ai-content-maker/.venv/Lib/site-packages/scipy/special/tests/test_logit.py

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2024-05-03 04:18:51 +03:00
import numpy as np
from numpy.testing import (assert_equal, assert_almost_equal,
assert_allclose)
from scipy.special import logit, expit, log_expit
class TestLogit:
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:
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)
class TestLogExpit:
def test_large_negative(self):
x = np.array([-10000.0, -750.0, -500.0, -35.0])
y = log_expit(x)
assert_equal(y, x)
def test_large_positive(self):
x = np.array([750.0, 1000.0, 10000.0])
y = log_expit(x)
# y will contain -0.0, and -0.0 is used in the expected value,
# but assert_equal does not check the sign of zeros, and I don't
# think the sign is an essential part of the test (i.e. it would
# probably be OK if log_expit(1000) returned 0.0 instead of -0.0).
assert_equal(y, np.array([-0.0, -0.0, -0.0]))
def test_basic_float64(self):
x = np.array([-32, -20, -10, -3, -1, -0.1, -1e-9,
0, 1e-9, 0.1, 1, 10, 100, 500, 710, 725, 735])
y = log_expit(x)
#
# Expected values were computed with mpmath:
#
# import mpmath
#
# mpmath.mp.dps = 100
#
# def mp_log_expit(x):
# return -mpmath.log1p(mpmath.exp(-x))
#
# expected = [float(mp_log_expit(t)) for t in x]
#
expected = [-32.000000000000014, -20.000000002061153,
-10.000045398899218, -3.048587351573742,
-1.3132616875182228, -0.7443966600735709,
-0.6931471810599453, -0.6931471805599453,
-0.6931471800599454, -0.6443966600735709,
-0.3132616875182228, -4.539889921686465e-05,
-3.720075976020836e-44, -7.124576406741286e-218,
-4.47628622567513e-309, -1.36930634e-315,
-6.217e-320]
# When tested locally, only one value in y was not exactly equal to
# expected. That was for x=1, and the y value differed from the
# expected by 1 ULP. For this test, however, I'll use rtol=1e-15.
assert_allclose(y, expected, rtol=1e-15)
def test_basic_float32(self):
x = np.array([-32, -20, -10, -3, -1, -0.1, -1e-9,
0, 1e-9, 0.1, 1, 10, 100], dtype=np.float32)
y = log_expit(x)
#
# Expected values were computed with mpmath:
#
# import mpmath
#
# mpmath.mp.dps = 100
#
# def mp_log_expit(x):
# return -mpmath.log1p(mpmath.exp(-x))
#
# expected = [np.float32(mp_log_expit(t)) for t in x]
#
expected = np.array([-32.0, -20.0, -10.000046, -3.0485873,
-1.3132616, -0.7443967, -0.6931472,
-0.6931472, -0.6931472, -0.64439666,
-0.3132617, -4.5398898e-05, -3.8e-44],
dtype=np.float32)
assert_allclose(y, expected, rtol=5e-7)