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)