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- import numpy as np
- from numpy.testing import assert_equal, assert_allclose
- import scipy.special as sc
- def test_ndtr():
- assert_equal(sc.ndtr(0), 0.5)
- assert_allclose(sc.ndtr(1), 0.8413447460685429)
- class TestNdtri:
- def test_zero(self):
- assert sc.ndtri(0.5) == 0.0
- def test_asymptotes(self):
- assert_equal(sc.ndtri([0.0, 1.0]), [-np.inf, np.inf])
- def test_outside_of_domain(self):
- assert all(np.isnan(sc.ndtri([-1.5, 1.5])))
- class TestLogNdtr:
- # The expected values in these tests were computed with mpmath:
- #
- # def log_ndtr_mp(x):
- # return mpmath.log(mpmath.ncdf(x))
- #
- def test_log_ndtr_moderate_le8(self):
- x = np.array([-0.75, -0.25, 0, 0.5, 1.5, 2.5, 3, 4, 5, 7, 8])
- expected = np.array([-1.4844482299196562,
- -0.9130617648111351,
- -0.6931471805599453,
- -0.3689464152886564,
- -0.06914345561223398,
- -0.006229025485860002,
- -0.0013508099647481938,
- -3.167174337748927e-05,
- -2.866516129637636e-07,
- -1.279812543886654e-12,
- -6.220960574271786e-16])
- y = sc.log_ndtr(x)
- assert_allclose(y, expected, rtol=1e-14)
- def test_log_ndtr_values_8_16(self):
- x = np.array([8.001, 8.06, 8.15, 8.5, 10, 12, 14, 16])
- expected = [-6.170639424817055e-16,
- -3.814722443652823e-16,
- -1.819621363526629e-16,
- -9.479534822203318e-18,
- -7.619853024160525e-24,
- -1.776482112077679e-33,
- -7.7935368191928e-45,
- -6.388754400538087e-58]
- y = sc.log_ndtr(x)
- assert_allclose(y, expected, rtol=5e-14)
- def test_log_ndtr_values_16_31(self):
- x = np.array([16.15, 20.3, 21.4, 26.2, 30.9])
- expected = [-5.678084565148492e-59,
- -6.429244467698346e-92,
- -6.680402412553295e-102,
- -1.328698078458869e-151,
- -5.972288641838264e-210]
- y = sc.log_ndtr(x)
- assert_allclose(y, expected, rtol=2e-13)
- def test_log_ndtr_values_gt31(self):
- x = np.array([31.6, 32.8, 34.9, 37.1])
- expected = [-1.846036234858162e-219,
- -2.9440539964066835e-236,
- -3.71721649450857e-267,
- -1.4047119663106221e-301]
- y = sc.log_ndtr(x)
- assert_allclose(y, expected, rtol=3e-13)
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