added test_estimation.py and test_continuous_extra.py
Per.Andreas.Brodtkorb
11 years ago
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# contains additional tests for continuous distributions
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#
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# NOTE: one test, _est_cont_skip, that is renamed so that nose doesn't
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# run it,
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# 6 distributions return nan for entropy
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# truncnorm fails by design for private method _ppf test
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from __future__ import division, print_function, absolute_import
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import numpy.testing as npt
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import numpy as np
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from wafo import stats
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from test_continuous_basic import distcont
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DECIMAL = 5
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@npt.dec.slow
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def test_cont_extra():
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for distname, arg in distcont[:]:
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distfn = getattr(stats, distname)
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yield check_ppf_limits, distfn, arg, distname + \
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' ppf limit test'
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yield check_isf_limits, distfn, arg, distname + \
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' isf limit test'
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yield check_loc_scale, distfn, arg, distname + \
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' loc, scale test'
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@npt.dec.slow
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def _est_cont_skip():
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for distname, arg in distcont:
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distfn = getattr(stats, distname)
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#entropy test checks only for isnan, currently 6 isnan left
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yield check_entropy, distfn, arg, distname + \
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' entropy nan test'
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# _ppf test has 1 failure be design
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yield check_ppf_private, distfn, arg, distname + \
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' _ppf private test'
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def test_540_567():
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# test for nan returned in tickets 540, 567
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npt.assert_almost_equal(stats.norm.cdf(-1.7624320982),0.03899815971089126,
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decimal=10, err_msg = 'test_540_567')
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npt.assert_almost_equal(stats.norm.cdf(-1.7624320983),0.038998159702449846,
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decimal=10, err_msg = 'test_540_567')
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npt.assert_almost_equal(stats.norm.cdf(1.38629436112, loc=0.950273420309,
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scale=0.204423758009),0.98353464004309321,
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decimal=10, err_msg = 'test_540_567')
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def check_ppf_limits(distfn,arg,msg):
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below,low,upp,above = distfn.ppf([-1,0,1,2], *arg)
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#print distfn.name, distfn.a, low, distfn.b, upp
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#print distfn.name,below,low,upp,above
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assert_equal_inf_nan(distfn.a,low, msg + 'ppf lower bound')
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assert_equal_inf_nan(distfn.b,upp, msg + 'ppf upper bound')
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npt.assert_(np.isnan(below), msg + 'ppf out of bounds - below')
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npt.assert_(np.isnan(above), msg + 'ppf out of bounds - above')
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def check_ppf_private(distfn,arg,msg):
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#fails by design for trunk norm self.nb not defined
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ppfs = distfn._ppf(np.array([0.1,0.5,0.9]), *arg)
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npt.assert_(not np.any(np.isnan(ppfs)), msg + 'ppf private is nan')
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def check_isf_limits(distfn,arg,msg):
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below,low,upp,above = distfn.isf([-1,0,1,2], *arg)
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#print distfn.name, distfn.a, low, distfn.b, upp
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#print distfn.name,below,low,upp,above
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assert_equal_inf_nan(distfn.a,upp, msg + 'isf lower bound')
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assert_equal_inf_nan(distfn.b,low, msg + 'isf upper bound')
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npt.assert_(np.isnan(below), msg + 'isf out of bounds - below')
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npt.assert_(np.isnan(above), msg + 'isf out of bounds - above')
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def check_loc_scale(distfn,arg,msg):
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m,v = distfn.stats(*arg)
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loc, scale = 10.0, 10.0
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mt,vt = distfn.stats(loc=loc, scale=scale, *arg)
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assert_equal_inf_nan(m*scale+loc,mt,msg + 'mean')
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assert_equal_inf_nan(v*scale*scale,vt,msg + 'var')
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def check_entropy(distfn,arg,msg):
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ent = distfn.entropy(*arg)
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#print 'Entropy =', ent
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npt.assert_(not np.isnan(ent), msg + 'test Entropy is nan')
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def assert_equal_inf_nan(v1,v2,msg):
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npt.assert_(not np.isnan(v1))
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if not np.isinf(v1):
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npt.assert_almost_equal(v1, v2, decimal=DECIMAL, err_msg = msg + \
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' - finite')
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else:
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npt.assert_(np.isinf(v2) or np.isnan(v2),
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msg + ' - infinite, v2=%s' % str(v2))
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if __name__ == "__main__":
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import nose
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#nose.run(argv=['', __file__])
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nose.runmodule(argv=[__file__,'-s'], exit=False)
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@ -1,48 +0,0 @@
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# -*- coding:utf-8 -*-
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"""
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Created on 19. nov. 2010
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@author: pab
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"""
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from numpy import array, log
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import wafo.stats as ws
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from wafo.stats.estimation import FitDistribution, Profile
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def test_profile():
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'''
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# MLE
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import wafo.stats as ws
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R = ws.weibull_min.rvs(1,size=20)
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>>> R = array([ 0.08018795, 1.09015299, 2.08591271, 0.51542081, 0.75692042,
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... 0.57837017, 0.45419753, 1.1559131 , 0.26582267, 0.51517273,
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... 0.75008492, 0.59404957, 1.33748264, 0.14472142, 0.77459603,
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... 1.77312556, 1.06347991, 0.42007769, 0.71094628, 0.02366977])
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>>> phat = FitDistribution(ws.weibull_min, R, 1, scale=1, floc=0.0)
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>>> phat.par
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array([ 1.37836487, 0. , 0.82085633])
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# Better CI for phat.par[i=0]
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>>> Lp = Profile(phat, i=0)
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>>> Lp.get_bounds(alpha=0.1)
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array([ 1.00225064, 1.8159036 ])
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>>> SF = 1./990
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>>> x = phat.isf(SF)
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>>> x
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3.3323076459875312
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# CI for x
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>>> Lx = phat.profile(i=0, x=x, link=phat.dist.link)
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>>> Lx.get_bounds(alpha=0.2)
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array([ 2.52211661, 4.98664787])
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# CI for logSF=log(SF)
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>>> logSF = log(SF)
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>>> Lsf = phat.profile(i=0, logSF=logSF, link=phat.dist.link, pmin=logSF-10,pmax=logSF+5)
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>>> Lsf.get_bounds(alpha=0.2)
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array([-10.87488318, -4.36225468])
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'''
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if __name__ == '__main__':
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import doctest
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doctest.testmod()
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