X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?p=CreaPhase.git;a=blobdiff_plain;f=octave_packages%2Fm%2Fplot%2Fhist.m;fp=octave_packages%2Fm%2Fplot%2Fhist.m;h=8c9114f0aa80865d7fe9df329b168a759ee3cab5;hp=0000000000000000000000000000000000000000;hb=1c0469ada9531828709108a4882a751d2816994a;hpb=63de9f36673d49121015e3695f2c336ea92bc278 diff --git a/octave_packages/m/plot/hist.m b/octave_packages/m/plot/hist.m new file mode 100644 index 0000000..8c9114f --- /dev/null +++ b/octave_packages/m/plot/hist.m @@ -0,0 +1,197 @@ +## Copyright (C) 1994-2012 John W. Eaton +## +## 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 +## . + +## -*- texinfo -*- +## @deftypefn {Function File} {} hist (@var{y}) +## @deftypefnx {Function File} {} hist (@var{y}, @var{x}) +## @deftypefnx {Function File} {} hist (@var{y}, @var{nbins}) +## @deftypefnx {Function File} {} hist (@var{y}, @var{x}, @var{norm}) +## @deftypefnx {Function File} {[@var{nn}, @var{xx}] =} hist (@dots{}) +## @deftypefnx {Function File} {[@dots{}] =} hist (@dots{}, @var{prop}, @var{val}) +## +## Produce histogram counts or plots. +## +## With one vector input argument, @var{y}, plot a histogram of the values +## with 10 bins. The range of the histogram bins is determined by the +## range of the data. With one matrix input argument, @var{y}, plot a +## histogram where each bin contains a bar per input column. +## +## Given a second vector argument, @var{x}, use that as the centers of +## the bins, with the width of the bins determined from the adjacent +## values in the vector. +## +## If scalar, the second argument, @var{nbins}, defines the number of bins. +## +## If a third argument is provided, the histogram is normalized such that +## the sum of the bars is equal to @var{norm}. +## +## Extreme values are lumped in the first and last bins. +## +## With two output arguments, produce the values @var{nn} and @var{xx} such +## that @code{bar (@var{xx}, @var{nn})} will plot the histogram. +## +## The histogram's appearance may be modified by specifying property/value +## pairs, @var{prop} and @var{val} pairs. For example the face and edge +## color may be modified. +## +## @example +## @group +## hist (randn (1, 100), 25, "facecolor", "r", "edgecolor", "b"); +## @end group +## @end example +## +## @noindent +## The histograms colors also depend upon the colormap. +## +## @example +## @group +## hist (rand (10, 3)); +## colormap (summer ()); +## @end group +## @end example +## +## @seealso{bar} +## @end deftypefn + +## Author: jwe + +function [nn, xx] = hist (y, varargin) + + if (nargin < 1) + print_usage (); + endif + + arg_is_vector = isvector (y); + + if (rows (y) == 1) + y = y(:); + endif + + if (isreal (y)) + max_val = max (y(:)); + min_val = min (y(:)); + else + error ("hist: first argument must be real valued"); + endif + + iarg = 1; + if (nargin == 1 || ischar (varargin{iarg})) + n = 10; + x = [0.5:n]'/n; + x = x * (max_val - min_val) + ones(size(x)) * min_val; + else + ## nargin is either 2 or 3 + x = varargin{iarg++}; + if (isscalar (x)) + n = x; + if (n <= 0) + error ("hist: number of bins must be positive"); + endif + x = [0.5:n]'/n; + x = x * (max_val - min_val) + ones (size (x)) * min_val; + elseif (isreal (x)) + if (isvector (x)) + x = x(:); + endif + tmp = sort (x); + if (any (tmp != x)) + warning ("hist: bin values not sorted on input"); + x = tmp; + endif + else + error ("hist: second argument must be a scalar or a vector"); + endif + endif + + ## Avoid issues with integer types for x and y + x = double (x); + y = double (y); + + cutoff = (x(1:end-1,:) + x(2:end,:)) / 2; + n = rows (x); + y_nc = columns (y); + if (n < 30 && columns (x) == 1) + ## The following algorithm works fastest for n less than about 30. + chist = zeros (n+1, y_nc); + for i = 1:n-1 + chist(i+1,:) = sum (y <= cutoff(i)); + endfor + chist(n+1,:) = sum (! isnan (y)); + else + ## The following algorithm works fastest for n greater than about 30. + ## Put cutoff elements between boundaries, integrate over all + ## elements, keep totals at boundaries. + [s, idx] = sort ([y; repmat(cutoff, 1, y_nc)]); + len = rows (y); + chist = cumsum (idx <= len); + chist = [(zeros (1, y_nc)); + (reshape (chist(idx > len), rows (cutoff), y_nc)); + (chist(end,:) - sum (isnan (y)))]; + endif + + freq = diff (chist); + + if (nargin > 2 && ! ischar (varargin{iarg})) + ## Normalise the histogram. + norm = varargin{iarg++}; + freq = freq / rows (y) * norm; + endif + + if (nargout > 0) + if (arg_is_vector) + nn = freq'; + xx = x'; + else + nn = freq; + xx = x; + endif + elseif (size (freq, 2) != 1) + bar (x, freq, 0.8, varargin{iarg:end}); + else + bar (x, freq, 1.0, varargin{iarg:end}); + endif + +endfunction + +%!test +%! [nn,xx]=hist([1:4],3); +%! assert(xx, [1.5,2.5,3.5]); +%! assert(nn, [2,1,1]); +%!test +%! [nn,xx]=hist([1:4]',3); +%! assert(xx, [1.5,2.5,3.5]); +%! assert(nn, [2,1,1]); +%!test +%! [nn,xx]=hist([1 1 1 NaN NaN NaN 2 2 3],[1 2 3]); +%! assert(xx, [1,2,3]); +%! assert(nn, [3,2,1]); +%!test +%! [nn,xx]=hist([[1:4]',[1:4]'],3); +%! assert(xx, [1.5;2.5;3.5]); +%! assert(nn, [[2,1,1]',[2,1,1]']); +%!assert(hist(1,1),1); +%!test +%! for n = [10, 30, 100, 1000] +%! assert(sum(hist([1:n], n)), n); +%! assert(sum(hist([1:n], [2:n-1])), n); +%! assert(sum(hist([1:n], [1:n])), n); +%! assert(sum(hist([1:n], 29)), n); +%! assert(sum(hist([1:n], 30)), n); +%! endfor +%!test +%! assert (size (hist(randn(750,240), 200)), [200,240]);