update

.CondaPkg/env/Lib/site-packages/scipy/special/tests/test_loggamma.py

@@ -1,70 +0,0 @@
-import numpy as np
-from numpy.testing import assert_allclose, assert_
-
-from scipy.special._testutils import FuncData
-from scipy.special import gamma, gammaln, loggamma
-
-
-def test_identities1():
-    # test the identity exp(loggamma(z)) = gamma(z)
-    x = np.array([-99.5, -9.5, -0.5, 0.5, 9.5, 99.5])
-    y = x.copy()
-    x, y = np.meshgrid(x, y)
-    z = (x + 1J*y).flatten()
-    dataset = np.vstack((z, gamma(z))).T
-
-    def f(z):
-        return np.exp(loggamma(z))
-
-    FuncData(f, dataset, 0, 1, rtol=1e-14, atol=1e-14).check()
-
-
-def test_identities2():
-    # test the identity loggamma(z + 1) = log(z) + loggamma(z)
-    x = np.array([-99.5, -9.5, -0.5, 0.5, 9.5, 99.5])
-    y = x.copy()
-    x, y = np.meshgrid(x, y)
-    z = (x + 1J*y).flatten()
-    dataset = np.vstack((z, np.log(z) + loggamma(z))).T
-
-    def f(z):
-        return loggamma(z + 1)
-
-    FuncData(f, dataset, 0, 1, rtol=1e-14, atol=1e-14).check()
-
-
-def test_complex_dispatch_realpart():
-    # Test that the real parts of loggamma and gammaln agree on the
-    # real axis.
-    x = np.r_[-np.logspace(10, -10), np.logspace(-10, 10)] + 0.5
-
-    dataset = np.vstack((x, gammaln(x))).T
-
-    def f(z):
-        z = np.array(z, dtype='complex128')
-        return loggamma(z).real
-
-    FuncData(f, dataset, 0, 1, rtol=1e-14, atol=1e-14).check()
-
-
-def test_real_dispatch():
-    x = np.logspace(-10, 10) + 0.5
-    dataset = np.vstack((x, gammaln(x))).T
-
-    FuncData(loggamma, dataset, 0, 1, rtol=1e-14, atol=1e-14).check()
-    assert_(loggamma(0) == np.inf)
-    assert_(np.isnan(loggamma(-1)))
-
-
-def test_gh_6536():
-    z = loggamma(complex(-3.4, +0.0))
-    zbar = loggamma(complex(-3.4, -0.0))
-    assert_allclose(z, zbar.conjugate(), rtol=1e-15, atol=0)
-
-
-def test_branch_cut():
-    # Make sure negative zero is treated correctly
-    x = -np.logspace(300, -30, 100)
-    z = np.asarray([complex(x0, 0.0) for x0 in x])
-    zbar = np.asarray([complex(x0, -0.0) for x0 in x])
-    assert_allclose(z, zbar.conjugate(), rtol=1e-15, atol=0)