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