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author Rik <octave@nomad.inbox5.com>
date Sat, 31 Jul 2010 11:18:11 -0700
parents a8ce6bdecce5
children a4f482e66b65
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1 /*
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2
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3 Copyright (C) 2004, 2007 David Bateman
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4 Copyright (C) 2009 VZLU Prague
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5
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6 This program is free software; you can redistribute it and/or modify it
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7 under the terms of the GNU General Public License as published by
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8 the Free Software Foundation; either version 3, or (at your option)
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9 any later version.
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10
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11 This program is distributed in the hope that it will be useful, but
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12 WITHOUT ANY WARRANTY; without even the implied warranty of
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13 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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14 General Public License for more details.
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15
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16 You should have received a copy of the GNU General Public License
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17 along with Octave; see the file COPYING. If not, see
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18 <http://www.gnu.org/licenses/>.
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19
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20 */
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21
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22 #ifdef HAVE_CONFIG_H
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23 #include <config.h>
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24 #endif
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25
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26 #include <algorithm>
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27 #include "Array.h"
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28 #include "Sparse.h"
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29 #include "mx-base.h"
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30
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31 #include "ov.h"
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32 #include "Cell.h"
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33
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34 #include "defun-dld.h"
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35 #include "error.h"
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36 #include "oct-obj.h"
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37
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38 // The bulk of the work.
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39 template <class T>
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40 static Array<T>
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41 do_tril (const Array<T>& a, octave_idx_type k, bool pack)
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42 {
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43 octave_idx_type nr = a.rows (), nc = a.columns ();
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44 const T *avec = a.fortran_vec ();
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45 octave_idx_type zero = 0;
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46
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47 if (pack)
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48 {
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49 octave_idx_type j1 = std::min (std::max (zero, k), nc);
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50 octave_idx_type j2 = std::min (std::max (zero, nr + k), nc);
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51 octave_idx_type n = j1 * nr + ((j2 - j1) * (nr-(j1-k) + nr-(j2-1-k))) / 2;
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52 Array<T> r (n, 1);
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53 T *rvec = r.fortran_vec ();
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54 for (octave_idx_type j = 0; j < nc; j++)
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55 {
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56 octave_idx_type ii = std::min (std::max (zero, j - k), nr);
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57 rvec = std::copy (avec + ii, avec + nr, rvec);
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58 avec += nr;
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59 }
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60
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61 return r;
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62 }
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63 else
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64 {
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65 Array<T> r (a.dims ());
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66 T *rvec = r.fortran_vec ();
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67 for (octave_idx_type j = 0; j < nc; j++)
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68 {
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69 octave_idx_type ii = std::min (std::max (zero, j - k), nr);
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70 std::fill (rvec, rvec + ii, T());
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71 std::copy (avec + ii, avec + nr, rvec + ii);
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72 avec += nr;
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73 rvec += nr;
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74 }
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75
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76 return r;
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77 }
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78 }
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79
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80 template <class T>
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81 static Array<T>
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82 do_triu (const Array<T>& a, octave_idx_type k, bool pack)
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83 {
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84 octave_idx_type nr = a.rows (), nc = a.columns ();
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85 const T *avec = a.fortran_vec ();
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86 octave_idx_type zero = 0;
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87
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88 if (pack)
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89 {
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90 octave_idx_type j1 = std::min (std::max (zero, k), nc);
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91 octave_idx_type j2 = std::min (std::max (zero, nr + k), nc);
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92 octave_idx_type n = ((j2 - j1) * ((j1+1-k) + (j2-k))) / 2 + (nc - j2) * nr;
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93 Array<T> r (n, 1);
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94 T *rvec = r.fortran_vec ();
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95 for (octave_idx_type j = 0; j < nc; j++)
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96 {
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97 octave_idx_type ii = std::min (std::max (zero, j + 1 - k), nr);
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98 rvec = std::copy (avec, avec + ii, rvec);
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99 avec += nr;
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100 }
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101
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102 return r;
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103 }
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104 else
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105 {
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106 NoAlias<Array<T> > r (a.dims ());
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107 T *rvec = r.fortran_vec ();
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108 for (octave_idx_type j = 0; j < nc; j++)
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109 {
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110 octave_idx_type ii = std::min (std::max (zero, j + 1 - k), nr);
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111 std::copy (avec, avec + ii, rvec);
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112 std::fill (rvec + ii, rvec + nr, T());
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113 avec += nr;
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114 rvec += nr;
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115 }
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116
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117 return r;
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118 }
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119 }
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120
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121 // These two are by David Bateman.
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122 // FIXME: optimizations possible. "pack" support missing.
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123
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124 template <class T>
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125 static Sparse<T>
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126 do_tril (const Sparse<T>& a, octave_idx_type k, bool pack)
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127 {
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128 if (pack) // FIXME
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129 {
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130 error ("tril: \"pack\" not implemented for sparse matrices");
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131 return Sparse<T> ();
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132 }
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133
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134 Sparse<T> m = a;
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135 octave_idx_type nc = m.cols();
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136
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137 for (octave_idx_type j = 0; j < nc; j++)
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138 for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++)
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139 if (m.ridx(i) < j-k)
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140 m.data(i) = 0.;
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141
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142 m.maybe_compress (true);
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143 return m;
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144 }
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145
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146 template <class T>
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147 static Sparse<T>
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148 do_triu (const Sparse<T>& a, octave_idx_type k, bool pack)
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149 {
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150 if (pack) // FIXME
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151 {
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152 error ("triu: \"pack\" not implemented for sparse matrices");
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153 return Sparse<T> ();
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154 }
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155
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156 Sparse<T> m = a;
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157 octave_idx_type nc = m.cols();
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158
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159 for (octave_idx_type j = 0; j < nc; j++)
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160 for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++)
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161 if (m.ridx(i) > j-k)
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162 m.data(i) = 0.;
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163
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164 m.maybe_compress (true);
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165 return m;
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166 }
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167
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168 // Convenience dispatchers.
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169 template <class T>
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170 static Array<T>
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171 do_trilu (const Array<T>& a, octave_idx_type k, bool lower, bool pack)
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172 {
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173 return lower ? do_tril (a, k, pack) : do_triu (a, k, pack);
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174 }
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175
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176 template <class T>
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177 static Sparse<T>
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178 do_trilu (const Sparse<T>& a, octave_idx_type k, bool lower, bool pack)
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179 {
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180 return lower ? do_tril (a, k, pack) : do_triu (a, k, pack);
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181 }
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182
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183 static octave_value
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184 do_trilu (const std::string& name,
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185 const octave_value_list& args)
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186 {
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187 bool lower = name == "tril";
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188
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189 octave_value retval;
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190 int nargin = args.length ();
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191 octave_idx_type k = 0;
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192 bool pack = false;
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193 if (nargin >= 2 && args(nargin-1).is_string ())
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194 {
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195 pack = args(nargin-1).string_value () == "pack";
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196 nargin--;
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197 }
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198
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199 if (nargin == 2)
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200 {
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201 k = args(1).int_value (true);
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202
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203 if (error_state)
10154
40dfc0c99116 DLD-FUNCTIONS/*.cc: untabify
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204 return retval;
9756
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205 }
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206
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207 if (nargin < 1 || nargin > 2)
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208 print_usage ();
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209 else
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210 {
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211 octave_value arg = args (0);
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212
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213 dim_vector dims = arg.dims ();
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214 if (dims.length () != 2)
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215 error ("%s: needs a 2D matrix", name.c_str ());
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216 else if (k < -dims (0) || k > dims(1))
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217 error ("%s: requested diagonal out of range", name.c_str ());
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218 else
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219 {
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220 switch (arg.builtin_type ())
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221 {
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222 case btyp_double:
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223 if (arg.is_sparse_type ())
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224 retval = do_trilu (arg.sparse_matrix_value (), k, lower, pack);
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225 else
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226 retval = do_trilu (arg.array_value (), k, lower, pack);
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227 break;
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228 case btyp_complex:
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229 if (arg.is_sparse_type ())
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230 retval = do_trilu (arg.sparse_complex_matrix_value (), k, lower, pack);
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231 else
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232 retval = do_trilu (arg.complex_array_value (), k, lower, pack);
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233 break;
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234 case btyp_bool:
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235 if (arg.is_sparse_type ())
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236 retval = do_trilu (arg.sparse_bool_matrix_value (), k, lower, pack);
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237 else
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238 retval = do_trilu (arg.bool_array_value (), k, lower, pack);
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239 break;
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240 #define ARRAYCASE(TYP) \
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241 case btyp_ ## TYP: \
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242 retval = do_trilu (arg.TYP ## _array_value (), k, lower, pack); \
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243 break
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244 ARRAYCASE (float);
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245 ARRAYCASE (float_complex);
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246 ARRAYCASE (int8);
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247 ARRAYCASE (int16);
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248 ARRAYCASE (int32);
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249 ARRAYCASE (int64);
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250 ARRAYCASE (uint8);
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251 ARRAYCASE (uint16);
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252 ARRAYCASE (uint32);
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253 ARRAYCASE (uint64);
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254 ARRAYCASE (char);
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255 #undef ARRAYCASE
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256 default:
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257 {
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258 // Generic code that works on octave-values, that is slow
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259 // but will also work on arbitrary user types
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260
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261 if (pack) // FIXME
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262 {
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263 error ("%s: \"pack\" not implemented for class %s",
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264 name.c_str (), arg.class_name ().c_str ());
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265 return octave_value ();
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266 }
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267
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268 octave_value tmp = arg;
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269 if (arg.numel () == 0)
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270 return arg;
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271
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272 octave_idx_type nr = dims(0), nc = dims (1);
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273
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274 // The sole purpose of the below is to force the correct
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275 // matrix size. This would not be necessary if the
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276 // octave_value resize function allowed a fill_value.
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277 // It also allows odd attributes in some user types
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278 // to be handled. With a fill_value ot should be replaced
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279 // with
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280 //
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281 // octave_value_list ov_idx;
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282 // tmp = tmp.resize(dim_vector (0,0)).resize (dims, fill_value);
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283
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284 octave_value_list ov_idx;
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285 std::list<octave_value_list> idx_tmp;
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286 ov_idx(1) = static_cast<double> (nc+1);
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287 ov_idx(0) = Range (1, nr);
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288 idx_tmp.push_back (ov_idx);
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289 ov_idx(1) = static_cast<double> (nc);
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290 tmp = tmp.resize (dim_vector (0,0));
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291 tmp = tmp.subsasgn("(",idx_tmp, arg.do_index_op (ov_idx));
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292 tmp = tmp.resize(dims);
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293
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294 if (lower)
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295 {
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296 octave_idx_type st = nc < nr + k ? nc : nr + k;
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297
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298 for (octave_idx_type j = 1; j <= st; j++)
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299 {
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300 octave_idx_type nr_limit = 1 > j - k ? 1 : j - k;
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301 ov_idx(1) = static_cast<double> (j);
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302 ov_idx(0) = Range (nr_limit, nr);
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303 std::list<octave_value_list> idx;
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304 idx.push_back (ov_idx);
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305
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306 tmp = tmp.subsasgn ("(", idx, arg.do_index_op(ov_idx));
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307
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308 if (error_state)
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309 return retval;
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310 }
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311 }
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312 else
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313 {
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314 octave_idx_type st = k + 1 > 1 ? k + 1 : 1;
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315
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316 for (octave_idx_type j = st; j <= nc; j++)
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317 {
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318 octave_idx_type nr_limit = nr < j - k ? nr : j - k;
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319 ov_idx(1) = static_cast<double> (j);
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320 ov_idx(0) = Range (1, nr_limit);
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321 std::list<octave_value_list> idx;
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322 idx.push_back (ov_idx);
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323
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324 tmp = tmp.subsasgn ("(", idx, arg.do_index_op(ov_idx));
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325
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326 if (error_state)
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327 return retval;
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328 }
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329 }
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330
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331 retval = tmp;
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332 }
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333 }
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334 }
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335 }
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336
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337 return retval;
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338 }
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339
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340 DEFUN_DLD (tril, args, ,
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341 "-*- texinfo -*-\n\
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342 @deftypefn {Function File} {} tril (@var{a})\n\
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343 @deftypefnx {Function File} {} tril (@var{a}, @var{k})\n\
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344 @deftypefnx {Function File} {} tril (@var{a}, @var{k}, @var{pack})\n\
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345 @deftypefnx {Function File} {} triu (@var{a})\n\
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346 @deftypefnx {Function File} {} triu (@var{a}, @var{k})\n\
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347 @deftypefnx {Function File} {} triu (@var{a}, @var{k}, @var{pack})\n\
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348 Return a new matrix formed by extracting extract the lower (@code{tril})\n\
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349 or upper (@code{triu}) triangular part of the matrix @var{a}, and\n\
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350 setting all other elements to zero. The second argument is optional,\n\
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351 and specifies how many diagonals above or below the main diagonal should\n\
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352 also be set to zero.\n\
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353 \n\
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354 The default value of @var{k} is zero, so that @code{triu} and\n\
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355 @code{tril} normally include the main diagonal as part of the result\n\
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356 matrix.\n\
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357 \n\
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358 If the value of @var{k} is negative, additional elements above (for\n\
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359 @code{tril}) or below (for @code{triu}) the main diagonal are also\n\
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360 selected.\n\
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361 \n\
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362 The absolute value of @var{k} must not be greater than the number of\n\
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363 sub- or super-diagonals.\n\
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364 \n\
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365 For example:\n\
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366 \n\
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367 @example\n\
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368 @group\n\
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369 tril (ones (3), -1)\n\
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370 @result{} 0 0 0\n\
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371 1 0 0\n\
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372 1 1 0\n\
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373 @end group\n\
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374 @end example\n\
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375 \n\
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376 @noindent\n\
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377 and\n\
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378 \n\
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379 @example\n\
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380 @group\n\
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381 tril (ones (3), 1)\n\
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382 @result{} 1 1 0\n\
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383 1 1 1\n\
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384 1 1 1\n\
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385 @end group\n\
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386 @end example\n\
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387 \n\
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388 If the option \"pack\" is given as third argument, the extracted elements\n\
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389 are not inserted into a matrix, but rather stacked column-wise one above other.\n\
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390 @seealso{triu, diag}\n\
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391 @end deftypefn")
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392 {
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393 return do_trilu ("tril", args);
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394 }
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395
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396 DEFUN_DLD (triu, args, ,
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397 "-*- texinfo -*-\n\
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398 @deftypefn {Function File} {} triu (@var{a}, @var{k})\n\
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399 See tril.\n\
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400 @end deftypefn")
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401 {
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402 return do_trilu ("triu", args);
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403 }
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404
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405 /*
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406
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407 %!test
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408 %! a = [1, 2, 3; 4, 5, 6; 7, 8, 9; 10, 11, 12];
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409 %!
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410 %! l0 = [1, 0, 0; 4, 5, 0; 7, 8, 9; 10, 11, 12];
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411 %! l1 = [1, 2, 0; 4, 5, 6; 7, 8, 9; 10, 11, 12];
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412 %! l2 = [1, 2, 3; 4, 5, 6; 7, 8, 9; 10, 11, 12];
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413 %! lm1 = [0, 0, 0; 4, 0, 0; 7, 8, 0; 10, 11, 12];
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414 %! lm2 = [0, 0, 0; 0, 0, 0; 7, 0, 0; 10, 11, 0];
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415 %! lm3 = [0, 0, 0; 0, 0, 0; 0, 0, 0; 10, 0, 0];
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416 %! lm4 = [0, 0, 0; 0, 0, 0; 0, 0, 0; 0, 0, 0];
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417 %!
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418 %! assert((tril (a, -4) == lm4 && tril (a, -3) == lm3
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419 %! && tril (a, -2) == lm2 && tril (a, -1) == lm1
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420 %! && tril (a) == l0 && tril (a, 1) == l1 && tril (a, 2) == l2));
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421
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422 %!error tril ();
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423
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424 */