## Copyright (C) 2012 Rik Wehbring
## Copyright (C) 1997-2016 Kurt Hornik
## Copyright (C) 2022 Nicholas R. Jankowski
## 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{p} =} hygecdf (@var{x}, @var{m}, @var{k}, @var{n})
## @deftypefnx {statistics} {@var{p} =} hygecdf (@var{x}, @var{m}, @var{k}, @var{n}, @qcode{'upper'})
##
## Hypergeometric cumulative distribution function (CDF).
##
## For each element of @var{x}, compute the cumulative distribution function
## (CDF) of the hypergeometric distribution with parameters @var{m}, @var{k},
## and @var{n}.  The size of @var{p} is the common size of @var{x}, @var{m},
## @var{k}, and @var{n}.  A scalar input functions as a constant matrix of the
## same size as the other inputs.
##
## This is the cumulative probability of obtaining not more than @var{x} marked
## items when randomly drawing a sample of size @var{n} without replacement from
## a population of total size @var{m} containing @var{k} marked items. The
## parameters @var{m}, @var{k}, and @var{n} must be positive integers with
## @var{k} and @var{n} not greater than @var{m}.
##
## @code{[@dots{}] = hygecdf (@var{x}, @var{m}, @var{k}, @var{n}, "upper")}
## computes the upper tail probability of the hypergeometric distribution with
## parameters @var{m}, @var{k}, and @var{n}, at the values in @var{x}.
##
## Further information about the hypergeometric distribution can be found at
## @url{https://en.wikipedia.org/wiki/Hypergeometric_distribution}
##
## Input arguments must be @qcode{double}, @qcode{single}, or an integer type;
## logical and character arrays are rejected.  Integer input is promoted to
## @qcode{double}, so the result is always a probability.  MATLAB is
## inconsistent here: for several of the discrete distributions it returns the
## result in the integer class of the input, truncating a probability to
## @math{0} or @math{1}.
##
## @seealso{hygeinv, hygepdf, hygernd, hygestat}
## @end deftypefn

function p = hygecdf (x, m, k, n, uflag)

  ## Check for valid number of input arguments
  if (nargin < 4)
    error ("hygecdf: function called with too few input arguments.");
  endif

  ## Check for common size of X, T, M, and N
  if (! isscalar (x) || ! isscalar (m) || ! isscalar (k) || ! isscalar (n))
    [retval, x, m, k, n] = common_size (x, m, k, n);
    if (retval > 0)
      error ("hygecdf: X, T, M, and N must be of common size or scalars.");
    endif
  endif

  ## Check for X, T, M, and N being double, single, or integer
  if (! (isnumeric (x) && isnumeric (m) && isnumeric (k) && isnumeric (n)))
    error ("hygecdf: X, T, M, and N must be double, single, or integer.");
  endif

  ## Integer input is promoted to double, so the result is a probability
  ## rather than a value truncated to the input's integer type.
  if (isinteger (x))
    x = double (x);
  endif
  if (isinteger (m))
    m = double (m);
  endif
  if (isinteger (k))
    k = double (k);
  endif
  if (isinteger (n))
    n = double (n);
  endif

  ## Check for X, T, M, and N being reals
  if (iscomplex (x) || iscomplex (m) || iscomplex (k) || iscomplex (n))
    error ("hygecdf: X, T, M, and N must not be complex.");
  endif

  ## Check for class type
  if (isa (x, 'single') || isa (m, 'single')
                        || isa (k, 'single') || isa (n, 'single'))
    p = zeros (size (x), 'single');
  else
    p = zeros (size (x));
  endif

  ## Check for "upper" flag
  if (nargin > 4 && strcmpi (uflag, 'upper'))
    x = n - floor (x) - 1;
    k = m - k;
  elseif (nargin > 4 && ! strcmpi (uflag, 'upper'))
    error ("hygecdf: invalid argument for upper tail.");
  endif

  ## Force 1 where required
  is_1 = (x >= n | x >= k);
  p(is_1) = 1;

  ## Force NaNs where required
  is_nan = (isnan (x) | isnan (m) | isnan (k) | isnan (n) | ...
            m < 0 | k < 0 | n < 0 | round (m) != m | round (k) != k | ...
            round (n) != n | n > m | k > m);
  p(is_nan) = NaN;

  ## Get values for which P = 0
  is_0 = (m - k - n + x + 1 <= 0 | x < 0);

  ok = ! (is_1 | is_nan | is_0);

  ## Compute hypergeometric CDF
  if (any (ok(:)))
    ## For improved accuracy, compute the upper tail 1-p instead
    ## of the lower tail pfor x values that are larger than the mean
    lo = (x <= k .* n ./ m);
    ok_lo = ok & lo;
    if (any (ok_lo(:)))
      p(ok_lo) = localPDF (floor (x(ok_lo)), m(ok_lo), k(ok_lo), n(ok_lo));
    endif
    ok_hi = ok & ! lo;
    if (any (ok_hi(:)))
      p(ok_hi) = 1 - localPDF (n(ok_hi) - floor (x(ok_hi)) - 1, ...
                               m(ok_hi), m(ok_hi) - k(ok_hi), n(ok_hi));
    endif
  endif

endfunction

function p = localPDF (x, m, k, n)
  HPDF = hygepdf (x, m, k, n);

  ## Compute hygecdf(x,m,k,n)/hygepdf(x,m,k,n) with a series
  ## whose terms can be computed recursively, backwards.
  xmax = max (x(:));
  ybig = repmat ((0:xmax)', 1, length (x));
  xbig = repmat (x(:)', xmax + 1, 1);
  mbig = repmat (m(:)', xmax + 1, 1);
  kbig = repmat (k(:)', xmax + 1, 1);
  nbig = repmat (n(:)', xmax + 1, 1);

  terms = ((ybig+1) .* (mbig-kbig-nbig+ybig+1)) ./ ((nbig-ybig) .* (kbig-ybig));
  terms(ybig >= xbig) = 1;
  terms = flip (cumprod (flip (terms)));

  terms(ybig > xbig) = 0;
  ratio = sum (terms,1);
  ratio = reshape (ratio,size (x));
  p = ratio.*HPDF;
  ## Correct round-off errors
  p(p > 1) = 1;
endfunction

%!demo
%! ## Plot various CDFs from the hypergeometric distribution
%! x = 0:60;
%! p1 = hygecdf (x, 500, 50, 100);
%! p2 = hygecdf (x, 500, 60, 200);
%! p3 = hygecdf (x, 500, 70, 300);
%! plot (x, p1, '*b', x, p2, '*g', x, p3, '*r')
%! grid on
%! xlim ([0, 60])
%! legend ({'m = 500, k = 50, n = 100', 'm = 500, k = 60, n = 200', ...
%!          'm = 500, k = 70, n = 300'}, 'location', 'southeast')
%! title ('Hypergeometric CDF')
%! xlabel ('values in x (number of successes)')
%! ylabel ('probability')

## Test output
%!shared x, y
%! x = [-1 0 1 2 3];
%! y = [0 1/6 5/6 1 1];
%!assert_equal (hygecdf (x, 4*ones (1,5), 2, 2), y, 5*eps)
%!assert_equal (hygecdf (x, 4, 2*ones (1,5), 2), y, 5*eps)
%!assert_equal (hygecdf (x, 4, 2, 2*ones (1,5)), y, 5*eps)
%!assert_equal (hygecdf (x, 4*[1 -1 NaN 1.1 1], 2, 2), [y(1) NaN NaN NaN y(5)], 5*eps)
%!assert_equal (hygecdf (x, 4*[1 -1 NaN 1.1 1], 2, 2, 'upper'), ...
%! [y(5) NaN NaN NaN y(1)], 5*eps)
%!assert_equal (hygecdf (x, 4, 2*[1 -1 NaN 1.1 1], 2), [y(1) NaN NaN NaN y(5)], 5*eps)
%!assert_equal (hygecdf (x, 4, 2*[1 -1 NaN 1.1 1], 2, 'upper'), ...
%! [y(5) NaN NaN NaN y(1)], 5*eps)
%!assert_equal (hygecdf (x, 4, 5, 2), [NaN NaN NaN NaN NaN])
%!assert_equal (hygecdf (x, 4, 2, 2*[1 -1 NaN 1.1 1]), [y(1) NaN NaN NaN y(5)], 5*eps)
%!assert_equal (hygecdf (x, 4, 2, 2*[1 -1 NaN 1.1 1], 'upper'), ...
%! [y(5) NaN NaN NaN y(1)], 5*eps)
%!assert_equal (hygecdf (x, 4, 2, 5), [NaN NaN NaN NaN NaN])
%!assert_equal (hygecdf ([x(1:2) NaN x(4:5)], 4, 2, 2), [y(1:2) NaN y(4:5)], 5*eps)
%!test
%! p = hygecdf (x, 10, [1 2 3 4 5], 2, 'upper');
%! assert_equal (p, [1, 34/90, 2/30, 0, 0], 10*eps);
%!test
%! p = hygecdf (2*x, 10, [1 2 3 4 5], 2, 'upper');
%! assert_equal (p, [1, 34/90, 0, 0, 0], 10*eps);

## Test class of input preserved
%!assert_equal (hygecdf ([x, NaN], 4, 2, 2), [y, NaN], 5*eps)
%!assert_equal (hygecdf (single ([x, NaN]), 4, 2, 2), single ([y, NaN]), ...
%! eps ('single'))
%!assert_equal (hygecdf ([x, NaN], single (4), 2, 2), single ([y, NaN]), ...
%! eps ('single'))
%!assert_equal (hygecdf ([x, NaN], 4, single (2), 2), single ([y, NaN]), ...
%! eps ('single'))
%!assert_equal (hygecdf ([x, NaN], 4, 2, single (2)), single ([y, NaN]), ...
%! eps ('single'))

## Test input validation
%!error<hygecdf: function called with too few input arguments.> hygecdf ()
%!error<hygecdf: function called with too few input arguments.> hygecdf (1)
%!error<hygecdf: function called with too few input arguments.> hygecdf (1,2)
%!error<hygecdf: function called with too few input arguments.> hygecdf (1,2,3)
%!error<hygecdf: invalid argument for upper tail.> hygecdf (1,2,3,4,5)
%!error<hygecdf: invalid argument for upper tail.> hygecdf (1,2,3,4,'uper')
%!error<hygecdf: X, T, M, and N must be of common size or scalars.> ...
%! hygecdf (ones (2), ones (3), 1, 1)
%!error<hygecdf: X, T, M, and N must be of common size or scalars.> ...
%! hygecdf (1, ones (2), ones (3), 1)
%!error<hygecdf: X, T, M, and N must be of common size or scalars.> ...
%! hygecdf (1, 1, ones (2), ones (3))
%!error<hygecdf: X, T, M, and N must be double, single, or integer.> hygecdf (true, 2, 2, 2)
%!error<hygecdf: X, T, M, and N must be double, single, or integer.> hygecdf ('a', 2, 2, 2)
%!assert_equal (class (hygecdf (int32 (2), 2, 2, 2)), 'double')
%!error<hygecdf: X, T, M, and N must not be complex.> hygecdf (i, 2, 2, 2)
%!error<hygecdf: X, T, M, and N must not be complex.> hygecdf (2, i, 2, 2)
%!error<hygecdf: X, T, M, and N must not be complex.> hygecdf (2, 2, i, 2)
%!error<hygecdf: X, T, M, and N must not be complex.> hygecdf (2, 2, 2, i)
