## Copyright (C) 2015 Michael Leitner <michael.leitner@frm2.tum.de>
## Copyright (C) 2012 Rik Wehbring
## Copyright (C) 1995-2016 Kurt Hornik
## Copyright (C) 2023 Andreas Bertsatos <abertsatos@biol.uoa.gr>
##
## This file is part of the statistics package for GNU Octave.
##
## This program 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.
##
## This program 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
## this program; if not, see <http://www.gnu.org/licenses/>.

## -*- texinfo -*-
## @deftypefn  {statistics} {@var{r} =} binornd (@var{n}, @var{ps})
## @deftypefnx {statistics} {@var{r} =} binornd (@var{n}, @var{ps}, @var{rows})
## @deftypefnx {statistics} {@var{r} =} binornd (@var{n}, @var{ps}, @var{rows}, @var{cols}, @dots{})
## @deftypefnx {statistics} {@var{r} =} binornd (@var{n}, @var{ps}, [@var{sz}])
##
## Random arrays from the Binomial distribution.
##
## @code{@var{r} = binornd (@var{n}, @var{ps})} returns a matrix of random
## samples from the binomial distribution with parameters @var{n} and @var{ps},
## where @var{n} is the number of trials and @var{ps} is the probability of
## success.  The size of @var{r} is the common size of @var{n} and @var{ps}.
## A scalar input functions as a constant matrix of the same size as the other
## inputs.
##
## When called with a single size argument, @code{binornd} returns a square
## matrix with the dimension specified.  When called with more than one scalar
## argument, the first two arguments are taken as the number of rows and columns
## and any further arguments specify additional matrix dimensions.  The size may
## also be specified with a row vector of dimensions, @var{sz}.
##
## Further information about the binomial distribution can be found at
## @url{https://en.wikipedia.org/wiki/Binomial_distribution}
##
## @seealso{binocdf, binoinv, binopdf, binofit, binolike, binostat, binotest}
## @end deftypefn

function r = binornd (n, ps, varargin)

  ## Check for valid number of input arguments
  if (nargin < 2)
    error ("binornd: function called with too few input arguments.");
  endif

  ## Check for common size of N and PS
  if (! isscalar (n) || ! isscalar (ps))
    [retval, n, ps] = common_size (n, ps);
    if (retval > 0)
      error ("binornd: N and PS must be of common size or scalars.");
    endif
  endif

  ## Check for N and PS being reals
  if (iscomplex (n) || iscomplex (ps))
    error ("binornd: N and PS must not be complex.");
  endif

  ## Parse and check SIZE arguments
  if (nargin == 2)
    sz = size (n);
  elseif (nargin == 3)
    if (isscalar (varargin{1}) && varargin{1} == fix (varargin{1}))
      sz = [varargin{1}, varargin{1}];
    elseif (isrow (varargin{1}) && all (varargin{1} == fix (varargin{1})))
      sz = varargin{1};
    elseif (isempty (varargin{1}))
      r = [];
      return;
    else
      error (strcat ("binornd: SZ must be a scalar or a row vector", ...
                     " of integers."));
    endif
  elseif (nargin > 3)
    notint = cellfun (@(x) (! isscalar (x) || x != fix (x)), varargin);
    if (any (notint))
      error ("binornd: dimensions must be integers.");
    endif
    sz = [varargin{:}];
  endif

  ## Negative dimensions are treated as zero, as in core Octave and MATLAB
  sz = max (sz, 0);

  ## Check that parameters match requested dimensions in size
  ## Use 'size (ones (sz))' to ignore any trailing singleton dimensions in SZ
  if (! isscalar (n) && ! isequal (size (n), size (ones (sz))))
    error ("binornd: N and PS must be scalars or of size SZ.");
  endif

  ## Check for class type
  if (isa (n, 'single') || isa (ps, 'single'))
    cls = 'single';
  else
    cls = 'double';
  endif

  ## Generate random sample from binomial distribution
  if (isscalar (n) && isscalar (ps))
    if ((n > 0) && (n < Inf) && (n == fix (n)) && (ps >= 0) && (ps <= 1))
      nel = prod (sz);
      tmp = rand (n, nel);
      r = sum (tmp < ps, 1);
      r = reshape (r, sz);
      if (strcmp (cls, 'single'))
        r = single (r);
      endif
    elseif ((n == 0) && (ps >= 0) && (ps <= 1))
      r = zeros (sz, cls);
    else
      r = NaN (sz, cls);
    endif
  else
    r = zeros (sz, cls);

    k = ! (n >= 0) | ! (n < Inf) | ! (n == fix (n)) | ! (ps >= 0) | ! (ps <= 1);
    r(k) = NaN;

    k = (n > 0) & (n < Inf) & (n == fix (n)) & (ps >= 0) & (ps <= 1);
    if (any (k(:)))
      L = sum (k(:));
      ind = repelems ((1 : L), [(1 : L); n(k)(:)'])';
      p_ext = ps(k)(ind)(:);
      r(k) = accumarray (ind, rand (sum (n(k)(:)), 1) < p_ext);
    endif
  endif

endfunction

## Test output
%!assert_equal (size (binornd (2, 1/2)), [1 1])
%!assert_equal (size (binornd (2 * ones (2, 1), 1/2)), [2, 1])
%!assert_equal (size (binornd (2 * ones (2, 2), 1/2)), [2, 2])
%!assert_equal (size (binornd (2, 1/2 * ones (2, 1))), [2, 1])
%!assert_equal (size (binornd (1, 1/2 * ones (2, 2))), [2, 2])
%!assert_equal (size (binornd (ones (2, 1), 1)), [2, 1])
%!assert_equal (size (binornd (ones (2, 2), 1)), [2, 2])
%!assert_equal (size (binornd (2, 1/2, 3)), [3, 3])
%!assert_equal (size (binornd (1, 1, [4, 1])), [4, 1])
%!assert_equal (size (binornd (1, 1, 4, 1)), [4, 1])
%!assert_equal (size (binornd (1, 1, 4, 1, 5)), [4, 1, 5])
%!assert_equal (size (binornd (1, 1, 0, 1)), [0, 1])
%!assert_equal (size (binornd (1, 1, 1, 0)), [1, 0])
%!assert_equal (size (binornd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5])
%!assert_equal (size (binornd (1, 1, [])), [0, 0])
%!assert_equal (size (binornd (1, 1, [2, 0, 2, 1])), [2, 0, 2])
%!assert_equal (size (binornd (1, 1/2, -1)), [0, 0])
%!assert_equal (size (binornd (1, 1/2, [2, -1, 2])), [2, 0, 2])
%!assert_equal (size (binornd (1, 1/2, 2, -1, 5)), [2, 0, 5])

## Test class of input preserved
%!assert_equal (class (binornd (1, 1)), "double")
%!assert_equal (class (binornd (1, single (0))), "single")
%!assert_equal (class (binornd (1, single ([0, 0]))), "single")
%!assert_equal (class (binornd (1, single (1), 2)), "single")
%!assert_equal (class (binornd (1, single ([1, 1]), 1, 2)), "single")
%!assert_equal (class (binornd (single (1), 1, 2)), "single")
%!assert_equal (class (binornd (single ([1, 1]), 1, 1, 2)), "single")

## Test input validation
%!error<binornd: function called with too few input arguments.> binornd ()
%!error<binornd: function called with too few input arguments.> binornd (1)
%!error<binornd: N and PS must be of common size or scalars.> ...
%! binornd (ones (3), ones (2))
%!error<binornd: N and PS must be of common size or scalars.> ...
%! binornd (ones (2), ones (3))
%!error<binornd: N and PS must not be complex.> binornd (i, 2)
%!error<binornd: N and PS must not be complex.> binornd (1, i)
%!error<binornd: SZ must be a scalar or a row vector of integers.> ...
%! binornd (1, 1/2, 1.2)
%!error<binornd: SZ must be a scalar or a row vector of integers.> ...
%! binornd (1, 1/2, ones (2))
%!error<binornd: SZ must be a scalar or a row vector of integers.> ...
%! binornd (1, 1/2, [2 0 2.5])
%!error<binornd: dimensions must be integers.> ...
%! binornd (1, 1/2, 2, 1.5, 5)
%!error<binornd: N and PS must be scalars or of size SZ.> ...
%! binornd (2, 1/2 * ones (2), 3)
%!error<binornd: N and PS must be scalars or of size SZ.> ...
%! binornd (2, 1/2 * ones (2), [3, 2])
%!error<binornd: N and PS must be scalars or of size SZ.> ...
%! binornd (2, 1/2 * ones (2), 3, 2)
%!error<binornd: N and PS must be scalars or of size SZ.> ...
%! binornd (2 * ones (2), 1/2, 3)
%!error<binornd: N and PS must be scalars or of size SZ.> ...
%! binornd (2 * ones (2), 1/2, [3, 2])
%!error<binornd: N and PS must be scalars or of size SZ.> ...
%! binornd (2 * ones (2), 1/2, 3, 2)
