146 lines
5.4 KiB
Python
146 lines
5.4 KiB
Python
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import numpy as np
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from numpy.testing import (assert_equal, assert_almost_equal,
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assert_allclose)
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from scipy.special import logit, expit, log_expit
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class TestLogit:
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def check_logit_out(self, dtype, expected):
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a = np.linspace(0, 1, 10)
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a = np.array(a, dtype=dtype)
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with np.errstate(divide='ignore'):
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actual = logit(a)
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assert_almost_equal(actual, expected)
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assert_equal(actual.dtype, np.dtype(dtype))
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def test_float32(self):
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expected = np.array([-np.inf, -2.07944155,
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-1.25276291, -0.69314718,
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-0.22314353, 0.22314365,
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0.6931473, 1.25276303,
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2.07944155, np.inf], dtype=np.float32)
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self.check_logit_out('f4', expected)
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def test_float64(self):
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expected = np.array([-np.inf, -2.07944154,
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-1.25276297, -0.69314718,
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-0.22314355, 0.22314355,
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0.69314718, 1.25276297,
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2.07944154, np.inf])
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self.check_logit_out('f8', expected)
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def test_nan(self):
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expected = np.array([np.nan]*4)
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with np.errstate(invalid='ignore'):
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actual = logit(np.array([-3., -2., 2., 3.]))
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assert_equal(expected, actual)
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class TestExpit:
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def check_expit_out(self, dtype, expected):
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a = np.linspace(-4, 4, 10)
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a = np.array(a, dtype=dtype)
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actual = expit(a)
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assert_almost_equal(actual, expected)
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assert_equal(actual.dtype, np.dtype(dtype))
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def test_float32(self):
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expected = np.array([0.01798621, 0.04265125,
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0.09777259, 0.20860852,
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0.39068246, 0.60931754,
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0.79139149, 0.9022274,
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0.95734876, 0.98201376], dtype=np.float32)
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self.check_expit_out('f4', expected)
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def test_float64(self):
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expected = np.array([0.01798621, 0.04265125,
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0.0977726, 0.20860853,
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0.39068246, 0.60931754,
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0.79139147, 0.9022274,
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0.95734875, 0.98201379])
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self.check_expit_out('f8', expected)
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def test_large(self):
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for dtype in (np.float32, np.float64, np.longdouble):
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for n in (88, 89, 709, 710, 11356, 11357):
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n = np.array(n, dtype=dtype)
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assert_allclose(expit(n), 1.0, atol=1e-20)
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assert_allclose(expit(-n), 0.0, atol=1e-20)
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assert_equal(expit(n).dtype, dtype)
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assert_equal(expit(-n).dtype, dtype)
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class TestLogExpit:
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def test_large_negative(self):
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x = np.array([-10000.0, -750.0, -500.0, -35.0])
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y = log_expit(x)
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assert_equal(y, x)
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def test_large_positive(self):
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x = np.array([750.0, 1000.0, 10000.0])
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y = log_expit(x)
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# y will contain -0.0, and -0.0 is used in the expected value,
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# but assert_equal does not check the sign of zeros, and I don't
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# think the sign is an essential part of the test (i.e. it would
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# probably be OK if log_expit(1000) returned 0.0 instead of -0.0).
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assert_equal(y, np.array([-0.0, -0.0, -0.0]))
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def test_basic_float64(self):
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x = np.array([-32, -20, -10, -3, -1, -0.1, -1e-9,
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0, 1e-9, 0.1, 1, 10, 100, 500, 710, 725, 735])
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y = log_expit(x)
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#
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# Expected values were computed with mpmath:
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#
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# import mpmath
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#
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# mpmath.mp.dps = 100
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#
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# def mp_log_expit(x):
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# return -mpmath.log1p(mpmath.exp(-x))
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#
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# expected = [float(mp_log_expit(t)) for t in x]
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#
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expected = [-32.000000000000014, -20.000000002061153,
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-10.000045398899218, -3.048587351573742,
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-1.3132616875182228, -0.7443966600735709,
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-0.6931471810599453, -0.6931471805599453,
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-0.6931471800599454, -0.6443966600735709,
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-0.3132616875182228, -4.539889921686465e-05,
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-3.720075976020836e-44, -7.124576406741286e-218,
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-4.47628622567513e-309, -1.36930634e-315,
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-6.217e-320]
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# When tested locally, only one value in y was not exactly equal to
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# expected. That was for x=1, and the y value differed from the
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# expected by 1 ULP. For this test, however, I'll use rtol=1e-15.
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assert_allclose(y, expected, rtol=1e-15)
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def test_basic_float32(self):
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x = np.array([-32, -20, -10, -3, -1, -0.1, -1e-9,
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0, 1e-9, 0.1, 1, 10, 100], dtype=np.float32)
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y = log_expit(x)
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#
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# Expected values were computed with mpmath:
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#
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# import mpmath
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#
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# mpmath.mp.dps = 100
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#
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# def mp_log_expit(x):
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# return -mpmath.log1p(mpmath.exp(-x))
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#
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# expected = [np.float32(mp_log_expit(t)) for t in x]
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#
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expected = np.array([-32.0, -20.0, -10.000046, -3.0485873,
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-1.3132616, -0.7443967, -0.6931472,
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-0.6931472, -0.6931472, -0.64439666,
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-0.3132617, -4.5398898e-05, -3.8e-44],
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dtype=np.float32)
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assert_allclose(y, expected, rtol=5e-7)
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