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numpy-scipy-output-20130131-1414.txt
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numpy-scipy-output-20130131-1414.txt
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[bpartrid@bc1013 ~/mic]$ ~/mic_launch_task.sh
Pseudo-terminal will not be allocated because stdin is not a terminal.
cat: can't open '/etc/clustername': No such file or directory
Number of cores: 240
nose.config: INFO: Ignoring files matching ['^\\.', '^_', '^setup\\.py$']
nose.config: INFO: Excluding tests matching ['f2py_ext', 'f2py_f90_ext', 'gen_ext', 'pyrex_ext', 'swig_ext']
test_n_zero (test_random.TestBinomial) ... ok
test_basic (test_random.TestMultinomial) ... ok
test_int_negative_interval (test_random.TestMultinomial) ... ok
test_zero_probability (test_random.TestMultinomial) ... ok
test_beta (test_random.TestRandomDist) ... ok
test_binomial (test_random.TestRandomDist) ... ok
test_bytes (test_random.TestRandomDist) ... ok
test_chisquare (test_random.TestRandomDist) ... ok
test_choice_exceptions (test_random.TestRandomDist) ... ok
test_choice_noninteger (test_random.TestRandomDist) ... ok
test_choice_nonuniform_noreplace (test_random.TestRandomDist) ... ok
test_choice_nonuniform_replace (test_random.TestRandomDist) ... ok
test_choice_return_shape (test_random.TestRandomDist) ... ok
test_choice_uniform_noreplace (test_random.TestRandomDist) ... ok
test_choice_uniform_replace (test_random.TestRandomDist) ... ok
test_dirichlet (test_random.TestRandomDist) ... ok
test_exponential (test_random.TestRandomDist) ... ok
test_f (test_random.TestRandomDist) ... ok
test_gamma (test_random.TestRandomDist) ... ok
test_geometric (test_random.TestRandomDist) ... ok
test_gumbel (test_random.TestRandomDist) ... ok
test_hypergeometric (test_random.TestRandomDist) ... ok
test_laplace (test_random.TestRandomDist) ... ok
test_logistic (test_random.TestRandomDist) ... ok
test_lognormal (test_random.TestRandomDist) ... ok
test_logseries (test_random.TestRandomDist) ... ok
test_multinomial (test_random.TestRandomDist) ... ok
test_multivariate_normal (test_random.TestRandomDist) ... ok
test_negative_binomial (test_random.TestRandomDist) ... ok
test_noncentral_chisquare (test_random.TestRandomDist) ... ok
test_noncentral_f (test_random.TestRandomDist) ... ok
test_normal (test_random.TestRandomDist) ... ok
test_pareto (test_random.TestRandomDist) ... ok
test_poisson (test_random.TestRandomDist) ... ok
test_poisson_exceptions (test_random.TestRandomDist) ... ok
test_power (test_random.TestRandomDist) ... ok
test_rand (test_random.TestRandomDist) ... ok
test_randint (test_random.TestRandomDist) ... ok
test_randn (test_random.TestRandomDist) ... ok
test_random_integers (test_random.TestRandomDist) ... ok
test_random_sample (test_random.TestRandomDist) ... ok
test_rayleigh (test_random.TestRandomDist) ... ok
test_shuffle (test_random.TestRandomDist) ... ok
test_standard_cauchy (test_random.TestRandomDist) ... ok
test_standard_exponential (test_random.TestRandomDist) ... ok
test_standard_gamma (test_random.TestRandomDist) ... ok
test_standard_normal (test_random.TestRandomDist) ... ok
test_standard_t (test_random.TestRandomDist) ... ok
test_triangular (test_random.TestRandomDist) ... ok
test_uniform (test_random.TestRandomDist) ... ok
test_vonmises (test_random.TestRandomDist) ... ok
test_wald (test_random.TestRandomDist) ... ok
test_weibull (test_random.TestRandomDist) ... ok
test_zipf (test_random.TestRandomDist) ... ok
Make sure we can accept old state tuples that do not have the cached ... ok
test_basic (test_random.TestSetState) ... ok
Make sure the cached every-other-Gaussian is reset. ... ok
When the state is saved with a cached Gaussian, make sure the cached ... ok
Ensure that the negative binomial results take floating point ... ok
test_VonMises_range (test_regression.TestRegression) ... ok
test_call_within_randomstate (test_regression.TestRegression) ... ok
test_hypergeometric_range (test_regression.TestRegression) ... ok
test_logseries_convergence (test_regression.TestRegression) ... ok
test_multivariate_normal_size_types (test_regression.TestRegression) ... ok
test_permutation_longs (test_regression.TestRegression) ... ok
test_randint_range (test_regression.TestRegression) ... ok
test_shuffle_mixed_dimension (test_regression.TestRegression) ... ok
----------------------------------------------------------------------
Ran 67 tests in 0.698s
OK
sys.maxunicode: 1114111
errors: {'over': 'ignore', 'divide': 'ignore', 'invalid': 'ignore', 'under': 'ignore'}
Running unit tests for numpy.random
NumPy version 1.8.0
NumPy is installed in /global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/numpy
Python version 2.7.3 (default, Jan 31 2014, 01:09:18) [GCC Intel(R) C++ gcc 4.7 mode]
nose version 1.3.0
<nose.result.TextTestResult run=67 errors=0 failures=0>
[ -inf 0. 0.69314718 1.09861229 1.38629436]
Traceback (most recent call last):
File "mic_task.py", line 17, in <module>
print scipy.stat.test(verbose=3)
AttributeError: 'module' object has no attribute 'stat'
[bpartrid@bc1013 ~/mic]$ ~/mic_launch_task.sh
Pseudo-terminal will not be allocated because stdin is not a terminal.
cat: can't open '/etc/clustername': No such file or directory
Number of cores: 240
nose.config: INFO: Ignoring files matching ['^\\.', '^_', '^setup\\.py$']
nose.config: INFO: Excluding tests matching ['f2py_ext', 'f2py_f90_ext', 'gen_ext', 'pyrex_ext', 'swig_ext']
test_n_zero (test_random.TestBinomial) ... ok
test_basic (test_random.TestMultinomial) ... ok
test_int_negative_interval (test_random.TestMultinomial) ... ok
test_zero_probability (test_random.TestMultinomial) ... ok
test_beta (test_random.TestRandomDist) ... ok
test_binomial (test_random.TestRandomDist) ... ok
test_bytes (test_random.TestRandomDist) ... ok
test_chisquare (test_random.TestRandomDist) ... ok
test_choice_exceptions (test_random.TestRandomDist) ... ok
test_choice_noninteger (test_random.TestRandomDist) ... ok
test_choice_nonuniform_noreplace (test_random.TestRandomDist) ... ok
test_choice_nonuniform_replace (test_random.TestRandomDist) ... ok
test_choice_return_shape (test_random.TestRandomDist) ... ok
test_choice_uniform_noreplace (test_random.TestRandomDist) ... ok
test_choice_uniform_replace (test_random.TestRandomDist) ... ok
test_dirichlet (test_random.TestRandomDist) ... ok
test_exponential (test_random.TestRandomDist) ... ok
test_f (test_random.TestRandomDist) ... ok
test_gamma (test_random.TestRandomDist) ... ok
test_geometric (test_random.TestRandomDist) ... ok
test_gumbel (test_random.TestRandomDist) ... ok
test_hypergeometric (test_random.TestRandomDist) ... ok
test_laplace (test_random.TestRandomDist) ... ok
test_logistic (test_random.TestRandomDist) ... ok
test_lognormal (test_random.TestRandomDist) ... ok
test_logseries (test_random.TestRandomDist) ... ok
test_multinomial (test_random.TestRandomDist) ... ok
test_multivariate_normal (test_random.TestRandomDist) ... ok
test_negative_binomial (test_random.TestRandomDist) ... ok
test_noncentral_chisquare (test_random.TestRandomDist) ... ok
test_noncentral_f (test_random.TestRandomDist) ... ok
test_normal (test_random.TestRandomDist) ... ok
test_pareto (test_random.TestRandomDist) ... ok
test_poisson (test_random.TestRandomDist) ... ok
test_poisson_exceptions (test_random.TestRandomDist) ... ok
test_power (test_random.TestRandomDist) ... ok
test_rand (test_random.TestRandomDist) ... ok
test_randint (test_random.TestRandomDist) ... ok
test_randn (test_random.TestRandomDist) ... ok
test_random_integers (test_random.TestRandomDist) ... ok
test_random_sample (test_random.TestRandomDist) ... ok
test_rayleigh (test_random.TestRandomDist) ... ok
test_shuffle (test_random.TestRandomDist) ... ok
test_standard_cauchy (test_random.TestRandomDist) ... ok
test_standard_exponential (test_random.TestRandomDist) ... ok
test_standard_gamma (test_random.TestRandomDist) ... ok
test_standard_normal (test_random.TestRandomDist) ... ok
test_standard_t (test_random.TestRandomDist) ... ok
test_triangular (test_random.TestRandomDist) ... ok
test_uniform (test_random.TestRandomDist) ... ok
test_vonmises (test_random.TestRandomDist) ... ok
test_wald (test_random.TestRandomDist) ... ok
test_weibull (test_random.TestRandomDist) ... ok
test_zipf (test_random.TestRandomDist) ... ok
Make sure we can accept old state tuples that do not have the cached ... ok
test_basic (test_random.TestSetState) ... ok
Make sure the cached every-other-Gaussian is reset. ... ok
When the state is saved with a cached Gaussian, make sure the cached ... ok
Ensure that the negative binomial results take floating point ... ok
test_VonMises_range (test_regression.TestRegression) ... ok
test_call_within_randomstate (test_regression.TestRegression) ... ok
test_hypergeometric_range (test_regression.TestRegression) ... ok
test_logseries_convergence (test_regression.TestRegression) ... ok
test_multivariate_normal_size_types (test_regression.TestRegression) ... ok
test_permutation_longs (test_regression.TestRegression) ... ok
test_randint_range (test_regression.TestRegression) ... ok
test_shuffle_mixed_dimension (test_regression.TestRegression) ... ok
----------------------------------------------------------------------
Ran 67 tests in 0.702s
OK
nose.config: INFO: Ignoring files matching ['^\\.', '^_', '^setup\\.py$']
nose.config: INFO: Excluding tests matching ['f2py_ext', 'f2py_f90_ext', 'gen_ext', 'pyrex_ext', 'swig_ext']
test_binned_statistic.TestBinnedStatistic.test_1d_bincode ... ok
test_binned_statistic.TestBinnedStatistic.test_1d_count ... ok
test_binned_statistic.TestBinnedStatistic.test_1d_mean ... /global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/numpy/core/_methods.py:55: RuntimeWarning: Mean of empty slice.
warnings.warn("Mean of empty slice.", RuntimeWarning)
ok
test_binned_statistic.TestBinnedStatistic.test_1d_median ... ok
test_binned_statistic.TestBinnedStatistic.test_1d_std ... /global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/numpy/core/_methods.py:77: RuntimeWarning: Degrees of freedom <= 0 for slice
warnings.warn("Degrees of freedom <= 0 for slice", RuntimeWarning)
ok
test_binned_statistic.TestBinnedStatistic.test_1d_sum ... ok
test_binned_statistic.TestBinnedStatistic.test_2d_bincode ... ok
test_binned_statistic.TestBinnedStatistic.test_2d_count ... ok
test_binned_statistic.TestBinnedStatistic.test_2d_mean ... ok
test_binned_statistic.TestBinnedStatistic.test_2d_median ... ok
test_binned_statistic.TestBinnedStatistic.test_2d_std ... ok
test_binned_statistic.TestBinnedStatistic.test_2d_sum ... ok
test_binned_statistic.TestBinnedStatistic.test_dd_bincode ... ok
test_binned_statistic.TestBinnedStatistic.test_dd_count ... ok
test_binned_statistic.TestBinnedStatistic.test_dd_mean ... ok
test_binned_statistic.TestBinnedStatistic.test_dd_median ... ok
test_binned_statistic.TestBinnedStatistic.test_dd_std ... ok
test_binned_statistic.TestBinnedStatistic.test_dd_sum ... ok
test_contingency.test_margins ... ok
test_contingency.test_expected_freq ... ok
test_contingency.test_chi2_contingency_trivial ... ok
test_contingency.test_chi2_contingency_R ... ok
test_contingency.test_chi2_contingency_g ... ok
test_contingency.test_chi2_contingency_bad_args ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), array(inf), array(inf), 0.31367479245062557, 0.017416610612647002, 500, 'alphasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), array(inf), array(inf), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, (3.5704770516650459,), 'alpha') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x35ca5d0>, 0.5, (3.5704770516650459,), (0, 1), [<bound method alpha_gen.pdf of <scipy.stats.distributions.alpha_gen object at 0x35ca5d0>>, <bound method alpha_gen.logpdf of <scipy.stats.distributions.alpha_gen object at 0x35ca5d0>>, <bound method alpha_gen.cdf of <scipy.stats.distributions.alpha_gen object at 0x35ca5d0>>, <bound method alpha_gen.logcdf of <scipy.stats.distributions.alpha_gen object at 0x35ca5d0>>, <bound method alpha_gen.logsf of <scipy.stats.distributions.alpha_gen object at 0x35ca5d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), array(0.0), array(0.11685027506808487), 0.018367440208548202, 0.11208199561517891, 500, 'anglitsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), array(0.0), array(0.11685027506808487), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, (), 'anglit') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x35ca550>, 0.5, (), (0, 1), [<bound method anglit_gen.pdf of <scipy.stats.distributions.anglit_gen object at 0x35ca550>>, <bound method anglit_gen.logpdf of <scipy.stats.distributions.anglit_gen object at 0x35ca550>>, <bound method anglit_gen.cdf of <scipy.stats.distributions.anglit_gen object at 0x35ca550>>, <bound method anglit_gen.logcdf of <scipy.stats.distributions.anglit_gen object at 0x35ca550>>, <bound method anglit_gen.logsf of <scipy.stats.distributions.anglit_gen object at 0x35ca550>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), array(0.5), array(0.125), 0.51727075923046451, 0.12643304814773981, 500, 'arcsinesample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), array(0.5), array(0.125), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, (), 'arcsine') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>, 0.5, (), (0, 1), [<bound method arcsine_gen.pdf of <scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>>, <bound method arcsine_gen.logpdf of <scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>>, <bound method arcsine_gen.cdf of <scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>>, <bound method arcsine_gen.logcdf of <scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>>, <bound method arcsine_gen.logsf of <scipy.stats.distributions.arcsine_gen object at 0x35ca8d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), array(0.78653818488354665), array(0.04264856955583702), 0.78535971919302683, 0.047244450357504325, 500, 'betasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), array(0.78653818488354665), array(0.04264856955583702), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x35ca810>, 0.5, (2.3098496451481823, 0.62687954300963677), (0, 1), [<bound method beta_gen.pdf of <scipy.stats.distributions.beta_gen object at 0x35ca810>>, <bound method beta_gen.logpdf of <scipy.stats.distributions.beta_gen object at 0x35ca810>>, <bound method beta_gen.cdf of <scipy.stats.distributions.beta_gen object at 0x35ca810>>, <bound method beta_gen.logcdf of <scipy.stats.distributions.beta_gen object at 0x35ca810>>, <bound method beta_gen.logsf of <scipy.stats.distributions.beta_gen object at 0x35ca810>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), array(1.0), array(0.5), 0.99538612978827079, 0.45669922054638912, 500, 'betaprimesample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), array(1.0), array(0.5), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, (5, 6), 'betaprime') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x35cacd0>, 0.5, (5, 6), (0, 1), [<bound method betaprime_gen.pdf of <scipy.stats.distributions.betaprime_gen object at 0x35cacd0>>, <bound method betaprime_gen.logpdf of <scipy.stats.distributions.betaprime_gen object at 0x35cacd0>>, <bound method betaprime_gen.cdf of <scipy.stats.distributions.betaprime_gen object at 0x35cacd0>>, <bound method betaprime_gen.logcdf of <scipy.stats.distributions.betaprime_gen object at 0x35cacd0>>, <bound method betaprime_gen.logsf of <scipy.stats.distributions.betaprime_gen object at 0x35cacd0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), array(0.47823078529291196), array(0.083238491922311225), 0.49307116783612509, 0.082730699030605204, 500, 'bradfordsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), array(0.47823078529291196), array(0.083238491922311225), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, (0.29891359763170633,), 'bradford') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x35cae10>, 0.5, (0.29891359763170633,), (0, 1), [<bound method bradford_gen.pdf of <scipy.stats.distributions.bradford_gen object at 0x35cae10>>, <bound method bradford_gen.logpdf of <scipy.stats.distributions.bradford_gen object at 0x35cae10>>, <bound method bradford_gen.cdf of <scipy.stats.distributions.bradford_gen object at 0x35cae10>>, <bound method bradford_gen.logcdf of <scipy.stats.distributions.bradford_gen object at 0x35cae10>>, <bound method bradford_gen.logsf of <scipy.stats.distributions.bradford_gen object at 0x35cae10>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), array(1.2109372989617821), array(0.029148272765685351), 1.2172088960241723, 0.026780180283484011, 500, 'burrsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), array(1.2109372989617821), array(0.029148272765685351), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, (10.5, 4.2999999999999998), 'burr') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x35d2210>, 0.5, (10.5, 4.2999999999999998), (0, 1), [<bound method burr_gen.pdf of <scipy.stats.distributions.burr_gen object at 0x35d2210>>, <bound method burr_gen.logpdf of <scipy.stats.distributions.burr_gen object at 0x35d2210>>, <bound method burr_gen.cdf of <scipy.stats.distributions.burr_gen object at 0x35d2210>>, <bound method burr_gen.logcdf of <scipy.stats.distributions.burr_gen object at 0x35d2210>>, <bound method burr_gen.logsf of <scipy.stats.distributions.burr_gen object at 0x35d2210>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), array(inf), array(inf), 1.14108871883173, 255.27806250564547, 500, 'cauchysample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), array(inf), array(inf), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, (), 'cauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x35d2950>, 0.5, (), (0, 1), [<bound method cauchy_gen.pdf of <scipy.stats.distributions.cauchy_gen object at 0x35d2950>>, <bound method cauchy_gen.logpdf of <scipy.stats.distributions.cauchy_gen object at 0x35d2950>>, <bound method cauchy_gen.cdf of <scipy.stats.distributions.cauchy_gen object at 0x35d2950>>, <bound method cauchy_gen.logcdf of <scipy.stats.distributions.cauchy_gen object at 0x35d2950>>, <bound method cauchy_gen.logsf of <scipy.stats.distributions.cauchy_gen object at 0x35d2950>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), array(8.8035000285242742), array(0.49838724777310972), 8.7717120969213145, 0.45211144086349253, 500, 'chisample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), array(8.8035000285242742), array(0.49838724777310972), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, (78,), 'chi') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x35d2b10>, 0.5, (78,), (0, 1), [<bound method chi_gen.pdf of <scipy.stats.distributions.chi_gen object at 0x35d2b10>>, <bound method chi_gen.logpdf of <scipy.stats.distributions.chi_gen object at 0x35d2b10>>, <bound method chi_gen.cdf of <scipy.stats.distributions.chi_gen object at 0x35d2b10>>, <bound method chi_gen.logcdf of <scipy.stats.distributions.chi_gen object at 0x35d2b10>>, <bound method chi_gen.logsf of <scipy.stats.distributions.chi_gen object at 0x35d2b10>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), array(55.0), array(110.0), 54.482410915931212, 97.639217966893725, 500, 'chi2sample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), array(55.0), array(110.0), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, (55,), 'chi2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x35d29d0>, 0.5, (55,), (0, 1), [<bound method chi2_gen.pdf of <scipy.stats.distributions.chi2_gen object at 0x35d29d0>>, <bound method chi2_gen.logpdf of <scipy.stats.distributions.chi2_gen object at 0x35d29d0>>, <bound method chi2_gen.cdf of <scipy.stats.distributions.chi2_gen object at 0x35d29d0>>, <bound method chi2_gen.logcdf of <scipy.stats.distributions.chi2_gen object at 0x35d29d0>>, <bound method chi2_gen.logsf of <scipy.stats.distributions.chi2_gen object at 0x35d29d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), array(0.0), array(2.3174697893161609), 0.042812927055214021, 2.1013263587307547, 500, 'dgammasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), array(0.0), array(2.3174697893161609), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, (1.1023326088288166,), 'dgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x35d2c90>, 0.5, (1.1023326088288166,), (0, 1), [<bound method dgamma_gen.pdf of <scipy.stats.distributions.dgamma_gen object at 0x35d2c90>>, <bound method dgamma_gen.logpdf of <scipy.stats.distributions.dgamma_gen object at 0x35d2c90>>, <bound method dgamma_gen.cdf of <scipy.stats.distributions.dgamma_gen object at 0x35d2c90>>, <bound method dgamma_gen.logcdf of <scipy.stats.distributions.dgamma_gen object at 0x35d2c90>>, <bound method dgamma_gen.logsf of <scipy.stats.distributions.dgamma_gen object at 0x35d2c90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), array(0.0), array(0.98644644671326831), 0.022932864264314318, 1.0524606122901337, 500, 'dweibullsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), array(0.0), array(0.98644644671326831), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, (2.0685080649914673,), 'dweibull') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x35dd150>, 0.5, (2.0685080649914673,), (0, 1), [<bound method dweibull_gen.pdf of <scipy.stats.distributions.dweibull_gen object at 0x35dd150>>, <bound method dweibull_gen.logpdf of <scipy.stats.distributions.dweibull_gen object at 0x35dd150>>, <bound method dweibull_gen.cdf of <scipy.stats.distributions.dweibull_gen object at 0x35dd150>>, <bound method dweibull_gen.logcdf of <scipy.stats.distributions.dweibull_gen object at 0x35dd150>>, <bound method dweibull_gen.logsf of <scipy.stats.distributions.dweibull_gen object at 0x35dd150>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), array(10.0), array(10.0), 9.8360649709830064, 8.7098316478958662, 500, 'erlangsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), array(10.0), array(10.0), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, (10,), 'erlang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x35edad0>, 0.5, (10,), (0, 1), [<bound method erlang_gen.pdf of <scipy.stats.distributions.erlang_gen object at 0x35edad0>>, <bound method erlang_gen.logpdf of <scipy.stats.distributions.erlang_gen object at 0x35edad0>>, <bound method erlang_gen.cdf of <scipy.stats.distributions.erlang_gen object at 0x35edad0>>, <bound method erlang_gen.logcdf of <scipy.stats.distributions.erlang_gen object at 0x35edad0>>, <bound method erlang_gen.logsf of <scipy.stats.distributions.erlang_gen object at 0x35edad0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), array(1.0), array(1.0), 1.0278015071799511, 0.94136143490892221, 500, 'exponsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), array(1.0), array(1.0), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, (), 'expon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x35dd5d0>, 0.5, (), (0, 1), [<bound method expon_gen.pdf of <scipy.stats.distributions.expon_gen object at 0x35dd5d0>>, <bound method expon_gen.logpdf of <scipy.stats.distributions.expon_gen object at 0x35dd5d0>>, <bound method expon_gen.cdf of <scipy.stats.distributions.expon_gen object at 0x35dd5d0>>, <bound method expon_gen.logcdf of <scipy.stats.distributions.expon_gen object at 0x35dd5d0>>, <bound method expon_gen.logsf of <scipy.stats.distributions.expon_gen object at 0x35dd5d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), array(0.76622330667382155), array(0.05900404926303815), 0.7801740181561988, 0.054499283630077743, 500, 'exponpowsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), array(0.76622330667382155), array(0.05900404926303815), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, (2.697119160358469,), 'exponpow') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x35dd350>, 0.5, (2.697119160358469,), (0, 1), [<bound method exponpow_gen.pdf of <scipy.stats.distributions.exponpow_gen object at 0x35dd350>>, <bound method exponpow_gen.logpdf of <scipy.stats.distributions.exponpow_gen object at 0x35dd350>>, <bound method exponpow_gen.cdf of <scipy.stats.distributions.exponpow_gen object at 0x35dd350>>, <bound method exponpow_gen.logcdf of <scipy.stats.distributions.exponpow_gen object at 0x35dd350>>, <bound method exponpow_gen.logsf of <scipy.stats.distributions.exponpow_gen object at 0x35dd350>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), array(1.2873418037984088), array(0.1811917449895788), 1.3078688230441771, 0.16993814077150385, 500, 'exponweibsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), array(1.2873418037984088), array(0.1811917449895788), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x35dd610>, 0.5, (2.8923945291034436, 1.9505288745913174), (0, 1), [<bound method exponweib_gen.pdf of <scipy.stats.distributions.exponweib_gen object at 0x35dd610>>, <bound method exponweib_gen.logpdf of <scipy.stats.distributions.exponweib_gen object at 0x35dd610>>, <bound method exponweib_gen.cdf of <scipy.stats.distributions.exponweib_gen object at 0x35dd610>>, <bound method exponweib_gen.logcdf of <scipy.stats.distributions.exponweib_gen object at 0x35dd610>>, <bound method exponweib_gen.logsf of <scipy.stats.distributions.exponweib_gen object at 0x35dd610>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), array(1.125), array(0.2805572660098522), 1.1058441497371254, 0.2761099956674532, 500, 'fsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), array(1.125), array(0.2805572660098522), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, (29, 18), 'f') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x35ddfd0>, 0.5, (29, 18), (0, 1), [<bound method f_gen.pdf of <scipy.stats.distributions.f_gen object at 0x35ddfd0>>, <bound method f_gen.logpdf of <scipy.stats.distributions.f_gen object at 0x35ddfd0>>, <bound method f_gen.cdf of <scipy.stats.distributions.f_gen object at 0x35ddfd0>>, <bound method f_gen.logcdf of <scipy.stats.distributions.f_gen object at 0x35ddfd0>>, <bound method f_gen.logsf of <scipy.stats.distributions.f_gen object at 0x35ddfd0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), array(421.5), array(884942.25), 440.64984271265479, 761399.69888533256, 500, 'fatiguelifesample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), array(421.5), array(884942.25), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, (29,), 'fatiguelife') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>, 0.5, (29,), (0, 1), [<bound method fatiguelife_gen.pdf of <scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>>, <bound method fatiguelife_gen.logpdf of <scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>>, <bound method fatiguelife_gen.cdf of <scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>>, <bound method fatiguelife_gen.logcdf of <scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>>, <bound method fatiguelife_gen.logsf of <scipy.stats.distributions.fatiguelife_gen object at 0x35ddc50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), array(1.19619763403311), array(0.84763509403100801), 1.2116968934029968, 0.67028483370021164, 500, 'fisksample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), array(1.19619763403311), array(0.84763509403100801), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, (3.0857548622253179,), 'fisk') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x35d2190>, 0.5, (3.0857548622253179,), (0, 1), [<bound method fisk_gen.pdf of <scipy.stats.distributions.fisk_gen object at 0x35d2190>>, <bound method fisk_gen.logpdf of <scipy.stats.distributions.fisk_gen object at 0x35d2190>>, <bound method fisk_gen.cdf of <scipy.stats.distributions.fisk_gen object at 0x35d2190>>, <bound method fisk_gen.logcdf of <scipy.stats.distributions.fisk_gen object at 0x35d2190>>, <bound method fisk_gen.logsf of <scipy.stats.distributions.fisk_gen object at 0x35d2190>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), array(inf), array(inf), 6.5390809793828817, 246.8294454984825, 500, 'foldcauchysample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), array(inf), array(inf), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, (4.7164673455831894,), 'foldcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>, 0.5, (4.7164673455831894,), (0, 1), [<bound method foldcauchy_gen.pdf of <scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>>, <bound method foldcauchy_gen.logpdf of <scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>>, <bound method foldcauchy_gen.cdf of <scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>>, <bound method foldcauchy_gen.logcdf of <scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>>, <bound method foldcauchy_gen.logsf of <scipy.stats.distributions.foldcauchy_gen object at 0x35dde90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), array(1.97141281966251), array(0.92432482721597609), 2.0130752480273602, 0.93181489170164788, 500, 'foldnormsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), array(1.97141281966251), array(0.92432482721597609), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, (1.9521253373555869,), 'foldnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x35e5250>, 0.5, (1.9521253373555869,), (0, 1), [<bound method foldnorm_gen.pdf of <scipy.stats.distributions.foldnorm_gen object at 0x35e5250>>, <bound method foldnorm_gen.logpdf of <scipy.stats.distributions.foldnorm_gen object at 0x35e5250>>, <bound method foldnorm_gen.cdf of <scipy.stats.distributions.foldnorm_gen object at 0x35e5250>>, <bound method foldnorm_gen.logcdf of <scipy.stats.distributions.foldnorm_gen object at 0x35e5250>>, <bound method foldnorm_gen.logsf of <scipy.stats.distributions.foldnorm_gen object at 0x35e5250>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), array(-0.90148416697658329), array(0.076288054283963236), -0.88601789019302302, 0.070655885568653806, 500, 'frechet_lsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), array(-0.90148416697658329), array(0.076288054283963236), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, (3.6279911255583239,), 'frechet_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>, -0.5, (3.6279911255583239,), (0, 1), [<bound method frechet_l_gen.pdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>>, <bound method frechet_l_gen.logpdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>>, <bound method frechet_l_gen.cdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>>, <bound method frechet_l_gen.logcdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>>, <bound method frechet_l_gen.logsf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5a50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), array(0.88747270666698841), array(0.23766896745884436), 0.9089260664991714, 0.22728316833696841, 500, 'frechet_rsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), array(0.88747270666698841), array(0.23766896745884436), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, (1.8928171603534227,), 'frechet_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5610>, 0.5, (1.8928171603534227,), (0, 1), [<bound method frechet_r_gen.pdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5610>>, <bound method frechet_r_gen.logpdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5610>>, <bound method frechet_r_gen.cdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5610>>, <bound method frechet_r_gen.logcdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5610>>, <bound method frechet_r_gen.logsf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5610>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), array(1.9932305483800778), array(1.9932305483800778), 1.9122509111901549, 1.6434812827802439, 500, 'gammasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), array(1.9932305483800778), array(1.9932305483800778), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, (1.9932305483800778,), 'gamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x35ed890>, 0.5, (1.9932305483800778,), (0, 1), [<bound method gamma_gen.pdf of <scipy.stats.distributions.gamma_gen object at 0x35ed890>>, <bound method gamma_gen.logpdf of <scipy.stats.distributions.gamma_gen object at 0x35ed890>>, <bound method gamma_gen.cdf of <scipy.stats.distributions.gamma_gen object at 0x35ed890>>, <bound method gamma_gen.logcdf of <scipy.stats.distributions.gamma_gen object at 0x35ed890>>, <bound method gamma_gen.logsf of <scipy.stats.distributions.gamma_gen object at 0x35ed890>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), array(0.6862870211931944), array(2.2262410732082278), 0.73543589359791284, 2.0520236584037406, 500, 'genextremesample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), array(0.6862870211931944), array(2.2262410732082278), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, (-0.10000000000000001,), 'genextreme') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x35ed310>, 0.5, (-0.10000000000000001,), (0, 1), [<bound method genextreme_gen.pdf of <scipy.stats.distributions.genextreme_gen object at 0x35ed310>>, <bound method genextreme_gen.logpdf of <scipy.stats.distributions.genextreme_gen object at 0x35ed310>>, <bound method genextreme_gen.cdf of <scipy.stats.distributions.genextreme_gen object at 0x35ed310>>, <bound method genextreme_gen.logcdf of <scipy.stats.distributions.genextreme_gen object at 0x35ed310>>, <bound method genextreme_gen.logsf of <scipy.stats.distributions.genextreme_gen object at 0x35ed310>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), array(1.5702162249275609), array(0.060317549758582167), 1.5838942373483642, 0.055266524800612372, 500, 'gengammasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), array(1.5702162249275609), array(0.060317549758582167), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x35edd10>, 0.5, (4.4162385429431925, 3.1193091679242761), (0, 1), [<bound method gengamma_gen.pdf of <scipy.stats.distributions.gengamma_gen object at 0x35edd10>>, <bound method gengamma_gen.logpdf of <scipy.stats.distributions.gengamma_gen object at 0x35edd10>>, <bound method gengamma_gen.cdf of <scipy.stats.distributions.gengamma_gen object at 0x35edd10>>, <bound method gengamma_gen.logcdf of <scipy.stats.distributions.gengamma_gen object at 0x35edd10>>, <bound method gengamma_gen.logsf of <scipy.stats.distributions.gengamma_gen object at 0x35edd10>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), array(0.70597656450848101), array(0.12459765121103777), 0.72452837582593232, 0.12092761155861501, 500, 'genhalflogisticsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), array(0.70597656450848101), array(0.12459765121103777), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, (0.77274727809929322,), 'genhalflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>, 0.5, (0.77274727809929322,), (0, 1), [<bound method genhalflogistic_gen.pdf of <scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>>, <bound method genhalflogistic_gen.logpdf of <scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>>, <bound method genhalflogistic_gen.cdf of <scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>>, <bound method genhalflogistic_gen.logcdf of <scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>>, <bound method genhalflogistic_gen.logsf of <scipy.stats.distributions.genhalflogistic_gen object at 0x35edc10>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), array(-1.8996417990533176), array(8.5520107632574316), -1.7014478088458649, 6.8944989242387527, 500, 'genlogisticsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), array(-1.8996417990533176), array(8.5520107632574316), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, (0.41192440799679475,), 'genlogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>, 0.5, (0.41192440799679475,), (0, 1), [<bound method genlogistic_gen.pdf of <scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>>, <bound method genlogistic_gen.logpdf of <scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>>, <bound method genlogistic_gen.cdf of <scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>>, <bound method genlogistic_gen.logcdf of <scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>>, <bound method genlogistic_gen.logsf of <scipy.stats.distributions.genlogistic_gen object at 0x35e5e90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), array(1.1111111111111116), array(1.543209876543199), 1.1380337927959154, 1.4171766392561735, 500, 'genparetosample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), array(1.1111111111111116), array(1.543209876543199), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, (0.10000000000000001,), 'genpareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>, 0.5, (0.10000000000000001,), (0, 1), [<bound method genpareto_gen.pdf of <scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>>, <bound method genpareto_gen.logpdf of <scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>>, <bound method genpareto_gen.cdf of <scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>>, <bound method genpareto_gen.logcdf of <scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>>, <bound method genpareto_gen.logsf of <scipy.stats.distributions.genpareto_gen object at 0x35e5fd0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), array(1.6487212707001282), array(4.670774270471604), 1.6771449621521464, 3.4197840525811904, 500, 'gilbratsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), array(1.6487212707001282), array(4.670774270471604), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, (), 'gilbrat') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>, 0.5, (), (0, 1), [<bound method gilbrat_gen.pdf of <scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>>, <bound method gilbrat_gen.logpdf of <scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>>, <bound method gilbrat_gen.cdf of <scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>>, <bound method gilbrat_gen.logcdf of <scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>>, <bound method gilbrat_gen.logsf of <scipy.stats.distributions.gilbrat_gen object at 0x36a9c50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), array(0.61842381762891119), array(0.18616258957404036), 0.63690201333766361, 0.1817927873650822, 500, 'gompertzsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), array(0.61842381762891119), array(0.18616258957404036), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, (0.94743713075105251,), 'gompertz') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x35f70d0>, 0.5, (0.94743713075105251,), (0, 1), [<bound method gompertz_gen.pdf of <scipy.stats.distributions.gompertz_gen object at 0x35f70d0>>, <bound method gompertz_gen.logpdf of <scipy.stats.distributions.gompertz_gen object at 0x35f70d0>>, <bound method gompertz_gen.cdf of <scipy.stats.distributions.gompertz_gen object at 0x35f70d0>>, <bound method gompertz_gen.logcdf of <scipy.stats.distributions.gompertz_gen object at 0x35f70d0>>, <bound method gompertz_gen.logsf of <scipy.stats.distributions.gompertz_gen object at 0x35f70d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), array(-0.57721566490153287), array(1.6449340668482264), -0.48813688091010909, 1.3517840299292785, 500, 'gumbel_lsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), array(-0.57721566490153287), array(1.6449340668482264), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, (), 'gumbel_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>, 0.5, (), (0, 1), [<bound method gumbel_l_gen.pdf of <scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>>, <bound method gumbel_l_gen.logpdf of <scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>>, <bound method gumbel_l_gen.cdf of <scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>>, <bound method gumbel_l_gen.logcdf of <scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>>, <bound method gumbel_l_gen.logsf of <scipy.stats.distributions.gumbel_l_gen object at 0x35f74d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), array(0.57721566490153287), array(1.6449340668482264), 0.62929461732133063, 1.5374714001867402, 500, 'gumbel_rsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), array(0.57721566490153287), array(1.6449340668482264), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, (), 'gumbel_r') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>, 0.5, (), (0, 1), [<bound method gumbel_r_gen.pdf of <scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>>, <bound method gumbel_r_gen.logpdf of <scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>>, <bound method gumbel_r_gen.cdf of <scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>>, <bound method gumbel_r_gen.logcdf of <scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>>, <bound method gumbel_r_gen.logsf of <scipy.stats.distributions.gumbel_r_gen object at 0x35f7490>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), array(inf), array(inf), 4.8882174751255674, 944.7992816275538, 500, 'halfcauchysample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), array(inf), array(inf), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, (), 'halfcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>, 0.5, (), (0, 1), [<bound method halfcauchy_gen.pdf of <scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>>, <bound method halfcauchy_gen.logpdf of <scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>>, <bound method halfcauchy_gen.cdf of <scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>>, <bound method halfcauchy_gen.logcdf of <scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>>, <bound method halfcauchy_gen.logsf of <scipy.stats.distributions.halfcauchy_gen object at 0x35f7750>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), array(1.3862943611198906), array(1.3680560780236473), 1.4245028078549744, 1.300592278909374, 500, 'halflogisticsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), array(1.3862943611198906), array(1.3680560780236473), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, (), 'halflogistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x35f7890>, 0.5, (), (0, 1), [<bound method halflogistic_gen.pdf of <scipy.stats.distributions.halflogistic_gen object at 0x35f7890>>, <bound method halflogistic_gen.logpdf of <scipy.stats.distributions.halflogistic_gen object at 0x35f7890>>, <bound method halflogistic_gen.cdf of <scipy.stats.distributions.halflogistic_gen object at 0x35f7890>>, <bound method halflogistic_gen.logcdf of <scipy.stats.distributions.halflogistic_gen object at 0x35f7890>>, <bound method halflogistic_gen.logsf of <scipy.stats.distributions.halflogistic_gen object at 0x35f7890>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), array(0.79788456080286541), array(0.36338022763241862), 0.82379228338887001, 0.35647010671566165, 500, 'halfnormsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), array(0.79788456080286541), array(0.36338022763241862), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, (), 'halfnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>, 0.5, (), (0, 1), [<bound method halfnorm_gen.pdf of <scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>>, <bound method halfnorm_gen.logpdf of <scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>>, <bound method halfnorm_gen.cdf of <scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>>, <bound method halfnorm_gen.logcdf of <scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>>, <bound method halfnorm_gen.logsf of <scipy.stats.distributions.halfnorm_gen object at 0x35f7a10>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), array(0.0), array(2.4674011002723395), 0.090205448723165882, 2.1073463624281303, 500, 'hypsecantsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), array(0.0), array(2.4674011002723395), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, (), 'hypsecant') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>, 0.5, (), (0, 1), [<bound method hypsecant_gen.pdf of <scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>>, <bound method hypsecant_gen.logpdf of <scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>>, <bound method hypsecant_gen.cdf of <scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>>, <bound method hypsecant_gen.logcdf of <scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>>, <bound method hypsecant_gen.logsf of <scipy.stats.distributions.hypsecant_gen object at 0x35f7b90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), array(0.93729530609975309), array(13.131951625091871), 0.92929104026580023, 1.7220796371139628, 500, 'invgammasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), array(0.93729530609975309), array(13.131951625091871), 'invgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), 'invgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), 'invgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), 'invgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), 'invgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), 'invgamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, (2.0668996136993067,), 'invgamma') ... ok
test_continuous_basic.test_cont_basic('invgamma', (2.0668996136993067,), 0.01, array([ 0.21067307, 0.32595448, 0.29520302, 2.31382057, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>, 0.5, (2.0668996136993067,), (0, 1), [<bound method invgamma_gen.pdf of <scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>>, <bound method invgamma_gen.logpdf of <scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>>, <bound method invgamma_gen.cdf of <scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>>, <bound method invgamma_gen.logcdf of <scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>>, <bound method invgamma_gen.logsf of <scipy.stats.distributions.invgamma_gen object at 0x35f7dd0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), array(0.14546264555347513), array(0.0030778995751055637), 0.14868174489819427, 0.0028988442995278385, 500, 'invgausssample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), array(0.14546264555347513), array(0.0030778995751055637), 'invgauss') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), 'invgauss') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), 'invgauss') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), 'invgauss') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), 'invgauss') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), 'invgauss') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, (0.14546264555347513,), 'invgauss') ... ok
test_continuous_basic.test_cont_basic('invgauss', (0.14546264555347513,), 0.01, array([ 0.19059476, 0.23925666, 0.12168429, 0.1750588 , 0.0919458 , ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgauss_gen object at 0x35ff110>, 0.5, (0.14546264555347513,), (0, 1), [<bound method invgauss_gen.pdf of <scipy.stats.distributions.invgauss_gen object at 0x35ff110>>, <bound method invgauss_gen.logpdf of <scipy.stats.distributions.invgauss_gen object at 0x35ff110>>, <bound method invgauss_gen.cdf of <scipy.stats.distributions.invgauss_gen object at 0x35ff110>>, <bound method invgauss_gen.logcdf of <scipy.stats.distributions.invgauss_gen object at 0x35ff110>>, <bound method invgauss_gen.logsf of <scipy.stats.distributions.invgauss_gen object at 0x35ff110>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), array(0.2095207364338911), array(0.0026608544463240097), 0.21201214525530065, 0.0024950933582882384, 500, 'johnsonsbsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), array(0.2095207364338911), array(0.0026608544463240097), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
test_continuous_basic.test_cont_basic('johnsonsb', (4.3172675099141058, 3.1837781130785063), 0.01, array([ 0.1347666 , 0.16548787, 0.15849644, 0.29449495, 0.17234755, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>, 0.5, (4.3172675099141058, 3.1837781130785063), (0, 1), [<bound method johnsonsb_gen.pdf of <scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>>, <bound method johnsonsb_gen.logpdf of <scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>>, <bound method johnsonsb_gen.cdf of <scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>>, <bound method johnsonsb_gen.logcdf of <scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>>, <bound method johnsonsb_gen.logsf of <scipy.stats.distributions.johnsonsb_gen object at 0x35ff710>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), array(0.0), array(2.0), 0.081555808868726168, 1.6634734528663011, 500, 'laplacesample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), array(0.0), array(2.0), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, (), 'laplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x35ff290>, 0.5, (), (0, 1), [<bound method laplace_gen.pdf of <scipy.stats.distributions.laplace_gen object at 0x35ff290>>, <bound method laplace_gen.logpdf of <scipy.stats.distributions.laplace_gen object at 0x35ff290>>, <bound method laplace_gen.cdf of <scipy.stats.distributions.laplace_gen object at 0x35ff290>>, <bound method laplace_gen.logcdf of <scipy.stats.distributions.laplace_gen object at 0x35ff290>>, <bound method laplace_gen.logsf of <scipy.stats.distributions.laplace_gen object at 0x35ff290>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), array(inf), array(inf), 1522.2005254079072, 485955516.06046021, 500, 'levysample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), array(inf), array(inf), 'levy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), 'levy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), 'levy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), 'levy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), 'levy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), 'levy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, (), 'levy') ... ok
test_continuous_basic.test_cont_basic('levy', (), 0.01, array([ 2.70436559e-01, 6.14746137e-01, 5.04492446e-01, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x35ffcd0>, 0.5, (), (0, 1), [<bound method levy_gen.pdf of <scipy.stats.distributions.levy_gen object at 0x35ffcd0>>, <bound method levy_gen.logpdf of <scipy.stats.distributions.levy_gen object at 0x35ffcd0>>, <bound method levy_gen.cdf of <scipy.stats.distributions.levy_gen object at 0x35ffcd0>>, <bound method levy_gen.logcdf of <scipy.stats.distributions.levy_gen object at 0x35ffcd0>>, <bound method levy_gen.logsf of <scipy.stats.distributions.levy_gen object at 0x35ffcd0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), array(inf), array(inf), -94.225857577823859, 1311894.9063678393, 500, 'levy_lsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), array(inf), array(inf), 'levy_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), 'levy_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), 'levy_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), 'levy_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), 'levy_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), 'levy_l') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, (), 'levy_l') ... ok
test_continuous_basic.test_cont_basic('levy_l', (), 0.01, array([ -2.14103094e+02, -1.52414151e+01, -2.47965116e+01, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x35ffe50>, -0.5, (), (0, 1), [<bound method levy_l_gen.pdf of <scipy.stats.distributions.levy_l_gen object at 0x35ffe50>>, <bound method levy_l_gen.logpdf of <scipy.stats.distributions.levy_l_gen object at 0x35ffe50>>, <bound method levy_l_gen.cdf of <scipy.stats.distributions.levy_l_gen object at 0x35ffe50>>, <bound method levy_l_gen.logcdf of <scipy.stats.distributions.levy_l_gen object at 0x35ffe50>>, <bound method levy_l_gen.logsf of <scipy.stats.distributions.levy_l_gen object at 0x35ffe50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), array(-2.4617679388246976), array(6.8426502245978593), -2.3149954392978636, 5.9436315776861628, 500, 'loggammasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), array(-2.4617679388246976), array(6.8426502245978593), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, (0.41411931826052117,), 'loggamma') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x36a9450>, 0.5, (0.41411931826052117,), (0, 1), [<bound method loggamma_gen.pdf of <scipy.stats.distributions.loggamma_gen object at 0x36a9450>>, <bound method loggamma_gen.logpdf of <scipy.stats.distributions.loggamma_gen object at 0x36a9450>>, <bound method loggamma_gen.cdf of <scipy.stats.distributions.loggamma_gen object at 0x36a9450>>, <bound method loggamma_gen.logcdf of <scipy.stats.distributions.loggamma_gen object at 0x36a9450>>, <bound method loggamma_gen.logsf of <scipy.stats.distributions.loggamma_gen object at 0x36a9450>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), array(0.0), array(3.2898681336964528), 0.10349036101100972, 2.8774655378842309, 500, 'logisticsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), array(0.0), array(3.2898681336964528), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, (), 'logistic') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x36a9290>, 0.5, (), (0, 1), [<bound method logistic_gen.pdf of <scipy.stats.distributions.logistic_gen object at 0x36a9290>>, <bound method logistic_gen.logpdf of <scipy.stats.distributions.logistic_gen object at 0x36a9290>>, <bound method logistic_gen.cdf of <scipy.stats.distributions.logistic_gen object at 0x36a9290>>, <bound method logistic_gen.logcdf of <scipy.stats.distributions.logistic_gen object at 0x36a9290>>, <bound method logistic_gen.logsf of <scipy.stats.distributions.logistic_gen object at 0x36a9290>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), array(1.1045330480739983), array(0.38917293304477574), 1.1159779194372486, 0.30590858699075046, 500, 'loglaplacesample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), array(1.1045330480739983), array(0.38917293304477574), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, (3.2505926592051435,), 'loglaplace') ... ok
test_continuous_basic.test_cont_basic('loglaplace', (3.2505926592051435,), 0.01, array([ 0.50564412, 0.75686013, 0.70317403, 1.8978091 , 0.80674887, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x36a9650>, 0.5, (3.2505926592051435,), (0, 1), [<bound method loglaplace_gen.pdf of <scipy.stats.distributions.loglaplace_gen object at 0x36a9650>>, <bound method loglaplace_gen.logpdf of <scipy.stats.distributions.loglaplace_gen object at 0x36a9650>>, <bound method loglaplace_gen.cdf of <scipy.stats.distributions.loglaplace_gen object at 0x36a9650>>, <bound method loglaplace_gen.logcdf of <scipy.stats.distributions.loglaplace_gen object at 0x36a9650>>, <bound method loglaplace_gen.logsf of <scipy.stats.distributions.loglaplace_gen object at 0x36a9650>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), array(1.5757871665018548), array(3.6827062109137709), 1.6056555414792437, 2.7977370822350083, 500, 'lognormsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), array(1.5757871665018548), array(3.6827062109137709), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, (0.95368226960575331,), 'lognorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x36a9a10>, 0.5, (0.95368226960575331,), (0, 1), [<bound method lognorm_gen.pdf of <scipy.stats.distributions.lognorm_gen object at 0x36a9a10>>, <bound method lognorm_gen.logpdf of <scipy.stats.distributions.lognorm_gen object at 0x36a9a10>>, <bound method lognorm_gen.cdf of <scipy.stats.distributions.lognorm_gen object at 0x36a9a10>>, <bound method lognorm_gen.logcdf of <scipy.stats.distributions.lognorm_gen object at 0x36a9a10>>, <bound method lognorm_gen.logsf of <scipy.stats.distributions.lognorm_gen object at 0x36a9a10>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), array(1.1400690695795155), array(inf), 1.1053332551165382, 6.2566550878316187, 500, 'lomaxsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), array(1.1400690695795155), array(inf), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, (1.8771398388773268,), 'lomax') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x36bf0d0>, 0.5, (1.8771398388773268,), (0, 1), [<bound method lomax_gen.pdf of <scipy.stats.distributions.lomax_gen object at 0x36bf0d0>>, <bound method lomax_gen.logpdf of <scipy.stats.distributions.lomax_gen object at 0x36bf0d0>>, <bound method lomax_gen.cdf of <scipy.stats.distributions.lomax_gen object at 0x36bf0d0>>, <bound method lomax_gen.logcdf of <scipy.stats.distributions.lomax_gen object at 0x36bf0d0>>, <bound method lomax_gen.logsf of <scipy.stats.distributions.lomax_gen object at 0x36bf0d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), array(1.5957691216057308), array(0.45352091052967447), 1.5730574489749882, 0.40085884223991197, 500, 'maxwellsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), array(1.5957691216057308), array(0.45352091052967447), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, (), 'maxwell') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x36a9c90>, 0.5, (), (0, 1), [<bound method maxwell_gen.pdf of <scipy.stats.distributions.maxwell_gen object at 0x36a9c90>>, <bound method maxwell_gen.logpdf of <scipy.stats.distributions.maxwell_gen object at 0x36a9c90>>, <bound method maxwell_gen.cdf of <scipy.stats.distributions.maxwell_gen object at 0x36a9c90>>, <bound method maxwell_gen.logcdf of <scipy.stats.distributions.maxwell_gen object at 0x36a9c90>>, <bound method maxwell_gen.logsf of <scipy.stats.distributions.maxwell_gen object at 0x36a9c90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), array(0.9751907537016975), array(0.049002993894715186), 0.9867563078157402, 0.045501916873606163, 500, 'nakagamisample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), array(0.9751907537016975), array(0.049002993894715186), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, (4.9673794866666237,), 'nakagami') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x36b90d0>, 0.5, (4.9673794866666237,), (0, 1), [<bound method nakagami_gen.pdf of <scipy.stats.distributions.nakagami_gen object at 0x36b90d0>>, <bound method nakagami_gen.logpdf of <scipy.stats.distributions.nakagami_gen object at 0x36b90d0>>, <bound method nakagami_gen.cdf of <scipy.stats.distributions.nakagami_gen object at 0x36b90d0>>, <bound method nakagami_gen.logcdf of <scipy.stats.distributions.nakagami_gen object at 0x36b90d0>>, <bound method nakagami_gen.logsf of <scipy.stats.distributions.nakagami_gen object at 0x36b90d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), array(1.0966313767196905), array(0.19835325341303081), 1.0740685247899553, 0.19118274095379129, 500, 'ncfsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), array(1.0966313767196905), array(0.19835325341303081), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, (27, 27, 0.41578441799226107), 'ncf') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x36b9390>, 0.5, (27, 27, 0.41578441799226107), (0, 1), [<bound method ncf_gen.pdf of <scipy.stats.distributions.ncf_gen object at 0x36b9390>>, <bound method ncf_gen.logpdf of <scipy.stats.distributions.ncf_gen object at 0x36b9390>>, <bound method ncf_gen.cdf of <scipy.stats.distributions.ncf_gen object at 0x36b9390>>, <bound method ncf_gen.logcdf of <scipy.stats.distributions.ncf_gen object at 0x36b9390>>, <bound method ncf_gen.logsf of <scipy.stats.distributions.ncf_gen object at 0x36b9390>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), array(0.25436732738327772), array(1.1694163414603564), 0.29200805409199576, 1.2103533692156592, 500, 'nctsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), array(0.25436732738327772), array(1.1694163414603564), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, (14, 0.24045031331198066), 'nct') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x36b9c90>, 0.5, (14, 0.24045031331198066), (0, 1), [<bound method nct_gen.pdf of <scipy.stats.distributions.nct_gen object at 0x36b9c90>>, <bound method nct_gen.logpdf of <scipy.stats.distributions.nct_gen object at 0x36b9c90>>, <bound method nct_gen.cdf of <scipy.stats.distributions.nct_gen object at 0x36b9c90>>, <bound method nct_gen.logcdf of <scipy.stats.distributions.nct_gen object at 0x36b9c90>>, <bound method nct_gen.logsf of <scipy.stats.distributions.nct_gen object at 0x36b9c90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), array(22.056046597511642), array(46.224186390046569), 21.965924328314692, 47.626355015322346, 500, 'ncx2sample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), array(22.056046597511642), array(46.224186390046569), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, (21, 1.0560465975116415), 'ncx2') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x36b9490>, 0.5, (21, 1.0560465975116415), (0, 1), [<bound method ncx2_gen.pdf of <scipy.stats.distributions.ncx2_gen object at 0x36b9490>>, <bound method ncx2_gen.logpdf of <scipy.stats.distributions.ncx2_gen object at 0x36b9490>>, <bound method ncx2_gen.cdf of <scipy.stats.distributions.ncx2_gen object at 0x36b9490>>, <bound method ncx2_gen.logcdf of <scipy.stats.distributions.ncx2_gen object at 0x36b9490>>, <bound method ncx2_gen.logsf of <scipy.stats.distributions.ncx2_gen object at 0x36b9490>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), array(0.0), array(1.0), 0.035445900332699912, 1.0338474210363131, 500, 'normsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), array(0.0), array(1.0), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, (), 'norm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x35ca350>, 0.5, (), (0, 1), [<bound method norm_gen.pdf of <scipy.stats.distributions.norm_gen object at 0x35ca350>>, <bound method norm_gen.logpdf of <scipy.stats.distributions.norm_gen object at 0x35ca350>>, <bound method norm_gen.cdf of <scipy.stats.distributions.norm_gen object at 0x35ca350>>, <bound method norm_gen.logcdf of <scipy.stats.distributions.norm_gen object at 0x35ca350>>, <bound method norm_gen.logsf of <scipy.stats.distributions.norm_gen object at 0x35ca350>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), array(1.6166305764162521), array(1.6034057205287133), 1.6175136021410468, 0.99652438237091601, 500, 'paretosample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), array(1.6166305764162521), array(1.6034057205287133), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, (2.621716532144454,), 'pareto') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x36b95d0>, 1.5, (2.621716532144454,), (0, 1), [<bound method pareto_gen.pdf of <scipy.stats.distributions.pareto_gen object at 0x36b95d0>>, <bound method pareto_gen.logpdf of <scipy.stats.distributions.pareto_gen object at 0x36b95d0>>, <bound method pareto_gen.cdf of <scipy.stats.distributions.pareto_gen object at 0x36b95d0>>, <bound method pareto_gen.logcdf of <scipy.stats.distributions.pareto_gen object at 0x36b95d0>>, <bound method pareto_gen.logsf of <scipy.stats.distributions.pareto_gen object at 0x36b95d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), array(0.0), array(1.0), -0.045157918926598602, 0.90343127909740151, 500, 'pearson3sample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), array(0.0), array(1.0), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, (0.10000000000000001,), 'pearson3') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pearson3_gen object at 0x36bf490>, 0.5, (0.10000000000000001,), (0, 1), [<bound method pearson3_gen.pdf of <scipy.stats.distributions.pearson3_gen object at 0x36bf490>>, <bound method pearson3_gen.logpdf of <scipy.stats.distributions.pearson3_gen object at 0x36bf490>>, <bound method pearson3_gen.cdf of <scipy.stats.distributions.pearson3_gen object at 0x36bf490>>, <bound method pearson3_gen.logcdf of <scipy.stats.distributions.pearson3_gen object at 0x36bf490>>, <bound method pearson3_gen.logsf of <scipy.stats.distributions.pearson3_gen object at 0x36bf490>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), array(0.62393479469353574), array(0.06412487003483977), 0.63825155628294095, 0.060978170226970378, 500, 'powerlawsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), array(0.62393479469353574), array(0.06412487003483977), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, (1.6591133289905851,), 'powerlaw') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>, 0.5, (1.6591133289905851,), (0, 1), [<bound method powerlaw_gen.pdf of <scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>>, <bound method powerlaw_gen.logpdf of <scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>>, <bound method powerlaw_gen.cdf of <scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>>, <bound method powerlaw_gen.logcdf of <scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>>, <bound method powerlaw_gen.logsf of <scipy.stats.distributions.powerlaw_gen object at 0x36bf6d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), array(-1.0934378551735346), array(0.46999722851188852), -1.0525819131267065, 0.42074144479195152, 500, 'powernormsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), array(-1.0934378551735346), array(0.46999722851188852), 'powernorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), 'powernorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), 'powernorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), 'powernorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), 'powernorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), 'powernorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, (4.4453652254590779,), 'powernorm') ... ok
test_continuous_basic.test_cont_basic('powernorm', (4.4453652254590779,), 0.01, array([-2.24064782, -1.64936365, -1.7714141 , -0.0892759 , -1.53556507, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>, 0.5, (4.4453652254590779,), (0, 1), [<bound method powernorm_gen.pdf of <scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>>, <bound method powernorm_gen.logpdf of <scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>>, <bound method powernorm_gen.cdf of <scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>>, <bound method powernorm_gen.logcdf of <scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>>, <bound method powernorm_gen.logsf of <scipy.stats.distributions.powernorm_gen object at 0x36bf7d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), array(1.2533141373155001), array(0.42920367320510344), 1.2828507672382079, 0.40989692335624117, 500, 'rayleighsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), array(1.2533141373155001), array(0.42920367320510344), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, (), 'rayleigh') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>, 0.5, (), (0, 1), [<bound method rayleigh_gen.pdf of <scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>>, <bound method rayleigh_gen.logpdf of <scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>>, <bound method rayleigh_gen.cdf of <scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>>, <bound method rayleigh_gen.logcdf of <scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>>, <bound method rayleigh_gen.logsf of <scipy.stats.distributions.rayleigh_gen object at 0x36bfbd0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), array(0.19667848552072986), array(0.060882307287375481), 0.20609257124548058, 0.06052621443358297, 500, 'reciprocalsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), array(0.19667848552072986), array(0.060882307287375481), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x36c3090>, 0.5, (0.0062309367010521255, 1.0062309367010522), (0, 1), [<bound method reciprocal_gen.pdf of <scipy.stats.distributions.reciprocal_gen object at 0x36c3090>>, <bound method reciprocal_gen.logpdf of <scipy.stats.distributions.reciprocal_gen object at 0x36c3090>>, <bound method reciprocal_gen.cdf of <scipy.stats.distributions.reciprocal_gen object at 0x36c3090>>, <bound method reciprocal_gen.logcdf of <scipy.stats.distributions.reciprocal_gen object at 0x36c3090>>, <bound method reciprocal_gen.logsf of <scipy.stats.distributions.reciprocal_gen object at 0x36c3090>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), array(0.0), array(3.6905172081719186), -0.096308839423193945, 4.1822620019789927, 500, 'tsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), array(0.0), array(3.6905172081719186), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, (2.7433514990818093,), 't') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x36b9710>, 0.5, (2.7433514990818093,), (0, 1), [<bound method t_gen.pdf of <scipy.stats.distributions.t_gen object at 0x36b9710>>, <bound method t_gen.logpdf of <scipy.stats.distributions.t_gen object at 0x36b9710>>, <bound method t_gen.cdf of <scipy.stats.distributions.t_gen object at 0x36b9710>>, <bound method t_gen.logcdf of <scipy.stats.distributions.t_gen object at 0x36b9710>>, <bound method t_gen.logsf of <scipy.stats.distributions.t_gen object at 0x36b9710>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), array(0.38595009941509401), array(0.048170356578380126), 0.39670521794704355, 0.047257378789142226, 500, 'triangsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), array(0.38595009941509401), array(0.048170356578380126), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, (0.15785029824528218,), 'triang') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x36c3990>, 0.5, (0.15785029824528218,), (0, 1), [<bound method triang_gen.pdf of <scipy.stats.distributions.triang_gen object at 0x36c3990>>, <bound method triang_gen.logpdf of <scipy.stats.distributions.triang_gen object at 0x36c3990>>, <bound method triang_gen.cdf of <scipy.stats.distributions.triang_gen object at 0x36c3990>>, <bound method triang_gen.logcdf of <scipy.stats.distributions.triang_gen object at 0x36c3990>>, <bound method triang_gen.logsf of <scipy.stats.distributions.triang_gen object at 0x36c3990>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), array(0.95654169346841034), array(0.79425834443323384), 0.98643731816069158, 0.76187624238021057, 500, 'truncexponsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), array(0.95654169346841034), array(0.79425834443323384), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, (4.6907725456810478,), 'truncexpon') ... ok
test_continuous_basic.test_cont_basic('truncexpon', (4.6907725456810478,), 0.01, array([ 0.05549849, 0.22352616, 0.17161765, 2.64638353, 0.28302056, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>, 0.5, (4.6907725456810478,), (0, 1), [<bound method truncexpon_gen.pdf of <scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>>, <bound method truncexpon_gen.logpdf of <scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>>, <bound method truncexpon_gen.cdf of <scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>>, <bound method truncexpon_gen.logcdf of <scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>>, <bound method truncexpon_gen.logsf of <scipy.stats.distributions.truncexpon_gen object at 0x36c3b50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), array(0.24256013977032279), array(0.6322152443797493), 0.27881914654600104, 0.61146479078324167, 500, 'truncnormsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), array(0.24256013977032279), array(0.6322152443797493), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic('truncnorm', (-1.0978730080013919, 2.7306754109031979), 0.01, array([ -9.03888658e-01, -4.95474499e-01, -6.03402670e-01, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, 0.5, (-1.0978730080013919, 2.7306754109031979), (0, 1), [<bound method truncnorm_gen.pdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.logpdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.cdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.logcdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.logsf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), array(0.78405191516382167), array(0.22915093676528964), 0.80645844104152153, 0.22714480219714528, 500, 'truncnormsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), array(0.78405191516382167), array(0.22915093676528964), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, (0.10000000000000001, 2.0), 'truncnorm') ... ok
test_continuous_basic.test_cont_basic('truncnorm', (0.10000000000000001, 2.0), 0.01, array([ 0.16025914, 0.32724276, 0.27788027, 1.64484107, 0.38167675, ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>, 0.5, (0.10000000000000001, 2.0), (0, 1), [<bound method truncnorm_gen.pdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.logpdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.cdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.logcdf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>, <bound method truncnorm_gen.logsf of <scipy.stats.distributions.truncnorm_gen object at 0x36c3f50>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), array(0.0), array(0.02687245442325796), 0.0087410571447445844, 0.026136119132199764, 500, 'tukeylambdasample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), array(0.0), array(0.02687245442325796), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, (3.1321477856738267,), 'tukeylambda') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>, 0.29999999999999999, (3.1321477856738267,), (0, 1), [<bound method tukeylambda_gen.pdf of <scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>>, <bound method tukeylambda_gen.logpdf of <scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>>, <bound method tukeylambda_gen.cdf of <scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>>, <bound method tukeylambda_gen.logcdf of <scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>>, <bound method tukeylambda_gen.logsf of <scipy.stats.distributions.tukeylambda_gen object at 0x36ca0d0>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), array(0.5), array(0.083333333333333329), 0.5149356703175092, 0.08247875218331209, 500, 'uniformsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), array(0.5), array(0.083333333333333329), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, (), 'uniform') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x36ca490>, 0.5, (), (0, 1), [<bound method uniform_gen.pdf of <scipy.stats.distributions.uniform_gen object at 0x36ca490>>, <bound method uniform_gen.logpdf of <scipy.stats.distributions.uniform_gen object at 0x36ca490>>, <bound method uniform_gen.cdf of <scipy.stats.distributions.uniform_gen object at 0x36ca490>>, <bound method uniform_gen.logcdf of <scipy.stats.distributions.uniform_gen object at 0x36ca490>>, <bound method uniform_gen.logsf of <scipy.stats.distributions.uniform_gen object at 0x36ca490>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x36ca6d0>, (), array(1.0), array(1.0), 1.0411493806671195, 1.1145804454531147, 500, 'waldsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x36ca6d0>, (), array(1.0), array(1.0), 'wald') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x36ca6d0>, (), 'wald') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x36ca6d0>, (), 'wald') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x36ca6d0>, (), 'wald') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), array(-0.89129676887660936), array(0.11369305518071715), -0.87141717390154927, 0.10417967598316791, 500, 'weibull_maxsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), array(-0.89129676887660936), array(0.11369305518071715), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, (2.8687961709100187,), 'weibull_max') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>, -0.5, (2.8687961709100187,), (0, 1), [<bound method frechet_l_gen.pdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>>, <bound method frechet_l_gen.logpdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>>, <bound method frechet_l_gen.cdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>>, <bound method frechet_l_gen.logcdf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>>, <bound method frechet_l_gen.logsf of <scipy.stats.distributions.frechet_l_gen object at 0x35e5c90>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), array(0.8896162979747505), array(0.26510662289002973), 0.91166951756373482, 0.2537876833893653, 500, 'weibull_minsample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), array(0.8896162979747505), array(0.26510662289002973), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, (1.7866166930421596,), 'weibull_min') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x35e5850>, 0.5, (1.7866166930421596,), (0, 1), [<bound method frechet_r_gen.pdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5850>>, <bound method frechet_r_gen.logpdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5850>>, <bound method frechet_r_gen.cdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5850>>, <bound method frechet_r_gen.logcdf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5850>>, <bound method frechet_r_gen.logsf of <scipy.stats.distributions.frechet_r_gen object at 0x35e5850>>]) ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), array(3.1415926535897927), array(3.4151322438845035), 3.2366450690320034, 3.3881817541701791, 500, 'wrapcauchysample mean test') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), array(3.1415926535897927), array(3.4151322438845035), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, (0.031071279018614728,), 'wrapcauchy') ... ok
test_continuous_basic.test_cont_basic('wrapcauchy', (0.031071279018614728,), 0.01, array([ 0.32208266, 1.21142156, 0.94861337, 5.91479179, 1.5010211 , ... ok
test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>, 0.5, (0.031071279018614728,), (0, 1), [<bound method wrapcauchy_gen.pdf of <scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>>, <bound method wrapcauchy_gen.logpdf of <scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>>, <bound method wrapcauchy_gen.cdf of <scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>>, <bound method wrapcauchy_gen.logcdf of <scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>>, <bound method wrapcauchy_gen.logsf of <scipy.stats.distributions.wrapcauchy_gen object at 0x36ca8d0>>]) ... ok
test_continuous_extra.test_540_567 ... ok
test_continuous_extra.test_erlang_runtimewarning ... ok
test_discrete_basic.test_discrete_basic(0.29999999999999999, array(0.29999999999999999), 'bernoulli sample mean test') ... ok
test_discrete_basic.test_discrete_basic(0.20999999999999627, array(0.20999999999999999), 'bernoulli sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, (0.29999999999999999,), 'bernoulli cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, (0.29999999999999999,), array([0, 1]), 'bernoulli cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, (0.29999999999999999,), 'bernoulli pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, (0.29999999999999999,), 'bernoulli oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, (0.29999999999999999,), -1.2380952380951449, 0.87287156094400487, 'bernoulli skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, (0.29999999999999999,), array([0, 0, 0, ..., 1, 0, 0]), 0.01, 'bernoulli chisquare') ... ok
test_discrete_basic.test_discrete_basic(2.0015000000000001, array(2.0), 'binom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(1.1854977500000026, array(1.2), 'binom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, (5, 0.40000000000000002), 'binom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, (5, 0.40000000000000002), array([0, 1, 2, 3, 4, 5]), 'binom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, (5, 0.40000000000000002), 'binom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, (5, 0.40000000000000002), 'binom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, (5, 0.40000000000000002), -0.26248929225026352, 0.28057933666556623, 'binom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, (5, 0.40000000000000002), array([2, 2, 2, ..., 4, 1, 3]), 0.01, 'binom chisquare') ... ok
test_discrete_basic.test_discrete_basic(0.32900000000000001, array(0.32731081784804011), 'boltzmann sample mean test') ... ok
test_discrete_basic.test_discrete_basic(0.43975900000001117, array(0.4344431884043245), 'boltzmann sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, (1.3999999999999999, 19), 'boltzmann cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, (1.3999999999999999, 19), array([0, 1, 2, 3, 4]), 'boltzmann cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, (1.3999999999999999, 19), 'boltzmann pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, (1.3999999999999999, 19), 'boltzmann oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, (1.3999999999999999, 19), 6.7133652484343216, 2.418691392797208, 'boltzmann skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, (1.3999999999999999, 19), array([0, 0, 0, ..., 2, 0, 0]), 0.01, 'boltzmann chisquare') ... ok
test_discrete_basic.test_discrete_basic(0.0070000000000000001, array(0.0), 'dlaplace sample mean test') ... ok
test_discrete_basic.test_discrete_basic(2.9319510000000588, array(2.9635341891843718), 'dlaplace sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>, (0.80000000000000004,), 'dlaplace cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>, (0.80000000000000004,), array([-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7]), 'dlaplace cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>, (0.80000000000000004,), 'dlaplace pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>, (0.80000000000000004,), 'dlaplace oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>, (0.80000000000000004,), 3.0660776822072453, 0.021996158609059947, 'dlaplace skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(1.9870000000000001, array(2.0), 'geom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(2.0098310000000303, array(2.0), 'geom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, (0.5,), 'geom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, (0.5,), array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), 'geom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, (0.5,), 'geom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, (0.5,), 'geom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, (0.5,), 5.1935883716655766, 2.0476504362662378, 'geom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, (0.5,), array([1, 1, 2, ..., 6, 1, 2]), 0.01, 'geom chisquare') ... ok
test_discrete_basic.test_discrete_basic(2.3860000000000001, array(2.4000000000000004), 'hypergeom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(1.1500039999999776, array(1.1917241379310344), 'hypergeom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (30, 12, 6), 'hypergeom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (30, 12, 6), array([0, 1, 2, 3, 4, 5, 6]), 'hypergeom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (30, 12, 6), 'hypergeom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (30, 12, 6), 'hypergeom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (30, 12, 6), -0.29686916362552029, 0.020906577365969316, 'hypergeom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (30, 12, 6), array([1, 1, 4, ..., 3, 2, 2]), 0.01, 'hypergeom chisquare') ... ok
test_discrete_basic.test_discrete_basic(1.724, array(1.7142857142857142), 'hypergeom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(0.65282400000000196, array(0.66122448979591841), 'hypergeom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 3, 12), 'hypergeom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 3, 12), array([0, 1, 2, 3]), 'hypergeom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 3, 12), 'hypergeom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 3, 12), 'hypergeom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 3, 12), -0.46243472564588117, -0.18093529905213196, 'hypergeom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 3, 12), array([2, 3, 2, ..., 2, 2, 1]), 0.01, 'hypergeom chisquare') ... ok
test_discrete_basic.test_discrete_basic(9.4184999999999999, array(9.4285714285714288), 'hypergeom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(0.68435774999998666, array(0.67346938775510201), 'hypergeom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 18, 11), 'hypergeom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 18, 11), array([ 8, 9, 10, 11]), 'hypergeom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 18, 11), 'hypergeom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 18, 11), 'hypergeom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 18, 11), -0.53396352457617935, 0.093601755841816861, 'hypergeom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, (21, 18, 11), array([ 9, 8, 9, ..., 10, 10, 10]), 0.01, 'hypergeom chisquare') ... ok
test_discrete_basic.test_discrete_basic(1.635, array(1.637035001905937), 'logser sample mean test') ... ok
test_discrete_basic.test_discrete_basic(1.325775000000023, array(1.4127039072996714), 'logser sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, (0.59999999999999998,), 'logser cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, (0.59999999999999998,), array([1, 2, 3, 4, 5, 6, 7, 8, 9]), 'logser cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, (0.59999999999999998,), 'logser pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, (0.59999999999999998,), 'logser oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, (0.59999999999999998,), 7.559198377977479, 2.4947797038220592, 'logser skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, (0.59999999999999998,), array([1, 1, 1, ..., 1, 1, 4]), 0.01, 'logser chisquare') ... ok
test_discrete_basic.test_discrete_basic(4.9210000000000003, array(5.0), 'nbinom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(9.4787590000000037, array(10.0), 'nbinom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (5, 0.5), 'nbinom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (5, 0.5), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (5, 0.5), 'nbinom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (5, 0.5), 'nbinom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (5, 0.5), 1.5000586959708402, 0.97358518373019021, 'nbinom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (5, 0.5), array([0, 2, 6, ..., 3, 3, 3]), 0.01, 'nbinom chisquare') ... ok
test_discrete_basic.test_discrete_basic(0.58399999999999996, array(0.60000000000000009), 'nbinom sample mean test') ... ok
test_discrete_basic.test_discrete_basic(1.4729440000000598, array(1.5000000000000002), 'nbinom sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (0.40000000000000002, 0.40000000000000002), 'nbinom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (0.40000000000000002, 0.40000000000000002), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12]), 'nbinom cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (0.40000000000000002, 0.40000000000000002), 'nbinom pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (0.40000000000000002, 0.40000000000000002), 'nbinom oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (0.40000000000000002, 0.40000000000000002), 13.929082276070467, 3.2071528858780165, 'nbinom skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, (0.40000000000000002, 0.40000000000000002), array([0, 0, 0, ..., 0, 0, 0]), 0.01, 'nbinom chisquare') ... ok
test_discrete_basic.test_discrete_basic(1.496, array(1.5031012098113492), 'planck sample mean test') ... ok
test_discrete_basic.test_discrete_basic(3.8119840000000167, array(3.7624144567476914), 'planck sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, (0.51000000000000001,), 'planck cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, (0.51000000000000001,), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), 'planck cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, (0.51000000000000001,), 'planck pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, (0.51000000000000001,), 'planck oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, (0.51000000000000001,), 5.0921201134828475, 1.9924056300476671, 'planck skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, (0.51000000000000001,), array([1, 1, 1, ..., 7, 0, 2]), 0.01, 'planck chisquare') ... ok
test_discrete_basic.test_discrete_basic(0.58550000000000002, array(0.59999999999999998), 'poisson sample mean test') ... ok
test_discrete_basic.test_discrete_basic(0.59768974999998681, array(0.59999999999999998), 'poisson sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, (0.59999999999999998,), 'poisson cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, (0.59999999999999998,), array([0, 1, 2, 3, 4, 5]), 'poisson cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, (0.59999999999999998,), 'poisson pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, (0.59999999999999998,), 'poisson oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, (0.59999999999999998,), 1.9406814436782422, 1.3589585241917534, 'poisson skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, (0.59999999999999998,), array([0, 0, 0, ..., 1, 0, 0]), 0.01, 'poisson chisquare') ... ok
test_discrete_basic.test_discrete_basic(18.4725, array(18.5), 'randint sample mean test') ... ok
test_discrete_basic.test_discrete_basic(48.800243749999929, array(47.916666666666664), 'randint sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, (7, 31), 'randint cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, (7, 31), array([ 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, (7, 31), 'randint pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, (7, 31), 'randint oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, (7, 31), -1.2115060412211844, -0.025412774105826198, 'randint skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, (7, 31), array([27, 10, 15, ..., 16, 9, 17]), 0.01, 'randint chisquare') ... ok
test_discrete_basic.test_discrete_basic(7.0019999999999998, array(7.0), 'skellam sample mean test') ... ok
test_discrete_basic.test_discrete_basic(22.550995999999991, array(23.0), 'skellam sample var test') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x36dd790>, (15, 8), 'skellam cdf_ppf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x36dd790>, (15, 8), array([-10, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x36dd790>, (15, 8), 'skellam pmf_cdf') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x36dd790>, (15, 8), 'skellam oth') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x36dd790>, (15, 8), 0.11554402415317133, 0.10806520422790773, 'skellam skew_kurt') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x36dd790>, (15, 8), array([ 4, 6, 10, ..., 5, 14, 15]), 0.01, 'skellam chisquare') ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>, 0, (0.29999999999999999,), (0,), [<bound method bernoulli_gen.pmf of <scipy.stats.distributions.bernoulli_gen object at 0x36cae50>>, <bound method bernoulli_gen.logpmf of <scipy.stats.distributions.bernoulli_gen object at 0x36cae50>>, <bound method bernoulli_gen.cdf of <scipy.stats.distributions.bernoulli_gen object at 0x36cae50>>, <bound method bernoulli_gen.logcdf of <scipy.stats.distributions.bernoulli_gen object at 0x36cae50>>, <bound method bernoulli_gen.logsf of <scipy.stats.distributions.bernoulli_gen object at 0x36cae50>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x36cae50>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>, 1, (5, 0.40000000000000002), (0,), [<bound method binom_gen.pmf of <scipy.stats.distributions.binom_gen object at 0x36caa90>>, <bound method binom_gen.logpmf of <scipy.stats.distributions.binom_gen object at 0x36caa90>>, <bound method binom_gen.cdf of <scipy.stats.distributions.binom_gen object at 0x36caa90>>, <bound method binom_gen.logcdf of <scipy.stats.distributions.binom_gen object at 0x36caa90>>, <bound method binom_gen.logsf of <scipy.stats.distributions.binom_gen object at 0x36caa90>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x36caa90>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>, 1, (1.3999999999999999, 19), (0,), [<bound method boltzmann_gen.pmf of <scipy.stats.distributions.boltzmann_gen object at 0x36da210>>, <bound method boltzmann_gen.logpmf of <scipy.stats.distributions.boltzmann_gen object at 0x36da210>>, <bound method boltzmann_gen.cdf of <scipy.stats.distributions.boltzmann_gen object at 0x36da210>>, <bound method boltzmann_gen.logcdf of <scipy.stats.distributions.boltzmann_gen object at 0x36da210>>, <bound method boltzmann_gen.logsf of <scipy.stats.distributions.boltzmann_gen object at 0x36da210>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x36da210>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>, 1, (0.80000000000000004,), (0,), [<bound method dlaplace_gen.pmf of <scipy.stats.distributions.dlaplace_gen object at 0x36dd110>>, <bound method dlaplace_gen.logpmf of <scipy.stats.distributions.dlaplace_gen object at 0x36dd110>>, <bound method dlaplace_gen.cdf of <scipy.stats.distributions.dlaplace_gen object at 0x36dd110>>, <bound method dlaplace_gen.logcdf of <scipy.stats.distributions.dlaplace_gen object at 0x36dd110>>, <bound method dlaplace_gen.logsf of <scipy.stats.distributions.dlaplace_gen object at 0x36dd110>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x36dd110>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>, 1, (0.5,), (0,), [<bound method geom_gen.pmf of <scipy.stats.distributions.geom_gen object at 0x36da110>>, <bound method geom_gen.logpmf of <scipy.stats.distributions.geom_gen object at 0x36da110>>, <bound method geom_gen.cdf of <scipy.stats.distributions.geom_gen object at 0x36da110>>, <bound method geom_gen.logcdf of <scipy.stats.distributions.geom_gen object at 0x36da110>>, <bound method geom_gen.logsf of <scipy.stats.distributions.geom_gen object at 0x36da110>>]) ... /global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/scipy/stats/distributions.py:7357: DeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future
return (1-p)**(k-1) * p
/global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/scipy/stats/distributions.py:7357: DeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future
return (1-p)**(k-1) * p
ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x36da110>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>, 4, (30, 12, 6), (0,), [<bound method hypergeom_gen.pmf of <scipy.stats.distributions.hypergeom_gen object at 0x36da750>>, <bound method hypergeom_gen.logpmf of <scipy.stats.distributions.hypergeom_gen object at 0x36da750>>, <bound method hypergeom_gen.cdf of <scipy.stats.distributions.hypergeom_gen object at 0x36da750>>, <bound method hypergeom_gen.logcdf of <scipy.stats.distributions.hypergeom_gen object at 0x36da750>>, <bound method hypergeom_gen.logsf of <scipy.stats.distributions.hypergeom_gen object at 0x36da750>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x36da750>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>, 1, (0.59999999999999998,), (0,), [<bound method logser_gen.pmf of <scipy.stats.distributions.logser_gen object at 0x36da510>>, <bound method logser_gen.logpmf of <scipy.stats.distributions.logser_gen object at 0x36da510>>, <bound method logser_gen.cdf of <scipy.stats.distributions.logser_gen object at 0x36da510>>, <bound method logser_gen.logcdf of <scipy.stats.distributions.logser_gen object at 0x36da510>>, <bound method logser_gen.logsf of <scipy.stats.distributions.logser_gen object at 0x36da510>>]) ... /global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/scipy/stats/distributions.py:7525: DeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future
return -p**k * 1.0 / k / log(1 - p)
/global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/scipy/stats/distributions.py:7525: DeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future
return -p**k * 1.0 / k / log(1 - p)
/global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/scipy/stats/distributions.py:7525: DeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future
return -p**k * 1.0 / k / log(1 - p)
/global/homes/b/bpartrid/mic/python/_install/lib/python2.7/site-packages/scipy/stats/distributions.py:7525: DeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future
return -p**k * 1.0 / k / log(1 - p)
ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x36da510>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>, 1, (5, 0.5), (0,), [<bound method nbinom_gen.pmf of <scipy.stats.distributions.nbinom_gen object at 0x36caed0>>, <bound method nbinom_gen.logpmf of <scipy.stats.distributions.nbinom_gen object at 0x36caed0>>, <bound method nbinom_gen.cdf of <scipy.stats.distributions.nbinom_gen object at 0x36caed0>>, <bound method nbinom_gen.logcdf of <scipy.stats.distributions.nbinom_gen object at 0x36caed0>>, <bound method nbinom_gen.logsf of <scipy.stats.distributions.nbinom_gen object at 0x36caed0>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x36caed0>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>, 1, (0.51000000000000001,), (0,), [<bound method planck_gen.pmf of <scipy.stats.distributions.planck_gen object at 0x36dad50>>, <bound method planck_gen.logpmf of <scipy.stats.distributions.planck_gen object at 0x36dad50>>, <bound method planck_gen.cdf of <scipy.stats.distributions.planck_gen object at 0x36dad50>>, <bound method planck_gen.logcdf of <scipy.stats.distributions.planck_gen object at 0x36dad50>>, <bound method planck_gen.logsf of <scipy.stats.distributions.planck_gen object at 0x36dad50>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x36dad50>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>, 1, (0.59999999999999998,), (0,), [<bound method poisson_gen.pmf of <scipy.stats.distributions.poisson_gen object at 0x36dab90>>, <bound method poisson_gen.logpmf of <scipy.stats.distributions.poisson_gen object at 0x36dab90>>, <bound method poisson_gen.cdf of <scipy.stats.distributions.poisson_gen object at 0x36dab90>>, <bound method poisson_gen.logcdf of <scipy.stats.distributions.poisson_gen object at 0x36dab90>>, <bound method poisson_gen.logsf of <scipy.stats.distributions.poisson_gen object at 0x36dab90>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x36dab90>,) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>, 11, (7, 31), (0,), [<bound method randint_gen.pmf of <scipy.stats.distributions.randint_gen object at 0x36da8d0>>, <bound method randint_gen.logpmf of <scipy.stats.distributions.randint_gen object at 0x36da8d0>>, <bound method randint_gen.cdf of <scipy.stats.distributions.randint_gen object at 0x36da8d0>>, <bound method randint_gen.logcdf of <scipy.stats.distributions.randint_gen object at 0x36da8d0>>, <bound method randint_gen.logsf of <scipy.stats.distributions.randint_gen object at 0x36da8d0>>]) ... ok
test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x36da8d0>,) ... ok