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

118 lines
3.5 KiB
Python
Raw Normal View History

2024-05-03 04:18:51 +03:00
import pytest
import numpy as np
from numpy.testing import assert_, assert_equal, assert_allclose
import scipy.special as sc
from scipy.special._testutils import assert_func_equal
def test_wrightomega_nan():
pts = [complex(np.nan, 0),
complex(0, np.nan),
complex(np.nan, np.nan),
complex(np.nan, 1),
complex(1, np.nan)]
for p in pts:
res = sc.wrightomega(p)
assert_(np.isnan(res.real))
assert_(np.isnan(res.imag))
def test_wrightomega_inf_branch():
pts = [complex(-np.inf, np.pi/4),
complex(-np.inf, -np.pi/4),
complex(-np.inf, 3*np.pi/4),
complex(-np.inf, -3*np.pi/4)]
expected_results = [complex(0.0, 0.0),
complex(0.0, -0.0),
complex(-0.0, 0.0),
complex(-0.0, -0.0)]
for p, expected in zip(pts, expected_results):
res = sc.wrightomega(p)
# We can't use assert_equal(res, expected) because in older versions of
# numpy, assert_equal doesn't check the sign of the real and imaginary
# parts when comparing complex zeros. It does check the sign when the
# arguments are *real* scalars.
assert_equal(res.real, expected.real)
assert_equal(res.imag, expected.imag)
def test_wrightomega_inf():
pts = [complex(np.inf, 10),
complex(-np.inf, 10),
complex(10, np.inf),
complex(10, -np.inf)]
for p in pts:
assert_equal(sc.wrightomega(p), p)
def test_wrightomega_singular():
pts = [complex(-1.0, np.pi),
complex(-1.0, -np.pi)]
for p in pts:
res = sc.wrightomega(p)
assert_equal(res, -1.0)
assert_(np.signbit(res.imag) == np.bool_(False))
@pytest.mark.parametrize('x, desired', [
(-np.inf, 0),
(np.inf, np.inf),
])
def test_wrightomega_real_infinities(x, desired):
assert sc.wrightomega(x) == desired
def test_wrightomega_real_nan():
assert np.isnan(sc.wrightomega(np.nan))
def test_wrightomega_real_series_crossover():
desired_error = 2 * np.finfo(float).eps
crossover = 1e20
x_before_crossover = np.nextafter(crossover, -np.inf)
x_after_crossover = np.nextafter(crossover, np.inf)
# Computed using Mpmath
desired_before_crossover = 99999999999999983569.948
desired_after_crossover = 100000000000000016337.948
assert_allclose(
sc.wrightomega(x_before_crossover),
desired_before_crossover,
atol=0,
rtol=desired_error,
)
assert_allclose(
sc.wrightomega(x_after_crossover),
desired_after_crossover,
atol=0,
rtol=desired_error,
)
def test_wrightomega_exp_approximation_crossover():
desired_error = 2 * np.finfo(float).eps
crossover = -50
x_before_crossover = np.nextafter(crossover, np.inf)
x_after_crossover = np.nextafter(crossover, -np.inf)
# Computed using Mpmath
desired_before_crossover = 1.9287498479639314876e-22
desired_after_crossover = 1.9287498479639040784e-22
assert_allclose(
sc.wrightomega(x_before_crossover),
desired_before_crossover,
atol=0,
rtol=desired_error,
)
assert_allclose(
sc.wrightomega(x_after_crossover),
desired_after_crossover,
atol=0,
rtol=desired_error,
)
def test_wrightomega_real_versus_complex():
x = np.linspace(-500, 500, 1001)
results = sc.wrightomega(x + 0j).real
assert_func_equal(sc.wrightomega, results, x, atol=0, rtol=1e-14)