Mercurial > octave
annotate libinterp/corefcn/filter.cc @ 20915:a3359fe50966
remove unused nargout variables
* __ichol__.cc, __ilu__.cc, ellipj.cc, filter.cc, mgorth.cc, nproc.cc,
pr-output.cc, quad.cc, quadcc.cc, sylvester.cc:
Remove unused nargout from DEFUNs that no longer use it.
author | John W. Eaton <jwe@octave.org> |
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date | Wed, 16 Dec 2015 17:02:23 -0500 |
parents | 03e4ddd49396 |
children | 48b2ad5ee801 |
rev | line source |
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2928 | 1 /* |
2 | |
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3 Copyright (C) 1996-2015 John W. Eaton |
2928 | 4 |
5 This file is part of Octave. | |
6 | |
7 Octave is free software; you can redistribute it and/or modify it | |
8 under the terms of the GNU General Public License as published by the | |
7016 | 9 Free Software Foundation; either version 3 of the License, or (at your |
10 option) any later version. | |
2928 | 11 |
12 Octave is distributed in the hope that it will be useful, but WITHOUT | |
13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
15 for more details. | |
16 | |
17 You should have received a copy of the GNU General Public License | |
7016 | 18 along with Octave; see the file COPYING. If not, see |
19 <http://www.gnu.org/licenses/>. | |
2928 | 20 |
21 */ | |
22 | |
23 // Based on Tony Richardson's filter.m. | |
24 // | |
5428 | 25 // Originally translated to C++ by KH (Kurt.Hornik@wu-wien.ac.at) |
2928 | 26 // with help from Fritz Leisch and Andreas Weingessel on Oct 20, 1994. |
27 // | |
28 // Rewritten to use templates to handle both real and complex cases by | |
29 // jwe, Wed Nov 1 19:15:29 1995. | |
30 | |
31 #ifdef HAVE_CONFIG_H | |
32 #include <config.h> | |
33 #endif | |
34 | |
4153 | 35 #include "quit.h" |
36 | |
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37 #include "defun.h" |
2928 | 38 #include "error.h" |
39 #include "oct-obj.h" | |
40 | |
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41 #if ! defined (CXX_NEW_FRIEND_TEMPLATE_DECL) |
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42 extern MArray<double> |
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43 filter (MArray<double>&, MArray<double>&, MArray<double>&, int dim); |
2928 | 44 |
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45 extern MArray<Complex> |
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46 filter (MArray<Complex>&, MArray<Complex>&, MArray<Complex>&, int dim); |
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47 |
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48 extern MArray<float> |
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49 filter (MArray<float>&, MArray<float>&, MArray<float>&, int dim); |
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50 |
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51 extern MArray<FloatComplex> |
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52 filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArray<FloatComplex>&, |
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53 int dim); |
3107 | 54 #endif |
2928 | 55 |
56 template <class T> | |
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57 MArray<T> |
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58 filter (MArray<T>& b, MArray<T>& a, MArray<T>& x, MArray<T>& si, |
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59 int dim = 0) |
2928 | 60 { |
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61 MArray<T> y; |
2928 | 62 |
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63 octave_idx_type a_len = a.numel (); |
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64 octave_idx_type b_len = b.numel (); |
2928 | 65 |
5275 | 66 octave_idx_type ab_len = a_len > b_len ? a_len : b_len; |
2928 | 67 |
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68 // FIXME: The two lines below should be unecessary because |
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69 // this template is called with a and b as column vectors |
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70 // already. However the a.resize line is currently (2011/04/26) |
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71 // necessary to stop bug #33164. |
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72 b.resize (dim_vector (ab_len, 1), 0.0); |
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73 if (a_len > 1) |
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74 a.resize (dim_vector (ab_len, 1), 0.0); |
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75 |
2928 | 76 T norm = a (0); |
77 | |
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78 if (norm == static_cast<T> (0.0)) |
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79 error ("filter: the first element of A must be nonzero"); |
2928 | 80 |
4844 | 81 dim_vector x_dims = x.dims (); |
5056 | 82 if (dim < 0 || dim > x_dims.length ()) |
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83 error ("filter: DIM must be a valid dimension"); |
4844 | 84 |
5275 | 85 octave_idx_type x_len = x_dims(dim); |
4844 | 86 |
87 dim_vector si_dims = si.dims (); | |
5275 | 88 octave_idx_type si_len = si_dims(0); |
4844 | 89 |
90 if (si_len != ab_len - 1) | |
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91 error ("filter: first dimension of SI must be of length max (length (a), length (b)) - 1"); |
4844 | 92 |
5059 | 93 if (si_dims.length () != x_dims.length ()) |
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94 error ("filter: dimensionality of SI and X must agree"); |
4844 | 95 |
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96 for (octave_idx_type i = 1; i < dim; i++) |
4844 | 97 { |
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98 if (si_dims(i) != x_dims(i-1)) |
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99 error ("filter: dimensionality of SI and X must agree"); |
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100 } |
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101 for (octave_idx_type i = dim+1; i < x_dims.length (); i++) |
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102 { |
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103 if (si_dims(i) != x_dims(i)) |
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104 error ("filter: dimensionality of SI and X must agree"); |
4844 | 105 } |
2928 | 106 |
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107 if (x_len == 0) |
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108 return x; |
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109 |
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110 if (norm != static_cast<T> (1.0)) |
4844 | 111 { |
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112 a /= norm; |
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113 b /= norm; |
4844 | 114 } |
2928 | 115 |
5056 | 116 if (a_len <= 1 && si_len <= 0) |
4844 | 117 return b(0) * x; |
118 | |
119 y.resize (x_dims, 0.0); | |
120 | |
121 int x_stride = 1; | |
122 for (int i = 0; i < dim; i++) | |
123 x_stride *= x_dims(i); | |
2928 | 124 |
5275 | 125 octave_idx_type x_num = x_dims.numel () / x_len; |
126 for (octave_idx_type num = 0; num < x_num; num++) | |
4844 | 127 { |
5275 | 128 octave_idx_type x_offset; |
4844 | 129 if (x_stride == 1) |
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130 x_offset = num * x_len; |
4844 | 131 else |
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132 { |
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133 octave_idx_type x_offset2 = 0; |
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134 x_offset = num; |
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135 while (x_offset >= x_stride) |
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136 { |
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137 x_offset -= x_stride; |
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138 x_offset2++; |
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139 } |
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140 x_offset += x_offset2 * x_stride * x_len; |
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141 } |
5275 | 142 octave_idx_type si_offset = num * si_len; |
2928 | 143 |
4844 | 144 if (a_len > 1) |
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145 { |
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146 T *py = y.fortran_vec (); |
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147 T *psi = si.fortran_vec (); |
5114 | 148 |
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149 const T *pa = a.data (); |
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150 const T *pb = b.data (); |
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151 const T *px = x.data (); |
5114 | 152 |
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153 psi += si_offset; |
5114 | 154 |
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155 for (octave_idx_type i = 0, idx = x_offset; |
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156 i < x_len; |
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157 i++, idx += x_stride) |
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158 { |
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159 py[idx] = psi[0] + pb[0] * px[idx]; |
5114 | 160 |
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161 if (si_len > 0) |
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162 { |
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163 for (octave_idx_type j = 0; j < si_len - 1; j++) |
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164 { |
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165 OCTAVE_QUIT; |
5114 | 166 |
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167 psi[j] = psi[j+1] - pa[j+1] * py[idx] + pb[j+1] * px[idx]; |
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168 } |
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170 psi[si_len-1] = pb[si_len] * px[idx] - pa[si_len] * py[idx]; |
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171 } |
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172 else |
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173 { |
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174 OCTAVE_QUIT; |
5114 | 175 |
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176 psi[0] = pb[si_len] * px[idx] - pa[si_len] * py[idx]; |
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177 } |
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178 } |
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179 } |
5114 | 180 else if (si_len > 0) |
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181 { |
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182 T *py = y.fortran_vec (); |
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183 T *psi = si.fortran_vec (); |
5114 | 184 |
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185 const T *pb = b.data (); |
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186 const T *px = x.data (); |
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188 psi += si_offset; |
5114 | 189 |
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190 for (octave_idx_type i = 0, idx = x_offset; |
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191 i < x_len; |
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192 i++, idx += x_stride) |
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193 { |
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194 py[idx] = psi[0] + pb[0] * px[idx]; |
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196 if (si_len > 1) |
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197 { |
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198 for (octave_idx_type j = 0; j < si_len - 1; j++) |
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199 { |
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200 OCTAVE_QUIT; |
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202 psi[j] = psi[j+1] + pb[j+1] * px[idx]; |
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203 } |
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205 psi[si_len-1] = pb[si_len] * px[idx]; |
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206 } |
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207 else |
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208 { |
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209 OCTAVE_QUIT; |
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211 psi[0] = pb[1] * px[idx]; |
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212 } |
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213 } |
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214 } |
2928 | 215 } |
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216 |
2928 | 217 return y; |
218 } | |
219 | |
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220 #if ! defined (CXX_NEW_FRIEND_TEMPLATE_DECL) |
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221 extern MArray<double> |
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222 filter (MArray<double>&, MArray<double>&, MArray<double>&, |
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223 MArray<double>&, int dim); |
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225 extern MArray<Complex> |
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226 filter (MArray<Complex>&, MArray<Complex>&, MArray<Complex>&, |
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227 MArray<Complex>&, int dim); |
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228 |
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229 extern MArray<float> |
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230 filter (MArray<float>&, MArray<float>&, MArray<float>&, |
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231 MArray<float>&, int dim); |
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232 |
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233 extern MArray<FloatComplex> |
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234 filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArray<FloatComplex>&, |
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235 MArray<FloatComplex>&, int dim); |
3107 | 236 #endif |
2928 | 237 |
238 template <class T> | |
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239 MArray<T> |
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240 filter (MArray<T>& b, MArray<T>& a, MArray<T>& x, int dim = -1) |
2928 | 241 { |
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242 dim_vector x_dims = x.dims (); |
4844 | 243 |
244 if (dim < 0) | |
245 { | |
246 // Find first non-singleton dimension | |
5059 | 247 while (dim < x_dims.length () && x_dims(dim) <= 1) |
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248 dim++; |
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249 |
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251 if (dim == x_dims.length ()) | |
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252 dim = 0; |
4844 | 253 } |
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254 else if (dim < 0 || dim > x_dims.length ()) |
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255 error ("filter: DIM must be a valid dimension"); |
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257 octave_idx_type a_len = a.numel (); |
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258 octave_idx_type b_len = b.numel (); |
2928 | 259 |
5275 | 260 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1; |
4844 | 261 dim_vector si_dims = x.dims (); |
262 for (int i = dim; i > 0; i--) | |
5059 | 263 si_dims(i) = si_dims(i-1); |
264 si_dims(0) = si_len; | |
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265 |
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266 MArray<T> si (si_dims, T (0.0)); |
2928 | 267 |
4844 | 268 return filter (b, a, x, si, dim); |
2928 | 269 } |
270 | |
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271 DEFUN (filter, args, , |
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272 "-*- texinfo -*-\n\ |
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273 @deftypefn {} {@var{y} =} filter (@var{b}, @var{a}, @var{x})\n\ |
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274 @deftypefnx {} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si})\n\ |
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275 @deftypefnx {} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, [], @var{dim})\n\ |
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276 @deftypefnx {} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si}, @var{dim})\n\ |
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277 Apply a 1-D digital filter to the data @var{x}.\n\ |
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278 \n\ |
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279 @code{filter} returns the solution to the following linear, time-invariant\n\ |
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280 difference equation:\n\ |
3367 | 281 @tex\n\ |
282 $$\n\ | |
283 \\sum_{k=0}^N a_{k+1} y_{n-k} = \\sum_{k=0}^M b_{k+1} x_{n-k}, \\qquad\n\ | |
284 1 \\le n \\le P\n\ | |
285 $$\n\ | |
286 @end tex\n\ | |
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287 @ifnottex\n\ |
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288 @c Set example in small font to prevent overfull line\n\ |
2928 | 289 \n\ |
3367 | 290 @smallexample\n\ |
10840 | 291 @group\n\ |
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292 N M\n\ |
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293 SUM a(k+1) y(n-k) = SUM b(k+1) x(n-k) for 1<=n<=length(x)\n\ |
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294 k=0 k=0\n\ |
10840 | 295 @end group\n\ |
3367 | 296 @end smallexample\n\ |
10840 | 297 \n\ |
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298 @end ifnottex\n\ |
2928 | 299 \n\ |
3367 | 300 @noindent\n\ |
301 where\n\ | |
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302 @ifnottex\n\ |
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303 N=length(a)-1 and M=length(b)-1.\n\ |
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304 @end ifnottex\n\ |
3367 | 305 @tex\n\ |
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306 $a \\in \\Re^{N-1}$, $b \\in \\Re^{M-1}$, and $x \\in \\Re^P$.\n\ |
3367 | 307 @end tex\n\ |
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308 The result is calculated over the first non-singleton dimension of @var{x}\n\ |
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309 or over @var{dim} if supplied.\n\ |
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310 \n\ |
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311 An equivalent form of the equation is:\n\ |
3367 | 312 @tex\n\ |
313 $$\n\ | |
314 y_n = -\\sum_{k=1}^N c_{k+1} y_{n-k} + \\sum_{k=0}^M d_{k+1} x_{n-k}, \\qquad\n\ | |
315 1 \\le n \\le P\n\ | |
316 $$\n\ | |
317 @end tex\n\ | |
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318 @ifnottex\n\ |
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319 @c Set example in small font to prevent overfull line\n\ |
2928 | 320 \n\ |
3367 | 321 @smallexample\n\ |
10840 | 322 @group\n\ |
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323 N M\n\ |
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324 y(n) = - SUM c(k+1) y(n-k) + SUM d(k+1) x(n-k) for 1<=n<=length(x)\n\ |
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325 k=1 k=0\n\ |
10840 | 326 @end group\n\ |
3367 | 327 @end smallexample\n\ |
10840 | 328 \n\ |
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329 @end ifnottex\n\ |
3367 | 330 \n\ |
331 @noindent\n\ | |
332 where\n\ | |
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333 @ifnottex\n\ |
3367 | 334 c = a/a(1) and d = b/a(1).\n\ |
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335 @end ifnottex\n\ |
3367 | 336 @tex\n\ |
337 $c = a/a_1$ and $d = b/a_1$.\n\ | |
338 @end tex\n\ | |
339 \n\ | |
340 If the fourth argument @var{si} is provided, it is taken as the\n\ | |
341 initial state of the system and the final state is returned as\n\ | |
342 @var{sf}. The state vector is a column vector whose length is\n\ | |
343 equal to the length of the longest coefficient vector minus one.\n\ | |
344 If @var{si} is not supplied, the initial state vector is set to all\n\ | |
2928 | 345 zeros.\n\ |
346 \n\ | |
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347 In terms of the Z Transform, @var{y} is the result of passing the\n\ |
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348 discrete-time signal @var{x} through a system characterized by the following\n\ |
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349 rational system function:\n\ |
3367 | 350 @tex\n\ |
351 $$\n\ | |
352 H(z) = {\\displaystyle\\sum_{k=0}^M d_{k+1} z^{-k}\n\ | |
353 \\over 1 + \\displaystyle\\sum_{k+1}^N c_{k+1} z^{-k}}\n\ | |
354 $$\n\ | |
355 @end tex\n\ | |
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356 @ifnottex\n\ |
3367 | 357 \n\ |
358 @example\n\ | |
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359 @group\n\ |
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360 M\n\ |
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361 SUM d(k+1) z^(-k)\n\ |
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362 k=0\n\ |
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363 H(z) = ---------------------\n\ |
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364 N\n\ |
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365 1 + SUM c(k+1) z^(-k)\n\ |
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366 k=1\n\ |
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367 @end group\n\ |
3367 | 368 @end example\n\ |
10840 | 369 \n\ |
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370 @end ifnottex\n\ |
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371 @seealso{filter2, fftfilt, freqz}\n\ |
3367 | 372 @end deftypefn") |
2928 | 373 { |
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374 int nargin = args.length (); |
2928 | 375 |
4844 | 376 if (nargin < 3 || nargin > 5) |
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377 print_usage (); |
2928 | 378 |
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379 const char *a_b_errmsg = "filter: A and B must be vectors"; |
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380 const char *x_si_errmsg = "filter: X and SI must be arrays"; |
4844 | 381 |
382 int dim; | |
383 dim_vector x_dims = args(2).dims (); | |
2928 | 384 |
4844 | 385 if (nargin == 5) |
386 { | |
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387 dim = args(4).nint_value () - 1; |
4844 | 388 if (dim < 0 || dim >= x_dims.length ()) |
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389 error ("filter: DIM must be a valid dimension"); |
4844 | 390 } |
391 else | |
392 { | |
393 // Find first non-singleton dimension | |
394 dim = 0; | |
5059 | 395 while (dim < x_dims.length () && x_dims(dim) <= 1) |
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396 dim++; |
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397 |
4844 | 398 // All dimensions singleton, pick first dimension |
399 if (dim == x_dims.length ()) | |
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400 dim = 0; |
4844 | 401 } |
2928 | 402 |
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403 octave_value_list retval; |
20892 | 404 |
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405 bool isfloat = (args(0).is_single_type () |
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406 || args(1).is_single_type () |
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407 || args(2).is_single_type () |
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408 || (nargin >= 4 && args(3).is_single_type ())); |
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409 |
2928 | 410 if (args(0).is_complex_type () |
411 || args(1).is_complex_type () | |
412 || args(2).is_complex_type () | |
4844 | 413 || (nargin >= 4 && args(3).is_complex_type ())) |
2928 | 414 { |
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415 if (isfloat) |
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416 { |
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417 FloatComplexColumnVector b = args(0).xfloat_complex_vector_value (a_b_errmsg); |
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418 FloatComplexColumnVector a = args(1).xfloat_complex_vector_value (a_b_errmsg); |
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419 FloatComplexNDArray x = args(2).xfloat_complex_array_value (x_si_errmsg); |
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420 |
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421 FloatComplexNDArray si; |
3088 | 422 |
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423 if (nargin == 3 || args(3).is_empty ()) |
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424 { |
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425 octave_idx_type a_len = a.numel (); |
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426 octave_idx_type b_len = b.numel (); |
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427 |
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428 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1; |
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429 |
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430 dim_vector si_dims = x.dims (); |
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431 for (int i = dim; i > 0; i--) |
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432 si_dims(i) = si_dims(i-1); |
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433 si_dims(0) = si_len; |
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434 |
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435 si.resize (si_dims, 0.0); |
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436 } |
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437 else |
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438 { |
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439 si = args(3).xfloat_complex_array_value (x_si_errmsg); |
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440 |
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441 if (si.is_vector () && x.is_vector ()) |
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442 si = si.reshape (dim_vector (si.numel (), 1)); |
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443 } |
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444 |
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445 FloatComplexNDArray y (filter (b, a, x, si, dim)); |
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446 |
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447 retval = ovl (y, si); |
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448 } |
2928 | 449 else |
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450 { |
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451 ComplexColumnVector b = args(0).xcomplex_vector_value (a_b_errmsg); |
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452 ComplexColumnVector a = args(1).xcomplex_vector_value (a_b_errmsg); |
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453 |
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454 ComplexNDArray x = args(2).xcomplex_array_value (x_si_errmsg); |
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455 |
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456 ComplexNDArray si; |
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457 |
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458 if (nargin == 3 || args(3).is_empty ()) |
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459 { |
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460 octave_idx_type a_len = a.numel (); |
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461 octave_idx_type b_len = b.numel (); |
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462 |
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463 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1; |
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464 |
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465 dim_vector si_dims = x.dims (); |
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466 for (int i = dim; i > 0; i--) |
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467 si_dims(i) = si_dims(i-1); |
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468 si_dims(0) = si_len; |
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469 |
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470 si.resize (si_dims, 0.0); |
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471 } |
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472 else |
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473 { |
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474 si = args(3).xcomplex_array_value (x_si_errmsg); |
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475 |
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476 if (si.is_vector () && x.is_vector ()) |
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477 si = si.reshape (dim_vector (si.numel (), 1)); |
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478 } |
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479 |
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480 ComplexNDArray y (filter (b, a, x, si, dim)); |
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481 |
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482 retval = ovl (y, si); |
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483 } |
2928 | 484 } |
485 else | |
486 { | |
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487 if (isfloat) |
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488 { |
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489 FloatColumnVector b = args(0).xfloat_vector_value (a_b_errmsg); |
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490 FloatColumnVector a = args(1).xfloat_vector_value (a_b_errmsg); |
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491 |
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492 FloatNDArray x = args(2).xfloat_array_value (x_si_errmsg); |
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493 |
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494 FloatNDArray si; |
3088 | 495 |
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496 if (nargin == 3 || args(3).is_empty ()) |
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497 { |
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498 octave_idx_type a_len = a.numel (); |
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499 octave_idx_type b_len = b.numel (); |
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500 |
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501 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1; |
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502 |
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503 dim_vector si_dims = x.dims (); |
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504 for (int i = dim; i > 0; i--) |
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505 si_dims(i) = si_dims(i-1); |
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506 si_dims(0) = si_len; |
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507 |
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508 si.resize (si_dims, 0.0); |
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509 } |
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510 else |
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511 { |
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512 si = args(3).xfloat_array_value (x_si_errmsg); |
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513 |
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514 if (si.is_vector () && x.is_vector ()) |
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515 si = si.reshape (dim_vector (si.numel (), 1)); |
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516 } |
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517 |
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518 FloatNDArray y (filter (b, a, x, si, dim)); |
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519 |
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520 retval = ovl (y, si); |
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521 } |
2928 | 522 else |
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523 { |
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524 ColumnVector b = args(0).xvector_value (a_b_errmsg); |
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525 ColumnVector a = args(1).xvector_value (a_b_errmsg); |
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526 |
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527 NDArray x = args(2).xarray_value (x_si_errmsg); |
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528 |
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529 NDArray si; |
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530 |
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531 if (nargin == 3 || args(3).is_empty ()) |
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532 { |
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533 octave_idx_type a_len = a.numel (); |
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534 octave_idx_type b_len = b.numel (); |
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535 |
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536 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1; |
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537 |
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538 dim_vector si_dims = x.dims (); |
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539 for (int i = dim; i > 0; i--) |
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540 si_dims(i) = si_dims(i-1); |
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541 si_dims(0) = si_len; |
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542 |
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543 si.resize (si_dims, 0.0); |
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544 } |
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545 else |
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546 { |
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547 si = args(3).xarray_value (x_si_errmsg); |
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548 |
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549 if (si.is_vector () && x.is_vector ()) |
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550 si = si.reshape (dim_vector (si.numel (), 1)); |
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551 } |
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552 |
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553 NDArray y (filter (b, a, x, si, dim)); |
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554 |
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555 retval = ovl (y, si); |
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556 } |
2928 | 557 } |
558 | |
559 return retval; | |
560 } | |
561 | |
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562 template MArray<double> |
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563 filter (MArray<double>&, MArray<double>&, MArray<double>&, |
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564 MArray<double>&, int dim); |
2928 | 565 |
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566 template MArray<double> |
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567 filter (MArray<double>&, MArray<double>&, MArray<double>&, int dim); |
2928 | 568 |
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569 template MArray<Complex> |
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570 filter (MArray<Complex>&, MArray<Complex>&, MArray<Complex>&, |
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571 MArray<Complex>&, int dim); |
2928 | 572 |
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573 template MArray<Complex> |
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574 filter (MArray<Complex>&, MArray<Complex>&, MArray<Complex>&, int dim); |
2928 | 575 |
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576 template MArray<float> |
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577 filter (MArray<float>&, MArray<float>&, MArray<float>&, |
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578 MArray<float>&, int dim); |
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579 |
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580 template MArray<float> |
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581 filter (MArray<float>&, MArray<float>&, MArray<float>&, int dim); |
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582 |
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583 template MArray<FloatComplex> |
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584 filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArray<FloatComplex>&, |
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585 MArray<FloatComplex>&, int dim); |
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586 |
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587 template MArray<FloatComplex> |
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588 filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArray<FloatComplex>&, |
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589 int dim); |
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590 |
2928 | 591 /* |
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592 %!shared a, b, x, r |
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593 %!test |
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594 %! a = [1 1]; |
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595 %! b = [1 1]; |
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596 %! x = zeros (1,10); x(1) = 1; |
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597 %! assert (filter (b, [1], x ), [1 1 0 0 0 0 0 0 0 0]); |
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598 %! assert (filter (b, [1], x.'), [1 1 0 0 0 0 0 0 0 0].'); |
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599 %! assert (filter (b.', [1], x ), [1 1 0 0 0 0 0 0 0 0] ); |
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600 %! assert (filter (b.', [1], x.'), [1 1 0 0 0 0 0 0 0 0].'); |
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601 %! assert (filter ([1], a, x ), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] ); |
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602 %! assert (filter ([1], a, x.'), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].'); |
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603 %! assert (filter ([1], a.', x ), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] ); |
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604 %! assert (filter ([1], a.', x.'), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].'); |
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605 %! assert (filter (b, a, x ), [1 0 0 0 0 0 0 0 0 0] ); |
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606 %! assert (filter (b.', a, x ), [1 0 0 0 0 0 0 0 0 0] ); |
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607 %! assert (filter (b, a.', x ), [1 0 0 0 0 0 0 0 0 0] ); |
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608 %! assert (filter (b.', a, x ), [1 0 0 0 0 0 0 0 0 0] ); |
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609 %! assert (filter (b, a, x.'), [1 0 0 0 0 0 0 0 0 0].'); |
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610 %! assert (filter (b.', a, x.'), [1 0 0 0 0 0 0 0 0 0].'); |
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611 %! assert (filter (b, a.', x.'), [1 0 0 0 0 0 0 0 0 0].'); |
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612 %! assert (filter (b.', a, x.'), [1 0 0 0 0 0 0 0 0 0].'); |
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613 |
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614 %!test |
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615 %! r = sqrt (1/2) * (1+i); |
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616 %! a = a*r; |
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617 %! b = b*r; |
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618 %! assert (filter (b, [1], x ), r*[1 1 0 0 0 0 0 0 0 0] ); |
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619 %! assert (filter (b, [1], r*x ), r*r*[1 1 0 0 0 0 0 0 0 0] ); |
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620 %! assert (filter (b, [1], x.' ), r*[1 1 0 0 0 0 0 0 0 0].' ); |
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621 %! assert (filter (b, a, x ), [1 0 0 0 0 0 0 0 0 0] ); |
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622 %! assert (filter (b, a, r*x ), r*[1 0 0 0 0 0 0 0 0 0] ); |
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623 |
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624 %!shared a, b, x, y, so |
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625 %!test |
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626 %! a = [1,1]; |
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627 %! b = [1,1]; |
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628 %! x = zeros (1,10); x(1) = 1; |
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629 %! [y, so] = filter (b, [1], x, [-1]); |
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630 %! assert (y, [0 1 0 0 0 0 0 0 0 0]); |
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631 %! assert (so, 0); |
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632 |
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633 %!test |
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634 %! x = zeros (10,3); x(1,1) = -1; x(1,2) = 1; |
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635 %! y0 = zeros (10,3); y0(1:2,1) = -1; y0(1:2,2) = 1; |
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636 %! y = filter (b, [1], x); |
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637 %! assert (y, y0); |
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638 |
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639 %!test |
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640 %! a = [1,1]; |
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641 %! b=[1,1]; |
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642 %! x = zeros (4,4,2); x(1,1:4,1) = +1; x(1,1:4,2) = -1; |
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643 %! y0 = zeros (4,4,2); y0(1:2,1:4,1) = +1; y0(1:2,1:4,2) = -1; |
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644 %! y = filter (b, [1], x); |
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645 %! assert (y, y0); |
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646 |
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maint: Use Octave coding conventions for coddling parenthis is DLD-FUNCTIONS directory
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647 %!assert (filter (1, ones (10,1) / 10, []), []) |
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648 %!assert (filter (1, ones (10,1) / 10, zeros (0,10)), zeros (0,10)) |
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649 %!assert (filter (1, ones (10,1) / 10, single (1:5)), repmat (single (10), 1, 5)) |
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650 |
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Merge with stable; recover on default backed-out 9843b3b055e0 from stable
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651 %% Test using initial conditions |
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652 %!assert (filter ([1, 1, 1], [1, 1], [1 2], [1, 1]), [2 2]) |
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653 %!assert (filter ([1, 1, 1], [1, 1], [1 2], [1, 1]'), [2 2]) |
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654 %!assert (filter ([1, 3], [1], [1 2; 3 4; 5 6], [4, 5]), [5 7; 6 10; 14 18]) |
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655 %!error (filter ([1, 3], [1], [1 2; 3 4; 5 6], [4, 5]')) |
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656 %!assert (filter ([1, 3, 2], [1], [1 2; 3 4; 5 6], [1 0 0; 1 0 0], 2), [2 6; 3 13; 5 21]) |
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657 |
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658 ## Test of DIM parameter |
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659 %!test |
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660 %! x = ones (2, 1, 3, 4); |
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661 %! x(1,1,:,:) = [1 2 3 4; 5 6 7 8; 9 10 11 12]; |
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662 %! y0 = [1 1 6 2 15 3 2 1 8 2 18 3 3 1 10 2 21 3 4 1 12 2 24 3]; |
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663 %! y0 = reshape (y0, size (x)); |
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664 %! y = filter ([1 1 1], 1, x, [], 3); |
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665 %! assert (y, y0); |
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666 */ |