Mercurial > hg > octave-lyh
annotate scripts/general/accumarray.m @ 13172:25467719730b stable
doc: Quiet Texinfo warning in accumarray.m
* accumarray.m: Use @pxref for cross-reference inside parentheses
author | Rik <octave@nomad.inbox5.com> |
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date | Tue, 20 Sep 2011 12:25:02 -0700 |
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11523 | 1 ## Copyright (C) 2007-2011 David Bateman |
2 ## Copyright (C) 2009-2010 VZLU Prague | |
6770 | 3 ## |
7016 | 4 ## This file is part of Octave. |
6770 | 5 ## |
7016 | 6 ## Octave is free software; you can redistribute it and/or modify it |
7 ## under the terms of the GNU General Public License as published by | |
8 ## the Free Software Foundation; either version 3 of the License, or (at | |
9 ## your option) any later version. | |
10 ## | |
11 ## Octave is distributed in the hope that it will be useful, but | |
12 ## WITHOUT ANY WARRANTY; without even the implied warranty of | |
13 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU | |
14 ## General Public License for more details. | |
6770 | 15 ## |
16 ## You should have received a copy of the GNU General Public License | |
7016 | 17 ## along with Octave; see the file COPYING. If not, see |
18 ## <http://www.gnu.org/licenses/>. | |
6770 | 19 |
20 ## -*- texinfo -*- | |
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21 ## @deftypefn {Function File} {} accumarray (@var{subs}, @var{vals}, @var{sz}, @var{func}, @var{fillval}, @var{issparse}) |
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22 ## @deftypefnx {Function File} {} accumarray (@var{subs}, @var{vals}, @dots{}) |
6770 | 23 ## |
7186 | 24 ## Create an array by accumulating the elements of a vector into the |
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25 ## positions defined by their subscripts. The subscripts are defined by |
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26 ## the rows of the matrix @var{subs} and the values by @var{vals}. Each |
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27 ## row of @var{subs} corresponds to one of the values in @var{vals}. If |
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28 ## @var{vals} is a scalar, it will be used for each of the row of |
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29 ## @var{subs}. |
6770 | 30 ## |
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31 ## The size of the matrix will be determined by the subscripts |
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32 ## themselves. However, if @var{sz} is defined it determines the matrix |
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33 ## size. The length of @var{sz} must correspond to the number of columns |
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34 ## in @var{subs}. |
6770 | 35 ## |
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36 ## The default action of @code{accumarray} is to sum the elements with |
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37 ## the same subscripts. This behavior can be modified by defining the |
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38 ## @var{func} function. This should be a function or function handle |
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39 ## that accepts a column vector and returns a scalar. The result of the |
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40 ## function should not depend on the order of the subscripts. |
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41 ## |
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42 ## The elements of the returned array that have no subscripts associated |
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43 ## with them are set to zero. Defining @var{fillval} to some other |
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44 ## value allows these values to be defined. |
6770 | 45 ## |
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46 ## By default @code{accumarray} returns a full matrix. If |
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47 ## @var{issparse} is logically true, then a sparse matrix is returned |
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48 ## instead. |
6770 | 49 ## |
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50 ## The following @code{accumarray} example constructs a frequency table |
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51 ## that in the first column counts how many occurrences each number in |
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52 ## the second column has, taken from the vector @var{x}. Note the usage |
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53 ## of @code{unique} for assigning to all repeated elements of @var{x} |
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54 ## the same index (@pxref{doc-unique}). |
6770 | 55 ## |
56 ## @example | |
57 ## @group | |
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58 ## x = [91, 92, 90, 92, 90, 89, 91, 89, 90, 100, 100, 100]; |
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59 ## [u, ~, j] = unique (x); |
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60 ## [accumarray(j', 1), u'] |
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61 ## @result{} 2 89 |
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62 ## 3 90 |
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63 ## 2 91 |
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64 ## 2 92 |
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65 ## 3 100 |
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66 ## @end group |
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67 ## @end example |
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68 ## |
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69 ## Another example, where the result is a multidimensional 3D array and |
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70 ## the default value (zero) appears in the output: |
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71 ## |
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72 ## @example |
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73 ## @group |
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74 ## accumarray ([1, 1, 1; |
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75 ## 2, 1, 2; |
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76 ## 2, 3, 2; |
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77 ## 2, 1, 2; |
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78 ## 2, 3, 2], 101:105) |
6770 | 79 ## @result{} ans(:,:,1) = [101, 0, 0; 0, 0, 0] |
80 ## ans(:,:,2) = [0, 0, 0; 206, 0, 208] | |
81 ## @end group | |
82 ## @end example | |
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83 ## |
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84 ## The complexity in the non-sparse case is generally O(M+N), where N is |
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85 ## the number of subscripts and M is the maximum subscript (linearized |
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86 ## in multi-dimensional case). If @var{func} is one of @code{@@sum} |
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87 ## (default), @code{@@max}, @code{@@min} or @code{@@(x) @{x@}}, an |
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88 ## optimized code path is used. Note that for general reduction function |
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89 ## the interpreter overhead can play a major part and it may be more |
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90 ## efficient to do multiple accumarray calls and compute the results in |
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91 ## a vectorized manner. |
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92 ## |
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93 ## @seealso{accumdim, unique} |
6770 | 94 ## @end deftypefn |
95 | |
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96 function A = accumarray (subs, vals, sz = [], func = [], fillval = [], issparse = []) |
6770 | 97 |
98 if (nargin < 2 || nargin > 6) | |
99 print_usage (); | |
100 endif | |
101 | |
7186 | 102 if (iscell (subs)) |
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103 subs = cellfun (@vec, subs, "uniformoutput", false); |
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104 ndims = numel (subs); |
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105 if (ndims == 1) |
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106 subs = subs{1}; |
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107 endif |
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108 else |
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109 ndims = columns (subs); |
6770 | 110 endif |
111 | |
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112 if (isempty (fillval)) |
6770 | 113 fillval = 0; |
114 endif | |
115 | |
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116 if (isempty (issparse)) |
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117 issparse = false; |
6770 | 118 endif |
7186 | 119 |
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120 if (issparse) |
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121 |
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122 ## Sparse case. Avoid linearizing the subscripts, because it could overflow. |
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123 |
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124 if (fillval != 0) |
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125 error ("accumarray: FILLVAL must be zero in the sparse case"); |
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126 endif |
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127 |
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128 ## Ensure subscripts are a two-column matrix. |
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129 if (iscell (subs)) |
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130 subs = [subs{:}]; |
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131 endif |
6770 | 132 |
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133 ## Validate dimensions. |
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134 if (ndims == 1) |
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135 subs(:,2) = 1; |
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136 elseif (ndims != 2) |
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137 error ("accumarray: in the sparse case, needs 1 or 2 subscripts"); |
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138 endif |
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139 |
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140 if (isnumeric (vals) || islogical (vals)) |
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141 vals = double (vals); |
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142 else |
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143 error ("accumarray: in the sparse case, values must be numeric or logical"); |
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144 endif |
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145 |
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146 if (! (isempty (func) || func == @sum)) |
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147 |
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148 ## Reduce values. This is not needed if we're about to sum them, because |
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149 ## "sparse" can do that. |
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150 |
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151 ## Sort indices. |
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152 [subs, idx] = sortrows (subs); |
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153 n = rows (subs); |
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154 ## Identify runs. |
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155 jdx = find (any (diff (subs, 1, 1), 2)); |
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156 jdx = [jdx; n]; |
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157 |
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158 vals = cellfun (func, mat2cell (vals(:)(idx), diff ([0; jdx]))); |
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159 subs = subs(jdx, :); |
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160 mode = "unique"; |
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161 else |
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162 mode = "sum"; |
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163 endif |
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164 |
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165 ## Form the sparse matrix. |
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166 if (isempty (sz)) |
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167 A = sparse (subs(:,1), subs(:,2), vals, mode); |
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168 elseif (length (sz) == 2) |
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169 A = sparse (subs(:,1), subs(:,2), vals, sz(1), sz(2), mode); |
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170 else |
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171 error ("accumarray: dimensions mismatch"); |
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172 endif |
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173 |
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174 else |
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175 |
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176 ## Linearize subscripts. |
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177 if (ndims > 1) |
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178 if (isempty (sz)) |
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179 if (iscell (subs)) |
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180 sz = cellfun (@max, subs); |
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181 else |
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182 sz = max (subs, [], 1); |
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183 endif |
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184 elseif (ndims != length (sz)) |
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185 error ("accumarray: dimensions mismatch"); |
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186 endif |
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187 |
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188 ## Convert multidimensional subscripts. |
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189 if (ismatrix (subs)) |
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190 subs = num2cell (subs, 1); |
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191 endif |
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192 subs = sub2ind (sz, subs{:}); # creates index cache |
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193 elseif (! isempty (sz) && length (sz) < 2) |
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194 error ("accumarray: needs at least 2 dimensions"); |
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195 elseif (! isindex (subs)) # creates index cache |
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196 error ("accumarray: indices must be positive integers"); |
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197 endif |
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198 |
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199 |
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200 ## Some built-in reductions handled efficiently. |
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201 |
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202 if (isempty (func) || func == @sum) |
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203 ## Fast summation. |
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204 if (isempty (sz)) |
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205 A = __accumarray_sum__ (subs, vals); |
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206 else |
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207 A = __accumarray_sum__ (subs, vals, prod (sz)); |
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208 ## set proper shape. |
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209 A = reshape (A, sz); |
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210 endif |
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211 |
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212 ## we fill in nonzero fill value. |
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213 if (fillval != 0) |
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214 mask = true (size (A)); |
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215 mask(subs) = false; |
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216 A(mask) = fillval; |
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217 endif |
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218 elseif (func == @max) |
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219 ## Fast maximization. |
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220 |
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221 if (isinteger (vals)) |
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222 zero = intmin (class (vals)); |
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223 elseif (islogical (vals)) |
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224 zero = false; |
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225 elseif (fillval == 0 && all (vals(:) >= 0)) |
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226 ## This is a common case - fillval is zero, all numbers nonegative. |
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227 zero = 0; |
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228 else |
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229 zero = NaN; # Neutral value. |
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230 endif |
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231 |
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232 if (isempty (sz)) |
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233 A = __accumarray_max__ (subs, vals, zero); |
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234 else |
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235 A = __accumarray_max__ (subs, vals, zero, prod (sz)); |
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236 A = reshape (A, sz); |
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237 endif |
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238 |
10775 | 239 if (fillval != zero && ! (isnan (fillval) || isnan (zero))) |
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240 mask = true (size (A)); |
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241 mask(subs) = false; |
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242 A(mask) = fillval; |
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243 endif |
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244 elseif (func == @min) |
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245 ## Fast minimization. |
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246 |
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247 if (isinteger (vals)) |
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248 zero = intmax (class (vals)); |
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249 elseif (islogical (vals)) |
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250 zero = true; |
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251 else |
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252 zero = NaN; # Neutral value. |
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253 endif |
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254 |
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255 if (isempty (sz)) |
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256 A = __accumarray_min__ (subs, vals, zero); |
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257 else |
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258 A = __accumarray_min__ (subs, vals, zero, prod (sz)); |
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259 A = reshape (A, sz); |
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260 endif |
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261 |
10775 | 262 if (fillval != zero && ! (isnan (fillval) || isnan (zero))) |
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263 mask = true (size (A)); |
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264 mask(subs) = false; |
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265 A(mask) = fillval; |
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266 endif |
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267 else |
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268 |
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269 ## The general case. Reduce values. |
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270 n = rows (subs); |
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271 if (numel (vals) == 1) |
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272 vals = vals(ones (1, n), 1); |
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273 else |
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274 vals = vals(:); |
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275 endif |
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276 |
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277 ## Sort indices. |
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278 [subs, idx] = sort (subs); |
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279 ## Identify runs. |
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280 jdx = find (subs(1:n-1) != subs(2:n)); |
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281 jdx = [jdx; n]; |
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282 vals = mat2cell (vals(idx), diff ([0; jdx])); |
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283 ## Optimize the case when function is @(x) {x}, i.e. we just want to |
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284 ## collect the values to cells. |
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285 persistent simple_cell_str = func2str (@(x) {x}); |
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286 if (! strcmp (func2str (func), simple_cell_str)) |
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287 vals = cellfun (func, vals); |
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288 endif |
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289 subs = subs(jdx); |
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290 |
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291 ## Construct matrix of fillvals. |
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292 if (iscell (vals)) |
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293 A = cell (sz); |
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294 elseif (fillval == 0) |
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295 A = zeros (sz, class (vals)); |
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296 else |
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297 A = repmat (fillval, sz); |
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298 endif |
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299 |
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300 ## Set the reduced values. |
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301 A(subs) = vals; |
6770 | 302 endif |
303 endif | |
304 endfunction | |
305 | |
306 %!error (accumarray (1:5)) | |
307 %!error (accumarray ([1,2,3],1:2)) | |
308 %!assert (accumarray ([1;2;4;2;4],101:105), [101;206;0;208]) | |
309 %!assert (accumarray ([1,1,1;2,1,2;2,3,2;2,1,2;2,3,2],101:105),cat(3, [101,0,0;0,0,0],[0,0,0;206,0,208])) | |
310 %!assert (accumarray ([1,1,1;2,1,2;2,3,2;2,1,2;2,3,2],101:105,[],@(x)sin(sum(x))),sin(cat(3, [101,0,0;0,0,0],[0,0,0;206,0,208]))) | |
311 %!assert (accumarray ({[1 3 3 2 3 1 2 2 3 3 1 2],[3 4 2 1 4 3 4 2 2 4 3 4],[1 1 2 2 1 1 2 1 1 1 2 2]},101:112),cat(3,[0,0,207,0;0,108,0,0;0,109,0,317],[0,0,111,0;104,0,0,219;0,103,0,0])) | |
312 %!assert (accumarray ([1,1;2,1;2,3;2,1;2,3],101:105,[2,4],@max,NaN),[101,NaN,NaN,NaN;104,NaN,105,NaN]) | |
313 %!assert (accumarray ([1 1; 2 1; 2 3; 2 1; 2 3],101:105,[2 4],@prod,0,true),sparse([1,2,2],[1,1,3],[101,10608,10815],2,4)) | |
314 %!assert (accumarray ([1 1; 2 1; 2 3; 2 1; 2 3],1,[2,4]), [1,0,0,0;2,0,2,0]) | |
315 %!assert (accumarray ([1 1; 2 1; 2 3; 2 1; 2 3],101:105,[2,4],@(x)length(x)>1),[false,false,false,false;true,false,true,false]) | |
316 %!test | |
317 %! A = accumarray ([1 1; 2 1; 2 3; 2 1; 2 3],101:105,[2,4],@(x){x}); | |
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318 %! assert (A{2},[102;104]) |
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319 %!test |
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320 %! subs = ceil (rand (2000, 3)*10); |
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321 %! vals = rand (2000, 1); |
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322 %! assert (accumarray (subs, vals, [], @max), accumarray (subs, vals, [], @(x) max (x))); |
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323 %!test |
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324 %! subs = ceil (rand (2000, 1)*100); |
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325 %! vals = rand (2000, 1); |
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326 %! assert (accumarray (subs, vals, [100, 1], @min, NaN), accumarray (subs, vals, [100, 1], @(x) min (x), NaN)); |
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327 %!test |
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328 %! subs = ceil (rand (2000, 2)*30); |
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329 %! subsc = num2cell (subs, 1); |
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330 %! vals = rand (2000, 1); |
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331 %! assert (accumarray (subsc, vals, [], [], 0, true), accumarray (subs, vals, [], [], 0, true)); |
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332 %!test |
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333 %! subs = ceil (rand (2000, 3)*10); |
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334 %! subsc = num2cell (subs, 1); |
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335 %! vals = rand (2000, 1); |
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336 %! assert (accumarray (subsc, vals, [], @max), accumarray (subs, vals, [], @max)); |
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337 |
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338 |