def test_log1mexp():
vals = np.array([-1, 0, 1e-20, 1e-4, 10, 100, 1e20])
# import mpmath
# mpmath.mp.dps = 1000
# [float(mpmath.log(1 - mpmath.exp(-x))) for x in vals]
expected = np.array([
np.nan, -np.inf, -46.051701859880914, -9.210390371559516,
-4.540096037048921e-05, -3.720075976020836e-44, 0.0
])
actual = log1mexp(vals).eval()
npt.assert_allclose(actual, expected)
def test_log1mexp():
vals = np.array([-1, 0, 1e-20, 1e-4, 10, 100, 1e20])
# import mpmath
# mpmath.mp.dps = 1000
# [float(mpmath.log(1 - mpmath.exp(-x))) for x in vals]
expected = np.array([
np.nan,
-np.inf,
-46.051701859880914,
-9.210390371559516,
-4.540096037048921e-05,
-3.720075976020836e-44,
0.0])
actual = log1mexp(vals).eval()
npt.assert_allclose(actual, expected)
def test_log1mexp():
vals = np.array([-1, 0, 1e-20, 1e-4, 10, 100, 1e20])
vals_ = vals.copy()
# import mpmath
# mpmath.mp.dps = 1000
# [float(mpmath.log(1 - mpmath.exp(-x))) for x in vals]
expected = np.array([
np.nan,
-np.inf,
-46.051701859880914,
-9.210390371559516,
-4.540096037048921e-05,
-3.720075976020836e-44,
0.0,
])
actual = log1mexp(vals).eval()
npt.assert_allclose(actual, expected)
actual_ = log1mexp_numpy(vals)
npt.assert_allclose(actual_, expected)
# Check that input was not changed in place
npt.assert_allclose(vals, vals_)