Mercurial > hg > octave-nkf
diff scripts/statistics/distributions/discrete_cdf.m @ 13171:19b9f17d22af
Overhaul of statistical distribution functions
Support class "single"
75% reduction in memory usage
More Matlab compatibility for corner cases
* betacdf.m, betainv.m, betapdf.m, betarnd.m, binocdf.m, binoinv.m, binopdf.m,
binornd.m, cauchy_cdf.m, cauchy_inv.m, cauchy_pdf.m, cauchy_rnd.m, chi2cdf.m,
chi2inv.m, chi2pdf.m, chi2rnd.m, discrete_cdf.m, discrete_inv.m,
discrete_pdf.m, discrete_rnd.m, empirical_cdf.m, empirical_inv.m,
empirical_pdf.m, empirical_rnd.m, expcdf.m, expinv.m, exppdf.m, exprnd.m,
fcdf.m, finv.m, fpdf.m, frnd.m, gamcdf.m, gaminv.m, gampdf.m, gamrnd.m,
geocdf.m, geoinv.m, geopdf.m, geornd.m, hygecdf.m, hygeinv.m, hygepdf.m,
hygernd.m, kolmogorov_smirnov_cdf.m, laplace_cdf.m, laplace_inv.m,
laplace_pdf.m, laplace_rnd.m, logistic_cdf.m, logistic_inv.m, logistic_pdf.m,
logistic_rnd.m, logncdf.m, logninv.m, lognpdf.m, lognrnd.m, nbincdf.m,
nbininv.m, nbinpdf.m, nbinrnd.m, normcdf.m, norminv.m, normpdf.m, normrnd.m,
poisscdf.m, poissinv.m, poisspdf.m, poissrnd.m, stdnormal_cdf.m,
stdnormal_inv.m, stdnormal_pdf.m, stdnormal_rnd.m, tcdf.m, tinv.m, tpdf.m,
trnd.m, unidcdf.m, unidinv.m, unidpdf.m, unidrnd.m, unifcdf.m, unifinv.m,
unifpdf.m, unifrnd.m, wblcdf.m, wblinv.m, wblpdf.m, wblrnd.m:
Return "single" outputs for "single" inputs,
Use logical indexing rather than find() for 75% memory savings,
Add tests for all functions,
Use consistent documentation across all functions,
More Matlab compatibilitcy for corner cases.
| author | Rik <octave@nomad.inbox5.com> |
|---|---|
| date | Tue, 20 Sep 2011 12:13:13 -0700 |
| parents | fd0a3ac60b0e |
| children | 72c96de7a403 |
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--- a/scripts/statistics/distributions/discrete_cdf.m +++ b/scripts/statistics/distributions/discrete_cdf.m @@ -1,3 +1,4 @@ +## Copyright (C) 2011 Rik Wehbring ## Copyright (C) 2010-2011 David Bateman ## ## This file is part of Octave. @@ -29,28 +30,52 @@ print_usage (); endif - sz = size (x); - if (! isvector (v)) error ("discrete_cdf: V must be a vector"); + elseif (any (isnan (v))) + error ("discrete_cdf: V must not have any NaN elements"); elseif (! isvector (p) || (length (p) != length (v))) error ("discrete_cdf: P must be a vector with length (V) elements"); elseif (! (all (p >= 0) && any (p))) - error ("discrete_cdf: P must be a nonzero, nonnegative vector"); + error ("discrete_cdf: P must be a nonzero, non-negative vector"); + endif + + p = p(:) / sum (p); # Reshape and normalize probability vector + + if (isa (x, "single") || isa (v, "single") || isa (p, "single")); + cdf = NaN (size (x), "single"); + else + cdf = NaN (size (x)); endif - n = numel (x); - m = length (v); - x = reshape (x, n, 1); - v = reshape (v, 1, m); - p = reshape (p / sum (p), m, 1); - - cdf = NaN (sz); - k = find (!isnan (x)); - if (any (k)) - n = length (k); - [vs, vi] = sort (v); - cdf(k) = [0 ; cumsum(p(vi))](lookup (vs, x(k)) + 1); - endif + k = !isnan (x); + [vs, vi] = sort (v); + cdf(k) = [0 ; cumsum(p(vi))](lookup (vs, x(k)) + 1); endfunction + + +%!shared x,v,p,y +%! x = [-1 0.1 1.1 1.9 3]; +%! v = 0.1:0.2:1.9; +%! p = 1/length(v) * ones(1, length(v)); +%! y = [0 0.1 0.6 1 1]; +%!assert(discrete_cdf ([x, NaN], v, p), [y, NaN], eps); + +%% Test class of input preserved +%!assert(discrete_cdf (single([x, NaN]), v, p), single([y, NaN]), 2*eps("single")); +%!assert(discrete_cdf ([x, NaN], single(v), p), single([y, NaN]), 2*eps("single")); +%!assert(discrete_cdf ([x, NaN], v, single(p)), single([y, NaN]), 2*eps("single")); + +%% Test input validation +%!error discrete_cdf () +%!error discrete_cdf (1) +%!error discrete_cdf (1,2) +%!error discrete_cdf (1,2,3,4) +%!error discrete_cdf (1, ones(2), ones(2,1)) +%!error discrete_cdf (1, [1 ; NaN], ones(2,1)) +%!error discrete_cdf (1, ones(2,1), ones(1,1)) +%!error discrete_cdf (1, ones(2,1), [1 -1]) +%!error discrete_cdf (1, ones(2,1), [1 NaN]) +%!error discrete_cdf (1, ones(2,1), [0 0]) +