import numpy as np from numpy.testing import (assert_equal, assert_almost_equal, assert_allclose) from scipy.special import logit, expit class TestLogit(object): def check_logit_out(self, dtype, expected): a = np.linspace(0,1,10) a = np.array(a, dtype=dtype) with np.errstate(divide='ignore'): actual = logit(a) assert_almost_equal(actual, expected) assert_equal(actual.dtype, np.dtype(dtype)) def test_float32(self): expected = np.array([-np.inf, -2.07944155, -1.25276291, -0.69314718, -0.22314353, 0.22314365, 0.6931473, 1.25276303, 2.07944155, np.inf], dtype=np.float32) self.check_logit_out('f4', expected) def test_float64(self): expected = np.array([-np.inf, -2.07944154, -1.25276297, -0.69314718, -0.22314355, 0.22314355, 0.69314718, 1.25276297, 2.07944154, np.inf]) self.check_logit_out('f8', expected) def test_nan(self): expected = np.array([np.nan]*4) with np.errstate(invalid='ignore'): actual = logit(np.array([-3., -2., 2., 3.])) assert_equal(expected, actual) class TestExpit(object): def check_expit_out(self, dtype, expected): a = np.linspace(-4,4,10) a = np.array(a, dtype=dtype) actual = expit(a) assert_almost_equal(actual, expected) assert_equal(actual.dtype, np.dtype(dtype)) def test_float32(self): expected = np.array([0.01798621, 0.04265125, 0.09777259, 0.20860852, 0.39068246, 0.60931754, 0.79139149, 0.9022274, 0.95734876, 0.98201376], dtype=np.float32) self.check_expit_out('f4',expected) def test_float64(self): expected = np.array([0.01798621, 0.04265125, 0.0977726, 0.20860853, 0.39068246, 0.60931754, 0.79139147, 0.9022274, 0.95734875, 0.98201379]) self.check_expit_out('f8', expected) def test_large(self): for dtype in (np.float32, np.float64, np.longdouble): for n in (88, 89, 709, 710, 11356, 11357): n = np.array(n, dtype=dtype) assert_allclose(expit(n), 1.0, atol=1e-20) assert_allclose(expit(-n), 0.0, atol=1e-20) assert_equal(expit(n).dtype, dtype) assert_equal(expit(-n).dtype, dtype)