Mercurial > octave
view scripts/statistics/histc.m @ 30564:796f54d4ddbf stable
update Octave Project Developers copyright for the new year
In files that have the "Octave Project Developers" copyright notice,
update for 2021.
In all .txi and .texi files except gpl.txi and gpl.texi in the
doc/liboctave and doc/interpreter directories, change the copyright
to "Octave Project Developers", the same as used for other source
files. Update copyright notices for 2022 (not done since 2019). For
gpl.txi and gpl.texi, change the copyright notice to be "Free Software
Foundation, Inc." and leave the date at 2007 only because this file
only contains the text of the GPL, not anything created by the Octave
Project Developers.
Add Paul Thomas to contributors.in.
author | John W. Eaton <jwe@octave.org> |
---|---|
date | Tue, 28 Dec 2021 18:22:40 -0500 |
parents | 7854d5752dd2 |
children | 597f3ee61a48 |
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######################################################################## ## ## Copyright (C) 2009-2022 The Octave Project Developers ## ## See the file COPYRIGHT.md in the top-level directory of this ## distribution or <https://octave.org/copyright/>. ## ## This file is part of Octave. ## ## Octave is free software: you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation, either version 3 of the License, or ## (at your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ## GNU General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <https://www.gnu.org/licenses/>. ## ######################################################################## ## -*- texinfo -*- ## @deftypefn {} {@var{n} =} histc (@var{x}, @var{edges}) ## @deftypefnx {} {@var{n} =} histc (@var{x}, @var{edges}, @var{dim}) ## @deftypefnx {} {[@var{n}, @var{idx}] =} histc (@dots{}) ## Compute histogram counts. ## ## When @var{x} is a vector, the function counts the number of elements of ## @var{x} that fall in the histogram bins defined by @var{edges}. This ## must be a vector of monotonically increasing values that define the edges ## of the histogram bins. ## @tex ## $n(k)$ ## @end tex ## @ifnottex ## @code{@var{n}(k)} ## @end ifnottex ## contains the number of elements in @var{x} for which ## @tex ## $@var{edges}(k) <= @var{x} < @var{edges}(k+1)$. ## @end tex ## @ifnottex ## @code{@var{edges}(k) <= @var{x} < @var{edges}(k+1)}. ## @end ifnottex ## The final element of @var{n} contains the number of elements of @var{x} ## exactly equal to the last element of @var{edges}. ## ## When @var{x} is an @math{N}-dimensional array, the computation is carried ## out along dimension @var{dim}. If not specified @var{dim} defaults to the ## first non-singleton dimension. ## ## When a second output argument is requested an index matrix is also returned. ## The @var{idx} matrix has the same size as @var{x}. Each element of ## @var{idx} contains the index of the histogram bin in which the ## corresponding element of @var{x} was counted. ## @seealso{hist} ## @end deftypefn function [n, idx] = histc (x, edges, dim) if (nargin < 2) print_usage (); endif if (! isreal (x)) error ("histc: X argument must be real-valued, not complex"); endif num_edges = numel (edges); if (num_edges == 0) warning ("histc: empty EDGES specified\n"); n = idx = []; return; endif if (! isreal (edges)) error ("histc: EDGES must be real-valued, not complex"); else ## Make sure 'edges' is sorted edges = edges(:); if (! issorted (edges) || edges(1) > edges(end)) warning ("histc: edge values not sorted on input"); edges = sort (edges); endif endif nd = ndims (x); sz = size (x); if (nargin < 3) ## Find the first non-singleton dimension. (dim = find (sz > 1, 1)) || (dim = 1); else if (!(isscalar (dim) && dim == fix (dim)) || !(1 <= dim && dim <= nd)) error ("histc: DIM must be an integer and a valid dimension"); endif endif nsz = sz; nsz(dim) = num_edges; ## the splitting point is 3 bins if (num_edges <= 3) ## This is the O(M*N) algorithm. ## Allocate the histogram n = zeros (nsz); ## Allocate 'idx' if (nargout > 1) idx = zeros (sz); endif ## Prepare indices idx1 = cell (1, dim-1); for k = 1:length (idx1) idx1{k} = 1:sz(k); endfor idx2 = cell (length (sz) - dim); for k = 1:length (idx2) idx2{k} = 1:sz(k+dim); endfor ## Compute the histograms for k = 1:num_edges-1 b = (edges(k) <= x & x < edges(k+1)); n(idx1{:}, k, idx2{:}) = sum (b, dim); if (nargout > 1) idx(b) = k; endif endfor b = (x == edges(end)); n(idx1{:}, num_edges, idx2{:}) = sum (b, dim); if (nargout > 1) idx(b) = num_edges; endif else ## This is the O(M*log(N) + N) algorithm. ## Look-up indices. idx = lookup (edges, x); ## Zero invalid ones (including NaNs). x < edges(1) are already zero. idx(! (x <= edges(end))) = 0; iidx = idx; ## In case of matrix input, we adjust the indices. if (! isvector (x)) nl = prod (sz(1:dim-1)); nn = sz(dim); nu = prod (sz(dim+1:end)); if (nl != 1) iidx = (iidx-1) * nl; iidx += reshape (kron (ones (1, nn*nu), 1:nl), sz); endif if (nu != 1) ne =length (edges); iidx += reshape (kron (nl*ne*(0:nu-1), ones (1, nl*nn)), sz); endif endif ## Select valid elements. iidx = iidx(idx != 0); ## Call accumarray to sum the indexed elements. n = accumarray (iidx(:), 1, nsz); endif endfunction %!test %! x = linspace (0, 10, 1001); %! n = histc (x, 0:10); %! assert (n, [repmat(100, 1, 10), 1]); %!test %! x = repmat (linspace (0, 10, 1001), [2, 1, 3]); %! n = histc (x, 0:10, 2); %! assert (n, repmat ([repmat(100, 1, 10), 1], [2, 1, 3])); ## Test input validation %!error <Invalid call> histc () %!error <Invalid call> histc (1) %!error histc ([1:10 1+i], 2) %!warning <empty EDGES specified> histc (1:10, []); %!error histc (1, 1, 3)