
|
578 hid_t space_id = H5Dget_space (data_hid); |
|
|
579 |
|
|
580 hsize_t rank = H5Sget_simple_extent_ndims (space_id); |
|
|
581 |
|
|
582 if (rank < 1) |
|
|
583 { |
|
|
584 H5Sclose (space_id); |
|
|
585 H5Dclose (data_hid); |
|
|
586 return false; |
|
|
587 } |
|
|
588 |
|
|
589 OCTAVE_LOCAL_BUFFER (hsize_t, hdims, rank); |
|
|
590 OCTAVE_LOCAL_BUFFER (hsize_t, maxdims, rank); |
|
|
591 |
|
|
592 H5Sget_simple_extent_dims (space_id, hdims, maxdims); |
|
|
593 |
|
|
594 // Octave uses column-major, while HDF5 uses row-major ordering |
|
|
595 if (rank == 1) |
|
|
596 { |
|
|
597 dv.resize (2); |
|
|
598 dv(0) = 1; |
|
|
599 dv(1) = hdims[0]; |
|
|
600 } |
|
|
601 else |
|
|
602 { |
|
|
603 dv.resize (rank); |
|
4815
|
604 for (hsize_t i = 0, j = rank - 1; i < rank; i++, j--) |
|
4687
|
605 dv(j) = hdims[i]; |
|
|
606 } |
|
|
607 |
|
|
608 NDArray m (dv); |
|
|
609 double *re = m.fortran_vec (); |
|
|
610 if (H5Dread (data_hid, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, |
|
4815
|
611 H5P_DEFAULT, re) >= 0) |
|
4687
|
612 { |
|
|
613 retval = true; |
|
|
614 matrix = m; |
|
|
615 } |
|
|
616 |
|
|
617 H5Sclose (space_id); |
|
|
618 H5Dclose (data_hid); |
|
4837
|
619 |
|
4687
|
620 return retval; |
|
|
621 } |
|
4944
|
622 |
|
4687
|
623 #endif |
|
|
624 |
|
4643
|
625 void |
|
|
626 octave_matrix::print_raw (std::ostream& os, |
|
|
627 bool pr_as_read_syntax) const |
|
|
628 { |
|
|
629 octave_print_internal (os, matrix, pr_as_read_syntax, |
|
|
630 current_print_indent_level ()); |
|
|
631 } |
|
|
632 |
|
5900
|
633 mxArray * |
|
|
634 octave_matrix::as_mxArray (void) const |
|
|
635 { |
|
|
636 mxArray *retval = new mxArray (mxDOUBLE_CLASS, dims (), mxREAL); |
|
|
637 |
|
|
638 double *pr = static_cast<double *> (retval->get_data ()); |
|
|
639 |
|
6686
|
640 mwSize nel = numel (); |
|
5900
|
641 |
|
|
642 const double *p = matrix.data (); |
|
|
643 |
|
6686
|
644 for (mwIndex i = 0; i < nel; i++) |
|
5900
|
645 pr[i] = p[i]; |
|
|
646 |
|
|
647 return retval; |
|
|
648 } |
|
|
649 |
|
4901
|
650 DEFUN (double, args, , |
|
|
651 "-*- texinfo -*-\n\ |
|
|
652 @deftypefn {Built-in Function} {} double (@var{x})\n\ |
|
|
653 Convert @var{x} to double precision type.\n\ |
|
|
654 @end deftypefn") |
|
|
655 { |
|
7004
|
656 // The OCTAVE_TYPE_CONV_BODY3 macro declares retval, so they go |
|
|
657 // inside their own scopes, and we don't declare retval here to |
|
|
658 // avoid a shadowed declaration warning. |
|
|
659 |
|
|
660 if (args.length () == 1) |
|
|
661 { |
|
|
662 if (args(0).is_sparse_type ()) |
|
|
663 { |
|
|
664 OCTAVE_TYPE_CONV_BODY3 (double, octave_sparse_matrix, octave_scalar); |
|
|
665 } |
|
|
666 else |
|
|
667 { |
|
|
668 OCTAVE_TYPE_CONV_BODY3 (double, octave_matrix, octave_scalar); |
|
|
669 } |
|
|
670 } |
|
|
671 else |
|
|
672 print_usage (); |
|
|
673 |
|
|
674 return octave_value (); |
|
4901
|
675 } |
|
|
676 |
|
2376
|
677 /* |
|
|
678 ;;; Local Variables: *** |
|
|
679 ;;; mode: C++ *** |
|
|
680 ;;; End: *** |
|
|
681 */ |
