view scripts/statistics/statistics.m @ 30920:47cbc69e66cd

eliminate direct access to call stack from evaluator The call stack is an internal implementation detail of the evaluator. Direct access to it outside of the evlauator should not be needed. * pt-eval.h (tree_evaluator::get_call_stack): Delete.
author John W. Eaton <jwe@octave.org>
date Fri, 08 Apr 2022 15:19:22 -0400
parents 5d3faba0342e
children 597f3ee61a48
line wrap: on
line source

########################################################################
##
## Copyright (C) 1995-2022 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{stats} =} statistics (@var{x})
## @deftypefnx {} {@var{stats} =} statistics (@var{x}, @var{dim})
## Return a vector with the minimum, first quartile, median, third quartile,
## maximum, mean, standard deviation, skewness, and kurtosis of the elements of
## the vector @var{x}.
##
## If @var{x} is a matrix, calculate statistics over the first non-singleton
## dimension.
##
## If the optional argument @var{dim} is given, operate along this dimension.
## @seealso{min, max, median, mean, std, skewness, kurtosis}
## @end deftypefn

function stats = statistics (x, dim)

  if (nargin < 1)
    print_usage ();
  endif

  if (! (isnumeric (x) || islogical (x)))
    error ("statistics: 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))
        || !(1 <= dim && dim <= nd))
      error ("statistics: DIM must be an integer and a valid dimension");
    endif
  endif

  if (sz(dim) < 2)
    error ("statistics: dimension of X is too small (<2)");
  endif

  emp_inv = quantile (x, [0.25; 0.5; 0.75], dim, 7);

  stats = cat (dim, min (x, [], dim), emp_inv, max (x, [], dim), mean (x, dim),
               std (x, [], dim), skewness (x, [], dim), kurtosis (x, [], dim));

endfunction


%!test
%! x = rand (7,5);
%! s = statistics (x);
%! assert (min (x), s(1,:), eps);
%! assert (median (x), s(3,:), eps);
%! assert (max (x), s(5,:), eps);
%! assert (mean (x), s(6,:), eps);
%! assert (std (x), s(7,:), eps);
%! assert (skewness (x), s(8,:), eps);
%! assert (kurtosis (x), s(9,:), eps);

%! x = rand (7,5);
%! s = statistics (x, 2);
%! assert (min (x, [], 2), s(:,1), eps);
%! assert (median (x, 2), s(:,3), eps);
%! assert (max (x, [], 2), s(:,5), eps);
%! assert (mean (x, 2), s(:,6), eps);
%! assert (std (x, [], 2), s(:,7), eps);
%! assert (skewness (x, [], 2), s(:,8), eps);
%! assert (kurtosis (x, [], 2), s(:,9), eps);

## Test input validation
%!error <Invalid call> statistics ()
%!error statistics (['A'; 'B'])
%!error statistics (1, ones (2,2))
%!error statistics (1, 1.5)
%!error statistics (1, 0)
%!error statistics (1, 3)
%!error statistics (1)