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1 /* |
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2 |
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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 2, or (at your option) any |
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10 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, write to the Free |
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19 Software Foundation, 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. |
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20 |
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21 */ |
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22 |
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23 #ifdef HAVE_CONFIG_H |
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24 #include <config.h> |
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25 #endif |
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26 |
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3145
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27 #include <cmath> |
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28 |
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2928
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29 #include "lo-ieee.h" |
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3248
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30 #include "lo-mappers.h" |
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31 #include "dNDArray.h" |
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32 #include "CNDArray.h" |
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33 #include "quit.h" |
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34 |
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35 #include "defun-dld.h" |
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36 #include "error.h" |
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37 #include "gripes.h" |
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38 #include "oct-obj.h" |
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39 |
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40 #include "ov-cx-mat.h" |
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41 |
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42 #define MINMAX_BODY(FCN) \ |
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43 \ |
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44 octave_value_list retval; \ |
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45 \ |
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46 int nargin = args.length (); \ |
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47 \ |
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48 if (nargin < 1 || nargin > 3 || nargout > 2) \ |
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49 { \ |
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50 print_usage (#FCN); \ |
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51 return retval; \ |
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52 } \ |
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53 \ |
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54 octave_value arg1; \ |
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55 octave_value arg2; \ |
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56 octave_value arg3; \ |
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57 \ |
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58 switch (nargin) \ |
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59 { \ |
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60 case 3: \ |
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61 arg3 = args(2); \ |
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62 \ |
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63 case 2: \ |
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64 arg2 = args(1); \ |
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65 \ |
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66 case 1: \ |
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67 arg1 = args(0); \ |
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68 break; \ |
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69 \ |
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70 default: \ |
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71 panic_impossible (); \ |
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72 break; \ |
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73 } \ |
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74 \ |
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75 int dim; \ |
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76 dim_vector dv = ((const octave_complex_matrix&) arg1) .dims (); \ |
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77 if (error_state) \ |
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78 { \ |
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79 gripe_wrong_type_arg (#FCN, arg1); \ |
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80 return retval; \ |
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81 } \ |
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82 \ |
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83 if (nargin == 3) \ |
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84 { \ |
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85 dim = arg3.nint_value () - 1; \ |
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86 if (dim < 0 || dim >= dv.length ()) \ |
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87 { \ |
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88 error ("%s: invalid dimension", #FCN); \ |
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89 return retval; \ |
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90 } \ |
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91 } \ |
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92 else \ |
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93 { \ |
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94 dim = 0; \ |
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95 while ((dim < dv.length ()) && (dv (dim) <= 1)) \ |
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96 dim++; \ |
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97 if (dim == dv.length ()) \ |
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98 dim = 0; \ |
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99 } \ |
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100 \ |
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101 bool single_arg = (nargin == 1) || arg2.is_empty(); \ |
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102 \ |
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103 if (single_arg) \ |
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104 { \ |
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105 dv(dim) = 1; \ |
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106 int n_dims = dv.length (); \ |
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107 for (int i = n_dims; i > 1; i--) \ |
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108 { \ |
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109 if (dv(i-1) == 1) \ |
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110 n_dims--; \ |
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111 else \ |
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112 break; \ |
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113 } \ |
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114 dv.resize (n_dims); \ |
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115 } \ |
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116 \ |
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117 if (single_arg && (nargout == 1 || nargout == 0)) \ |
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118 { \ |
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119 if (arg1.is_real_type ()) \ |
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120 { \ |
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121 NDArray m = arg1.array_value (); \ |
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122 \ |
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123 if (! error_state) \ |
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124 { \ |
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125 NDArray n = m. FCN (dim); \ |
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126 n.resize (dv); \ |
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127 retval(0) = n; \ |
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128 } \ |
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129 } \ |
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130 else if (arg1.is_complex_type ()) \ |
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131 { \ |
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132 ComplexNDArray m = arg1.complex_array_value (); \ |
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133 \ |
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134 if (! error_state) \ |
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135 { \ |
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136 ComplexNDArray n = m. FCN (dim); \ |
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137 n.resize (dv); \ |
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138 retval(0) = n; \ |
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139 } \ |
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140 } \ |
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141 else \ |
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142 gripe_wrong_type_arg (#FCN, arg1); \ |
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143 } \ |
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144 else if (single_arg && nargout == 2) \ |
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145 { \ |
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146 ArrayN<int> index; \ |
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147 \ |
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148 if (arg1.is_real_type ()) \ |
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149 { \ |
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150 NDArray m = arg1.array_value (); \ |
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151 \ |
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152 if (! error_state) \ |
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153 { \ |
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154 NDArray n = m. FCN (index, dim); \ |
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155 n.resize (dv); \ |
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156 retval(0) = n; \ |
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157 } \ |
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158 } \ |
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159 else if (arg1.is_complex_type ()) \ |
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160 { \ |
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161 ComplexNDArray m = arg1.complex_array_value (); \ |
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162 \ |
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163 if (! error_state) \ |
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164 { \ |
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165 ComplexNDArray n = m. FCN (index, dim); \ |
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166 n.resize (dv); \ |
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167 retval(0) = n; \ |
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168 } \ |
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169 } \ |
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170 else \ |
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171 gripe_wrong_type_arg (#FCN, arg1); \ |
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172 \ |
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173 int len = index.numel (); \ |
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174 \ |
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175 if (len > 0) \ |
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176 { \ |
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177 double nan_val = lo_ieee_nan_value (); \ |
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178 \ |
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179 NDArray idx (index.dims ()); \ |
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180 \ |
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181 for (int i = 0; i < len; i++) \ |
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182 { \ |
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183 OCTAVE_QUIT; \ |
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184 int tmp = index.elem (i) + 1; \ |
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185 idx.elem (i) = (tmp <= 0) \ |
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186 ? nan_val : static_cast<double> (tmp); \ |
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187 } \ |
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188 \ |
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189 retval(1) = idx; \ |
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190 } \ |
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191 else \ |
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192 retval(1) = NDArray (); \ |
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193 } \ |
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194 else \ |
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195 { \ |
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196 int arg1_is_scalar = arg1.is_scalar_type (); \ |
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197 int arg2_is_scalar = arg2.is_scalar_type (); \ |
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198 \ |
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199 int arg1_is_complex = arg1.is_complex_type (); \ |
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200 int arg2_is_complex = arg2.is_complex_type (); \ |
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201 \ |
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202 if (arg1_is_scalar) \ |
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203 { \ |
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204 if (arg1_is_complex || arg2_is_complex) \ |
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205 { \ |
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206 Complex c1 = arg1.complex_value (); \ |
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207 ComplexNDArray m2 = arg2.complex_array_value (); \ |
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208 if (! error_state) \ |
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209 { \ |
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210 ComplexNDArray result = FCN (c1, m2); \ |
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211 if (! error_state) \ |
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212 retval(0) = result; \ |
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213 } \ |
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214 } \ |
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215 else \ |
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216 { \ |
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217 double d1 = arg1.double_value (); \ |
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218 NDArray m2 = arg2.array_value (); \ |
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219 \ |
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220 if (! error_state) \ |
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221 { \ |
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222 NDArray result = FCN (d1, m2); \ |
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223 if (! error_state) \ |
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224 retval(0) = result; \ |
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225 } \ |
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226 } \ |
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227 } \ |
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228 else if (arg2_is_scalar) \ |
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229 { \ |
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230 if (arg1_is_complex || arg2_is_complex) \ |
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231 { \ |
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232 ComplexNDArray m1 = arg1.complex_array_value (); \ |
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233 \ |
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234 if (! error_state) \ |
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235 { \ |
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236 Complex c2 = arg2.complex_value (); \ |
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237 ComplexNDArray result = FCN (m1, c2); \ |
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238 if (! error_state) \ |
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239 retval(0) = result; \ |
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240 } \ |
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241 } \ |
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242 else \ |
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243 { \ |
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244 NDArray m1 = arg1.array_value (); \ |
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245 \ |
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246 if (! error_state) \ |
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247 { \ |
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248 double d2 = arg2.double_value (); \ |
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249 NDArray result = FCN (m1, d2); \ |
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250 if (! error_state) \ |
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251 retval(0) = result; \ |
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252 } \ |
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253 } \ |
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254 } \ |
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255 else \ |
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256 { \ |
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257 if (arg1_is_complex || arg2_is_complex) \ |
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258 { \ |
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259 ComplexNDArray m1 = arg1.complex_array_value (); \ |
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260 \ |
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261 if (! error_state) \ |
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262 { \ |
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263 ComplexNDArray m2 = arg2.complex_array_value (); \ |
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264 \ |
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265 if (! error_state) \ |
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266 { \ |
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267 ComplexNDArray result = FCN (m1, m2); \ |
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268 if (! error_state) \ |
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269 retval(0) = result; \ |
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270 } \ |
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271 } \ |
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272 } \ |
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273 else \ |
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274 { \ |
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275 NDArray m1 = arg1.array_value (); \ |
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276 \ |
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277 if (! error_state) \ |
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278 { \ |
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279 NDArray m2 = arg2.array_value (); \ |
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280 \ |
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281 if (! error_state) \ |
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282 { \ |
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283 NDArray result = FCN (m1, m2); \ |
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284 if (! error_state) \ |
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285 retval(0) = result; \ |
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286 } \ |
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287 } \ |
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288 } \ |
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289 } \ |
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290 } \ |
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291 \ |
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292 return retval |
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293 |
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294 DEFUN_DLD (min, args, nargout, |
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295 "-*- texinfo -*-\n\ |
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296 @deftypefn {Mapping Function} {} min (@var{x}, @var{y}, @var{dim})\n\ |
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297 @deftypefnx {Mapping Function} {[@var{w}, @var{iw}] =} min (@var{x})\n\ |
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298 @cindex Utility Functions\n\ |
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299 For a vector argument, return the minimum value. For a matrix\n\ |
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300 argument, return the minimum value from each column, as a row\n\ |
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301 vector, or over the dimension @var{dim} if defined. For two matrices\n\ |
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302 (or a matrix and scalar), return the pair-wise minimum.\n\ |
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303 Thus,\n\ |
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304 \n\ |
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305 @example\n\ |
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306 min (min (@var{x}))\n\ |
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307 @end example\n\ |
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308 \n\ |
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309 @noindent\n\ |
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310 returns the smallest element of @var{x}, and\n\ |
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311 \n\ |
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312 @example\n\ |
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313 @group\n\ |
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314 min (2:5, pi)\n\ |
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315 @result{} 2.0000 3.0000 3.1416 3.1416\n\ |
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316 @end group\n\ |
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317 @end example\n\ |
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318 @noindent\n\ |
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319 compares each element of the range @code{2:5} with @code{pi}, and\n\ |
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320 returns a row vector of the minimum values.\n\ |
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321 \n\ |
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322 For complex arguments, the magnitude of the elements are used for\n\ |
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323 comparison.\n\ |
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324 \n\ |
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325 If called with one input and two output arguments,\n\ |
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326 @code{min} also returns the first index of the\n\ |
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327 minimum value(s). Thus,\n\ |
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328 \n\ |
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329 @example\n\ |
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330 @group\n\ |
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331 [x, ix] = min ([1, 3, 0, 2, 5])\n\ |
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332 @result{} x = 0\n\ |
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333 ix = 3\n\ |
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334 @end group\n\ |
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335 @end example\n\ |
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336 @end deftypefn") |
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337 { |
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338 MINMAX_BODY (min); |
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339 } |
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340 |
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341 DEFUN_DLD (max, args, nargout, |
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342 "-*- texinfo -*-\n\ |
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343 @deftypefn {Mapping Function} {} max (@var{x}, @var{y}, @var{dim})\n\ |
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344 @deftypefnx {Mapping Function} {[@var{w}, @var{iw}] =} max (@var{x})\n\ |
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345 @cindex Utility Functions\n\ |
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346 For a vector argument, return the maximum value. For a matrix\n\ |
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347 argument, return the maximum value from each column, as a row\n\ |
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348 vector, or over the dimension @var{dim} if defined. For two matrices\n\ |
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349 (or a matrix and scalar), return the pair-wise maximum.\n\ |
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350 Thus,\n\ |
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351 \n\ |
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352 @example\n\ |
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353 max (max (@var{x}))\n\ |
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354 @end example\n\ |
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355 \n\ |
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356 @noindent\n\ |
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357 returns the largest element of @var{x}, and\n\ |
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358 \n\ |
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359 @example\n\ |
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360 @group\n\ |
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361 max (2:5, pi)\n\ |
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362 @result{} 3.1416 3.1416 4.0000 5.0000\n\ |
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363 @end group\n\ |
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364 @end example\n\ |
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365 @noindent\n\ |
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366 compares each element of the range @code{2:5} with @code{pi}, and\n\ |
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367 returns a row vector of the maximum values.\n\ |
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368 \n\ |
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369 For complex arguments, the magnitude of the elements are used for\n\ |
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370 comparison.\n\ |
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371 \n\ |
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372 If called with one input and two output arguments,\n\ |
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373 @code{max} also returns the first index of the\n\ |
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374 maximum value(s). Thus,\n\ |
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375 \n\ |
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376 @example\n\ |
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377 @group\n\ |
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378 [x, ix] = max ([1, 3, 5, 2, 5])\n\ |
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379 @result{} x = 5\n\ |
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380 ix = 3\n\ |
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381 @end group\n\ |
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382 @end example\n\ |
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383 @end deftypefn") |
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384 { |
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385 MINMAX_BODY (max); |
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386 } |
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387 |
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388 /* |
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389 ;;; Local Variables: *** |
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390 ;;; mode: C++ *** |
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391 ;;; End: *** |
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392 */ |
