Mercurial > octave
view scripts/statistics/mode.m @ 31248:8b75954a4670
delaunayn: adjust node ordering for positive outward normal vectors (bug #53397)
* delaunayn.m: Check sign of simplex volume, flip node order for negative
volumes to ensure positive (outward-pointing) normal vectors. Add BISTs to
check for positive volumes.
* etc/News.8.md: Append function improvement note to delaunayn change
paragraph under General Improvements.
author | Nicholas R. Jankowski <jankowski.nicholas@gmail.com> |
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date | Thu, 29 Sep 2022 23:09:05 -0400 |
parents | 5d3faba0342e |
children | 597f3ee61a48 |
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######################################################################## ## ## Copyright (C) 2007-2022 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{m} =} mode (@var{x}) ## @deftypefnx {} {@var{m} =} mode (@var{x}, @var{dim}) ## @deftypefnx {} {[@var{m}, @var{f}, @var{c}] =} mode (@dots{}) ## Compute the most frequently occurring value in a dataset (mode). ## ## @code{mode} determines the frequency of values along the first non-singleton ## dimension and returns the value with the highest frequency. If two, or ## more, values have the same frequency @code{mode} returns the smallest. ## ## If the optional argument @var{dim} is given, operate along this dimension. ## ## The return variable @var{f} is the number of occurrences of the mode in ## the dataset. ## ## The cell array @var{c} contains all of the elements with the maximum ## frequency. ## @seealso{mean, median} ## @end deftypefn function [m, f, c] = mode (x, dim) if (nargin < 1) print_usage (); endif if (! (isnumeric (x) || islogical (x))) error ("mode: X must be a numeric vector or matrix"); endif nd = ndims (x); sz = size (x); if (nargin < 2) ## Find the first non-singleton dimension. (dim = find (sz > 1, 1)) || (dim = 1); else if (! (isscalar (dim) && dim == fix (dim) && dim > 0)) error ("mode: DIM must be an integer and a valid dimension"); endif endif if (dim > nd) ## Special case of mode over non-existent dimension. m = x; f = ones (size (x)); c = num2cell (x); return; endif sz2 = sz; sz2(dim) = 1; sz3 = ones (1, nd); sz3(dim) = sz(dim); if (issparse (x)) t2 = sparse (sz(1), sz(2)); else t2 = zeros (sz); endif if (dim != 1) perm = [dim, 1:dim-1, dim+1:nd]; t2 = permute (t2, perm); endif xs = sort (x, dim); t = cat (dim, true (sz2), diff (xs, 1, dim) != 0); if (dim != 1) t2(permute (t != 0, perm)) = diff ([find(permute (t, perm))(:); prod(sz)+1]); f = max (ipermute (t2, perm), [], dim); xs = permute (xs, perm); else t2(t) = diff ([find(t)(:); prod(sz)+1]); f = max (t2, [], dim); endif c = cell (sz2); if (issparse (x)) m = sparse (sz2(1), sz2(2)); else m = zeros (sz2, class (x)); endif for i = 1 : prod (sz2) c{i} = xs(t2(:, i) == f(i), i); m(i) = c{i}(1); endfor endfunction %!test %! [m, f, c] = mode (toeplitz (1:5)); %! assert (m, [1,2,2,2,1]); %! assert (f, [1,2,2,2,1]); %! assert (c, {[1;2;3;4;5],[2],[2;3],[2],[1;2;3;4;5]}); %!test %! [m, f, c] = mode (toeplitz (1:5), 2); %! assert (m, [1;2;2;2;1]); %! assert (f, [1;2;2;2;1]); %! assert (c, {[1;2;3;4;5];[2];[2;3];[2];[1;2;3;4;5]}); %!test %! a = sprandn (32, 32, 0.05); %! sp0 = sparse (0); %! [m, f, c] = mode (a); %! [m2, f2, c2] = mode (full (a)); %! assert (m, sparse (m2)); %! assert (f, sparse (f2)); %! c_exp(1:length (a)) = { sp0 }; %! assert (c ,c_exp); %! assert (c2,c_exp); %!assert (mode ([2,3,1,2,3,4],1),[2,3,1,2,3,4]) %!assert (mode ([2,3,1,2,3,4],2),2) %!assert (mode ([2,3,1,2,3,4]),2) %!assert (mode (single ([2,3,1,2,3,4])), single (2)) %!assert (mode (int8 ([2,3,1,2,3,4])), int8 (2)) %!assert (mode ([2;3;1;2;3;4],1),2) %!assert (mode ([2;3;1;2;3;4],2),[2;3;1;2;3;4]) %!assert (mode ([2;3;1;2;3;4]),2) %!test %! x = magic (3); %! [m, f, c] = mode (x, 3); %! assert (m, x); %! assert (f, ones (3,3)); %! assert (c, num2cell (x)); %!shared x %! x(:,:,1) = toeplitz (1:3); %! x(:,:,2) = circshift (toeplitz (1:3), 1); %! x(:,:,3) = circshift (toeplitz (1:3), 2); %!test %! [m, f, c] = mode (x, 1); %! assert (reshape (m, [3, 3]), [1 1 1; 2 2 2; 1 1 1]); %! assert (reshape (f, [3, 3]), [1 1 1; 2 2 2; 1 1 1]); %! c = reshape (c, [3, 3]); %! assert (c{1}, [1; 2; 3]); %! assert (c{2}, 2); %! assert (c{3}, [1; 2; 3]); %!test %! [m, f, c] = mode (x, 2); %! assert (reshape (m, [3, 3]), [1 1 2; 2 1 1; 1 2 1]); %! assert (reshape (f, [3, 3]), [1 1 2; 2 1 1; 1 2 1]); %! c = reshape (c, [3, 3]); %! assert (c{1}, [1; 2; 3]); %! assert (c{2}, 2); %! assert (c{3}, [1; 2; 3]); %!test %! [m, f, c] = mode (x, 3); %! assert (reshape (m, [3, 3]), [1 2 1; 1 2 1; 1 2 1]); %! assert (reshape (f, [3, 3]), [1 2 1; 1 2 1; 1 2 1]); %! c = reshape (c, [3, 3]); %! assert (c{1}, [1; 2; 3]); %! assert (c{2}, [1; 2; 3]); %! assert (c{3}, [1; 2; 3]); ## Test input validation %!error <Invalid call> mode () %!error <X must be a numeric> mode ({1 2 3}) %!error <DIM must be an integer> mode (1, ones (2,2)) %!error <DIM must be an integer> mode (1, 1.5) %!error <DIM must be .* a valid dimension> mode (1, 0)