def example_n():
print(skewnorm.pdf(1,0), stats.norm.pdf(1), skewnorm.pdf(1,0) - stats.norm.pdf(1))
print(skewnorm.pdf(1,1000), stats.chi.pdf(1,1), skewnorm.pdf(1,1000) - stats.chi.pdf(1,1))
print(skewnorm.pdf(-1,-1000), stats.chi.pdf(1,1), skewnorm.pdf(-1,-1000) - stats.chi.pdf(1,1))
rvs = skewnorm.rvs(0,size=500)
print('sample mean var: ', rvs.mean(), rvs.var())
print('theoretical mean var', skewnorm.stats(0))
rvs = skewnorm.rvs(5,size=500)
print('sample mean var: ', rvs.mean(), rvs.var())
print('theoretical mean var', skewnorm.stats(5))
print(skewnorm.cdf(1,0), stats.norm.cdf(1), skewnorm.cdf(1,0) - stats.norm.cdf(1))
print(skewnorm.cdf(1,1000), stats.chi.cdf(1,1), skewnorm.cdf(1,1000) - stats.chi.cdf(1,1))
print(skewnorm.sf(0.05,1000), stats.chi.sf(0.05,1), skewnorm.sf(0.05,1000) - stats.chi.sf(0.05,1))
def test_skewnorm():
#library("sn")
#dsn(c(-2,-1,0,1,2), shape=10)
#psn(c(-2,-1,0,1,2), shape=10)
#noquote(sprintf("%.15e,", snp))
pdf_r = np.array([2.973416551551523e-90, 3.687562713971017e-24,
3.989422804014327e-01, 4.839414490382867e-01,
1.079819330263761e-01])
pdf_sn = skewnorm.pdf([-2,-1,0,1,2], 10)
#res = (snp-snp_r)/snp
assert_(np.allclose(pdf_sn, pdf_r,rtol=1e-13, atol=0))
pdf_sn2 = skewnorm2.pdf([-2,-1,0,1,2], 10)
assert_(np.allclose(pdf_sn2, pdf_r, rtol=1e-13, atol=0))
cdf_r = np.array([0.000000000000000e+00, 0.000000000000000e+00,
3.172551743055357e-02, 6.826894921370859e-01,
9.544997361036416e-01])
cdf_sn = skewnorm.cdf([-2,-1,0,1,2], 10)
maxabs = np.max(np.abs(cdf_sn - cdf_r))
maxrel = np.max(np.abs(cdf_sn - cdf_r)/(cdf_r+1e-50))
msg = "maxabs=%15.13g, maxrel=%15.13g\n%r\n%r" % (maxabs, maxrel, cdf_sn,
cdf_r)
#assert_(np.allclose(cdf_sn, cdf_r, rtol=1e-13, atol=1e-25), msg=msg)
assert_almost_equal(cdf_sn, cdf_r, decimal=10)
cdf_sn2 = skewnorm2.cdf([-2,-1,0,1,2], 10)
maxabs = np.max(np.abs(cdf_sn2 - cdf_r))
maxrel = np.max(np.abs(cdf_sn2 - cdf_r)/(cdf_r+1e-50))
msg = "maxabs=%15.13g, maxrel=%15.13g" % (maxabs, maxrel)
#assert_(np.allclose(cdf_sn2, cdf_r, rtol=1e-13, atol=1e-25), msg=msg)
assert_almost_equal(cdf_sn2, cdf_r, decimal=10, err_msg=msg)
def test_skewnorm():
#library("sn")
#dsn(c(-2,-1,0,1,2), shape=10)
#psn(c(-2,-1,0,1,2), shape=10)
#noquote(sprintf("%.15e,", snp))
pdf_r = np.array([2.973416551551523e-90, 3.687562713971017e-24,
3.989422804014327e-01, 4.839414490382867e-01,
1.079819330263761e-01])
pdf_sn = skewnorm.pdf([-2,-1,0,1,2], 10)
#res = (snp-snp_r)/snp
assert_(np.allclose(pdf_sn, pdf_r,rtol=1e-13, atol=0))
pdf_sn2 = skewnorm2.pdf([-2,-1,0,1,2], 10)
assert_(np.allclose(pdf_sn2, pdf_r, rtol=1e-13, atol=0))
cdf_r = np.array([0.000000000000000e+00, 0.000000000000000e+00,
3.172551743055357e-02, 6.826894921370859e-01,
9.544997361036416e-01])
cdf_sn = skewnorm.cdf([-2,-1,0,1,2], 10)
assert_(np.allclose(cdf_sn, cdf_r, rtol=1e-13, atol=1e-25))
cdf_sn2 = skewnorm2.cdf([-2,-1,0,1,2], 10)
assert_(np.allclose(cdf_sn2, cdf_r, rtol=1e-13, atol=1e-25))
