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Merge pull request #18200 from WarrenWeckesser/genexpon-not-xslow
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TST: stats: Move genexpon from xslow to slow fit test sets.
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@tylerjereddy
tylerjereddy committed Mar 27, 2023
2 parents 979102e + 63cb810 commit ec4241c
Showing 1 changed file with 57 additions and 39 deletions.
96 changes: 57 additions & 39 deletions scipy/stats/tests/test_fit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -219,24 +219,31 @@ def cases_test_fit_mle():
# These fail default test or hang
skip_basic_fit = {'argus', 'foldnorm', 'truncpareto', 'truncweibull_min',
'ksone', 'levy_stable', 'studentized_range', 'kstwo'}
slow_basic_fit = {'burr12', 'johnsonsb', 'bradford', 'fisk', 'mielke',
'exponpow', 'rdist', 'norminvgauss', 'betaprime',
'powerlaw', 'pareto', 'johnsonsu', 'loglaplace',
'wrapcauchy', 'weibull_max', 'arcsine', 'binom', 'rice',
'uniform', 'f', 'invweibull', 'genpareto',
'nbinom', 'kappa3', 'lognorm', 'halfgennorm', 'pearson3',
'alpha', 't', 'crystalball', 'fatiguelife', 'nakagami',
'kstwobign', 'gompertz', 'dweibull', 'lomax', 'invgauss',
'recipinvgauss', 'chi', 'foldcauchy', 'powernorm',
'gennorm', 'randint', 'genextreme'}
xslow_basic_fit = {'nchypergeom_fisher', 'nchypergeom_wallenius',
'gausshyper', 'genexpon', 'gengamma', 'genhyperbolic',
'geninvgauss', 'tukeylambda', 'skellam', 'ncx2',
'hypergeom', 'nhypergeom', 'zipfian', 'ncf',
'truncnorm', 'powerlognorm', 'beta',
'loguniform', 'reciprocal', 'trapezoid', 'nct',
'kappa4', 'betabinom', 'exponweib', 'genhalflogistic',
'burr', 'triang'}

# Please keep this list in alphabetical order...
slow_basic_fit = {'alpha', 'arcsine',
'betaprime', 'binom', 'bradford', 'burr12',
'chi', 'crystalball', 'dweibull', 'exponpow',
'f', 'fatiguelife', 'fisk', 'foldcauchy',
'genexpon', 'genextreme', 'gennorm', 'genpareto',
'gompertz', 'halfgennorm', 'invgauss', 'invweibull',
'johnsonsb', 'johnsonsu', 'kappa3', 'kstwobign',
'loglaplace', 'lognorm', 'lomax', 'mielke',
'nakagami', 'nbinom', 'norminvgauss',
'pareto', 'pearson3', 'powerlaw', 'powernorm',
'randint', 'rdist', 'recipinvgauss', 'rice',
't', 'uniform', 'weibull_max', 'wrapcauchy'}

# Please keep this list in alphabetical order...
xslow_basic_fit = {'beta', 'betabinom', 'burr', 'exponweib',
'gausshyper', 'gengamma', 'genhalflogistic',
'genhyperbolic', 'geninvgauss',
'hypergeom', 'kappa4', 'loguniform',
'ncf', 'nchypergeom_fisher', 'nchypergeom_wallenius',
'nct', 'ncx2', 'nhypergeom',
'powerlognorm', 'reciprocal', 'skellam',
'trapezoid', 'triang', 'truncnorm', 'tukeylambda',
'zipfian'}

for dist in dict(distdiscrete + distcont):
if dist in skip_basic_fit or not isinstance(dist, str):
Expand All @@ -261,27 +268,38 @@ def cases_test_fit_mse():
'gausshyper', 'genhyperbolic', # integration warnings
'argus', # close, but doesn't meet tolerance
'vonmises'} # can have negative CDF; doesn't play nice
slow_basic_fit = {'wald', 'genextreme', 'anglit', 'semicircular',
'kstwobign', 'arcsine', 'genlogistic', 'truncexpon',
'fisk', 'uniform', 'exponnorm', 'maxwell', 'lomax',
'laplace_asymmetric', 'lognorm', 'foldcauchy',
'genpareto', 'powernorm', 'loglaplace', 'foldnorm',
'recipinvgauss', 'exponpow', 'bradford', 'weibull_max',
'gompertz', 'dweibull', 'truncpareto', 'weibull_min',
'johnsonsu', 'loggamma', 'kappa3', 'fatiguelife',
'pareto', 'invweibull', 'alpha', 'erlang', 'dgamma',
'chi2', 'crystalball', 'nakagami', 'truncweibull_min',
't', 'vonmises_line', 'triang', 'wrapcauchy', 'gamma',
'mielke', 'chi', 'johnsonsb', 'exponweib',
'genhalflogistic', 'randint', 'nhypergeom', 'hypergeom',
'betabinom'}
xslow_basic_fit = {'burr', 'halfgennorm', 'invgamma',
'invgauss', 'powerlaw', 'burr12', 'trapezoid', 'kappa4',
'f', 'powerlognorm', 'ncx2', 'rdist', 'reciprocal',
'loguniform', 'betaprime', 'rice', 'gennorm',
'gengamma', 'truncnorm', 'ncf', 'nct', 'pearson3',
'beta', 'genexpon', 'tukeylambda', 'zipfian',
'nchypergeom_wallenius', 'nchypergeom_fisher'}

# Please keep this list in alphabetical order...
slow_basic_fit = {'alpha', 'anglit', 'arcsine', 'betabinom', 'bradford',
'chi', 'chi2', 'crystalball', 'dgamma', 'dweibull',
'erlang', 'exponnorm', 'exponpow', 'exponweib',
'fatiguelife', 'fisk', 'foldcauchy', 'foldnorm',
'gamma', 'genexpon', 'genextreme', 'genhalflogistic',
'genlogistic', 'genpareto', 'gompertz',
'hypergeom', 'invweibull', 'johnsonsb', 'johnsonsu',
'kappa3', 'kstwobign',
'laplace_asymmetric', 'loggamma', 'loglaplace',
'lognorm', 'lomax',
'maxwell', 'mielke', 'nakagami', 'nhypergeom',
'pareto', 'powernorm', 'randint', 'recipinvgauss',
'semicircular',
't', 'triang', 'truncexpon', 'truncpareto',
'truncweibull_min',
'uniform', 'vonmises_line',
'wald', 'weibull_max', 'weibull_min', 'wrapcauchy'}

# Please keep this list in alphabetical order...
xslow_basic_fit = {'beta', 'betaprime', 'burr', 'burr12',
'f', 'gengamma', 'gennorm',
'halfgennorm', 'invgamma', 'invgauss',
'kappa4', 'loguniform',
'ncf', 'nchypergeom_fisher', 'nchypergeom_wallenius',
'nct', 'ncx2',
'pearson3', 'powerlaw', 'powerlognorm',
'rdist', 'reciprocal', 'rice',
'trapezoid', 'truncnorm', 'tukeylambda',
'zipfian'}

warns_basic_fit = {'skellam'} # can remove mark after gh-14901 is resolved

for dist in dict(distdiscrete + distcont):
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