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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 "dMatrix.h" |
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32 #include "CMatrix.h" |
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4153
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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 #define MINMAX_BODY(FCN) \ |
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41 \ |
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42 octave_value_list retval; \ |
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43 \ |
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44 int nargin = args.length (); \ |
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45 \ |
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46 if (nargin < 1 || nargin > 2 || nargout > 2) \ |
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47 { \ |
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48 print_usage (#FCN); \ |
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49 return retval; \ |
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50 } \ |
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51 \ |
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52 octave_value arg1; \ |
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53 octave_value arg2; \ |
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54 \ |
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55 switch (nargin) \ |
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56 { \ |
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57 case 2: \ |
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58 arg2 = args(1); \ |
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59 \ |
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60 case 1: \ |
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61 arg1 = args(0); \ |
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62 break; \ |
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63 \ |
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64 default: \ |
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65 panic_impossible (); \ |
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66 break; \ |
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67 } \ |
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68 \ |
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69 if (nargin == 1 && (nargout == 1 || nargout == 0)) \ |
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70 { \ |
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71 if (arg1.is_real_type ()) \ |
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72 { \ |
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73 Matrix m = arg1.matrix_value (); \ |
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74 \ |
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75 if (! error_state) \ |
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76 { \ |
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77 if (m.rows () == 1) \ |
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78 retval(0) = m.row_ ## FCN (); \ |
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79 else \ |
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80 { \ |
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81 if (m.rows () == 0 || m.columns () == 0) \ |
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82 retval(0) = Matrix (); \ |
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83 else \ |
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84 retval(0) = m.column_ ## FCN (); \ |
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85 } \ |
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86 } \ |
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87 } \ |
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88 else if (arg1.is_complex_type ()) \ |
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89 { \ |
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90 ComplexMatrix m = arg1.complex_matrix_value (); \ |
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91 \ |
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92 if (! error_state) \ |
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93 { \ |
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94 if (m.rows () == 1) \ |
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95 retval(0) = m.row_ ## FCN (); \ |
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96 else \ |
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97 { \ |
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98 if (m.rows () == 0 || m.columns () == 0) \ |
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99 retval(0) = Matrix (); \ |
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100 else \ |
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101 retval(0) = m.column_ ## FCN (); \ |
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102 } \ |
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103 } \ |
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104 } \ |
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105 else \ |
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106 gripe_wrong_type_arg (#FCN, arg1); \ |
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107 } \ |
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108 else if (nargin == 1 && nargout == 2) \ |
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109 { \ |
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110 Array<int> index; \ |
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111 \ |
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112 if (arg1.is_real_type ()) \ |
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113 { \ |
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114 Matrix m = arg1.matrix_value (); \ |
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115 \ |
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116 if (! error_state) \ |
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117 { \ |
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118 retval.resize (2); \ |
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119 \ |
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120 if (m.rows () == 1) \ |
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121 retval(0) = m.row_ ## FCN (index); \ |
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122 else \ |
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123 { \ |
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124 if (m.rows () == 0 || m.columns () == 0) \ |
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125 retval(0) = Matrix (); \ |
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126 else \ |
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127 retval(0) = m.column_ ## FCN (index); \ |
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128 } \ |
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129 } \ |
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130 } \ |
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131 else if (arg1.is_complex_type ()) \ |
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132 { \ |
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133 ComplexMatrix m = arg1.complex_matrix_value (); \ |
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134 \ |
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135 if (! error_state) \ |
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136 { \ |
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137 retval.resize (2); \ |
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138 \ |
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139 if (m.rows () == 1) \ |
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140 retval(0) = m.row_ ## FCN (index); \ |
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141 else \ |
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142 { \ |
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143 if (m.rows () == 0 || m.columns () == 0) \ |
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144 retval(0) = Matrix (); \ |
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145 else \ |
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146 retval(0) = m.column_ ## FCN (index); \ |
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147 } \ |
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148 } \ |
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149 } \ |
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150 else \ |
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151 gripe_wrong_type_arg (#FCN, arg1); \ |
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152 \ |
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153 int len = index.length (); \ |
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154 \ |
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155 if (len > 0) \ |
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156 { \ |
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157 double nan_val = lo_ieee_nan_value (); \ |
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158 \ |
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159 RowVector idx (len); \ |
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160 \ |
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161 for (int i = 0; i < len; i++) \ |
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162 { \ |
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163 OCTAVE_QUIT; \ |
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164 int tmp = index.elem (i) + 1; \ |
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165 idx.elem (i) = (tmp <= 0) \ |
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166 ? nan_val : static_cast<double> (tmp); \ |
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167 } \ |
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168 \ |
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169 retval(1) = idx; \ |
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170 } \ |
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171 else \ |
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172 retval(1) = Matrix (); \ |
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173 } \ |
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174 else if (nargin == 2) \ |
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175 { \ |
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176 int arg1_is_scalar = arg1.is_scalar_type (); \ |
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177 int arg2_is_scalar = arg2.is_scalar_type (); \ |
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178 \ |
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179 int arg1_is_complex = arg1.is_complex_type (); \ |
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180 int arg2_is_complex = arg2.is_complex_type (); \ |
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181 \ |
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182 if (arg1_is_scalar) \ |
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183 { \ |
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184 if (arg1_is_complex || arg2_is_complex) \ |
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185 { \ |
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186 Complex c1 = arg1.complex_value (); \ |
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187 ComplexMatrix m2 = arg2.complex_matrix_value (); \ |
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188 if (! error_state) \ |
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189 { \ |
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190 ComplexMatrix result = FCN (c1, m2); \ |
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191 if (! error_state) \ |
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192 retval(0) = result; \ |
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193 } \ |
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194 } \ |
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195 else \ |
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196 { \ |
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197 double d1 = arg1.double_value (); \ |
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198 Matrix m2 = arg2.matrix_value (); \ |
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199 \ |
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200 if (! error_state) \ |
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201 { \ |
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202 Matrix result = FCN (d1, m2); \ |
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203 if (! error_state) \ |
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204 retval(0) = result; \ |
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205 } \ |
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206 } \ |
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207 } \ |
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208 else if (arg2_is_scalar) \ |
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209 { \ |
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210 if (arg1_is_complex || arg2_is_complex) \ |
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211 { \ |
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212 ComplexMatrix m1 = arg1.complex_matrix_value (); \ |
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213 \ |
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214 if (! error_state) \ |
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215 { \ |
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216 Complex c2 = arg2.complex_value (); \ |
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217 ComplexMatrix result = FCN (m1, c2); \ |
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218 if (! error_state) \ |
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219 retval(0) = result; \ |
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220 } \ |
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221 } \ |
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222 else \ |
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223 { \ |
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224 Matrix m1 = arg1.matrix_value (); \ |
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225 \ |
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226 if (! error_state) \ |
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227 { \ |
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228 double d2 = arg2.double_value (); \ |
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229 Matrix result = FCN (m1, d2); \ |
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230 if (! error_state) \ |
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231 retval(0) = result; \ |
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232 } \ |
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233 } \ |
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234 } \ |
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235 else \ |
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236 { \ |
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237 if (arg1_is_complex || arg2_is_complex) \ |
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238 { \ |
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239 ComplexMatrix m1 = arg1.complex_matrix_value (); \ |
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240 \ |
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241 if (! error_state) \ |
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242 { \ |
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243 ComplexMatrix m2 = arg2.complex_matrix_value (); \ |
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244 \ |
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245 if (! error_state) \ |
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246 { \ |
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247 ComplexMatrix result = FCN (m1, m2); \ |
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248 if (! error_state) \ |
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249 retval(0) = result; \ |
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250 } \ |
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251 } \ |
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252 } \ |
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253 else \ |
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254 { \ |
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255 Matrix m1 = arg1.matrix_value (); \ |
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256 \ |
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257 if (! error_state) \ |
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258 { \ |
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259 Matrix m2 = arg2.matrix_value (); \ |
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260 \ |
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261 if (! error_state) \ |
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262 { \ |
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263 Matrix result = FCN (m1, m2); \ |
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264 if (! error_state) \ |
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265 retval(0) = result; \ |
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266 } \ |
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267 } \ |
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268 } \ |
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269 } \ |
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270 } \ |
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271 else \ |
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272 panic_impossible (); \ |
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273 \ |
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274 return retval |
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275 |
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276 DEFUN_DLD (min, args, nargout, |
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277 "-*- texinfo -*-\n\ |
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278 @deftypefn {Mapping Function} {} min (@var{x}, @var{y})\n\ |
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279 @deftypefnx {Mapping Function} {[@var{w}, @var{iw}] =} min (@var{x})\n\ |
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280 @cindex Utility Functions\n\ |
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281 For a vector argument, return the minimum value. For a matrix\n\ |
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282 argument, return the minimum value from each column, as a row\n\ |
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283 vector.\n\ |
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284 For two matrices (or a matrix and scalar),\n\ |
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285 return the pair-wise minimum.\n\ |
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286 Thus,\n\ |
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287 \n\ |
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288 @example\n\ |
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289 min (min (@var{x}))\n\ |
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290 @end example\n\ |
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291 \n\ |
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292 @noindent\n\ |
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293 returns the smallest element of @var{x}, and\n\ |
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294 \n\ |
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295 @example\n\ |
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296 @group\n\ |
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297 min (2:5, pi)\n\ |
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298 @result{} 2.0000 3.0000 3.1416 3.1416\n\ |
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299 @end group\n\ |
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300 @end example\n\ |
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301 @noindent\n\ |
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302 compares each element of the range @code{2:5} with @code{pi}, and\n\ |
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303 returns a row vector of the minimum values.\n\ |
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304 \n\ |
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305 For complex arguments, the magnitude of the elements are used for\n\ |
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306 comparison.\n\ |
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307 \n\ |
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308 If called with one input and two output arguments,\n\ |
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309 @code{min} also returns the first index of the\n\ |
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310 minimum value(s). Thus,\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 [x, ix] = min ([1, 3, 0, 2, 5])\n\ |
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315 @result{} x = 0\n\ |
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316 ix = 3\n\ |
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317 @end group\n\ |
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318 @end example\n\ |
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319 @end deftypefn") |
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320 { |
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321 MINMAX_BODY (min); |
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322 } |
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323 |
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324 DEFUN_DLD (max, args, nargout, |
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325 "-*- texinfo -*-\n\ |
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326 @deftypefn {Mapping Function} {} max (@var{x}, @var{y})\n\ |
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327 @deftypefnx {Mapping Function} {[@var{w}, @var{iw}] =} max (@var{x})\n\ |
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328 @cindex Utility Functions\n\ |
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329 For a vector argument, return the maximum value. For a matrix\n\ |
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330 argument, return the maximum value from each column, as a row\n\ |
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331 vector.\n\ |
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332 For two matrices (or a matrix and scalar),\n\ |
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333 return the pair-wise maximum.\n\ |
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334 Thus,\n\ |
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335 \n\ |
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336 @example\n\ |
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337 max (max (@var{x}))\n\ |
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338 @end example\n\ |
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339 \n\ |
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340 @noindent\n\ |
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341 returns the largest element of @var{x}, and\n\ |
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342 \n\ |
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343 @example\n\ |
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344 @group\n\ |
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345 max (2:5, pi)\n\ |
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346 @result{} 3.1416 3.1416 4.0000 5.0000\n\ |
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347 @end group\n\ |
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348 @end example\n\ |
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349 @noindent\n\ |
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350 compares each element of the range @code{2:5} with @code{pi}, and\n\ |
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351 returns a row vector of the maximum values.\n\ |
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352 \n\ |
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353 For complex arguments, the magnitude of the elements are used for\n\ |
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354 comparison.\n\ |
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355 \n\ |
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356 If called with one input and two output arguments,\n\ |
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357 @code{max} also returns the first index of the\n\ |
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358 maximum value(s). Thus,\n\ |
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359 \n\ |
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360 @example\n\ |
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361 @group\n\ |
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362 [x, ix] = max ([1, 3, 5, 2, 5])\n\ |
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363 @result{} x = 5\n\ |
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364 ix = 3\n\ |
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365 @end group\n\ |
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366 @end example\n\ |
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367 @end deftypefn") |
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368 { |
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369 MINMAX_BODY (max); |
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370 } |
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371 |
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372 /* |
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373 ;;; Local Variables: *** |
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374 ;;; mode: C++ *** |
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375 ;;; End: *** |
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376 */ |
