86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
|
import pytest
|
||
|
|
||
|
import numpy as np
|
||
|
from numpy.testing import assert_allclose
|
||
|
import scipy.special as sc
|
||
|
from scipy.special._testutils import FuncData
|
||
|
|
||
|
|
||
|
class TestVoigtProfile:
|
||
|
|
||
|
@pytest.mark.parametrize('x, sigma, gamma', [
|
||
|
(np.nan, 1, 1),
|
||
|
(0, np.nan, 1),
|
||
|
(0, 1, np.nan),
|
||
|
(1, np.nan, 0),
|
||
|
(np.nan, 1, 0),
|
||
|
(1, 0, np.nan),
|
||
|
(np.nan, 0, 1),
|
||
|
(np.nan, 0, 0)
|
||
|
])
|
||
|
def test_nan(self, x, sigma, gamma):
|
||
|
assert np.isnan(sc.voigt_profile(x, sigma, gamma))
|
||
|
|
||
|
@pytest.mark.parametrize('x, desired', [
|
||
|
(-np.inf, 0),
|
||
|
(np.inf, 0)
|
||
|
])
|
||
|
def test_inf(self, x, desired):
|
||
|
assert sc.voigt_profile(x, 1, 1) == desired
|
||
|
|
||
|
def test_against_mathematica(self):
|
||
|
# Results obtained from Mathematica by computing
|
||
|
#
|
||
|
# PDF[VoigtDistribution[gamma, sigma], x]
|
||
|
#
|
||
|
points = np.array([
|
||
|
[-7.89, 45.06, 6.66, 0.0077921073660388806401],
|
||
|
[-0.05, 7.98, 24.13, 0.012068223646769913478],
|
||
|
[-13.98, 16.83, 42.37, 0.0062442236362132357833],
|
||
|
[-12.66, 0.21, 6.32, 0.010052516161087379402],
|
||
|
[11.34, 4.25, 21.96, 0.0113698923627278917805],
|
||
|
[-11.56, 20.40, 30.53, 0.0076332760432097464987],
|
||
|
[-9.17, 25.61, 8.32, 0.011646345779083005429],
|
||
|
[16.59, 18.05, 2.50, 0.013637768837526809181],
|
||
|
[9.11, 2.12, 39.33, 0.0076644040807277677585],
|
||
|
[-43.33, 0.30, 45.68, 0.0036680463875330150996]
|
||
|
])
|
||
|
FuncData(
|
||
|
sc.voigt_profile,
|
||
|
points,
|
||
|
(0, 1, 2),
|
||
|
3,
|
||
|
atol=0,
|
||
|
rtol=1e-15
|
||
|
).check()
|
||
|
|
||
|
def test_symmetry(self):
|
||
|
x = np.linspace(0, 10, 20)
|
||
|
assert_allclose(
|
||
|
sc.voigt_profile(x, 1, 1),
|
||
|
sc.voigt_profile(-x, 1, 1),
|
||
|
rtol=1e-15,
|
||
|
atol=0
|
||
|
)
|
||
|
|
||
|
@pytest.mark.parametrize('x, sigma, gamma, desired', [
|
||
|
(0, 0, 0, np.inf),
|
||
|
(1, 0, 0, 0)
|
||
|
])
|
||
|
def test_corner_cases(self, x, sigma, gamma, desired):
|
||
|
assert sc.voigt_profile(x, sigma, gamma) == desired
|
||
|
|
||
|
@pytest.mark.parametrize('sigma1, gamma1, sigma2, gamma2', [
|
||
|
(0, 1, 1e-16, 1),
|
||
|
(1, 0, 1, 1e-16),
|
||
|
(0, 0, 1e-16, 1e-16)
|
||
|
])
|
||
|
def test_continuity(self, sigma1, gamma1, sigma2, gamma2):
|
||
|
x = np.linspace(1, 10, 20)
|
||
|
assert_allclose(
|
||
|
sc.voigt_profile(x, sigma1, gamma1),
|
||
|
sc.voigt_profile(x, sigma2, gamma2),
|
||
|
rtol=1e-16,
|
||
|
atol=1e-16
|
||
|
)
|