Mercurial > octave
view scripts/statistics/zscore.m @ 33567:9f0f7a898b73 bytecode-interpreter tip
maint: Merge default to bytecode-interpreter
author | Arun Giridhar <arungiridhar@gmail.com> |
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date | Fri, 10 May 2024 17:57:29 -0400 |
parents | 2e484f9f1f18 |
children |
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######################################################################## ## ## Copyright (C) 1995-2024 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{z} =} zscore (@var{x}) ## @deftypefnx {} {@var{z} =} zscore (@var{x}, @var{opt}) ## @deftypefnx {} {@var{z} =} zscore (@var{x}, @var{opt}, @var{dim}) ## @deftypefnx {} {[@var{z}, @var{mu}, @var{sigma}] =} zscore (@dots{}) ## Compute the Z score of @var{x}. ## ## If @var{x} is a vector, subtract its mean and divide by its standard ## deviation. If the standard deviation is zero, divide by 1 instead. ## ## The optional parameter @var{opt} determines the normalization to use when ## computing the standard deviation and has the same definition as the ## corresponding parameter for @code{std}. ## ## If @var{x} is a matrix, calculate along the first non-singleton dimension. ## If the third optional argument @var{dim} is given, operate along this ## dimension. ## ## The optional outputs @var{mu} and @var{sigma} contain the mean and standard ## deviation. ## ## @seealso{mean, std, center} ## @end deftypefn function [z, mu, sigma] = zscore (x, opt = 0, dim) if (nargin < 1) print_usage (); endif if (! (isnumeric (x) || islogical (x))) error ("zscore: X must be a numeric vector or matrix"); endif if (isempty (opt)) opt = 0; elseif (! isscalar (opt) || (opt != 0 && opt != 1)) error ("zscore: normalization OPT must be empty, 0, or 1"); 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 ("zscore: DIM must be an integer and a valid dimension"); endif endif n = sz(dim); if (n == 0) z = x; else if (isinteger (x)) x = double (x); endif mu = mean (x, dim); sigma = std (x, opt, dim); s = sigma; s(s==0) = 1; z = (x - mu) ./ s; endif endfunction %!assert (zscore ([1,2,3]), [-1,0,1]) %!assert (zscore (single ([1,2,3])), single ([-1,0,1])) %!assert (zscore (int8 ([1,2,3])), [-1,0,1]) %!assert (zscore (ones (3,2,2,2)), zeros (3,2,2,2)) %!assert (zscore ([2,0,-2;0,2,0;-2,-2,2]), [1,0,-1;0,1,0;-1,-1,1]) %!assert <*54531> (zscore ([1,2,3], [], 2), [-1,0,1]) ## Test input validation %!error <Invalid call> zscore () %!error zscore (1, 2, 3) %!error <X must be a numeric> zscore (['A'; 'B']) %!error <OPT must be empty, 0, or 1> zscore (1, ones (2,2)) %!error <OPT must be empty, 0, or 1> zscore (1, 1.5) %!error <DIM must be an integer> zscore (1, [], ones (2,2)) %!error <DIM must be an integer> zscore (1, [], 1.5) %!error <DIM must be .* a valid dimension> zscore (1, [], 0)