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import numpy as np
import pytest
from numpy.testing import assert_allclose
from einsteinpy.geodesic.utils import _P, _sch, _kerr, _kerrnewman
@pytest.mark.parametrize(
"g, g_prms, q, p, time_like, expected",
[
(
_sch,
(),
[0., 2.5, np.pi / 6, np.pi / 2],
[0.1, 2., 2.],
True,
[-0.9167333309092672, 0.1, 2., 2.]
),
(
_kerr,
(0.9,),
[0., 25, np.pi / 2, 0.],
[0., 0, 2.427],
False,
[-0.09333038545829885, 0., 0, 2.427]
),
(
_kerrnewman,
(0.5, 0.1,),
[0., 5.5, np.pi / 4, 0.],
[0.1, -0.2, -4.],
True,
[-1.1220908695019767, 0.1, -0.2, -4.]
),
],
)
def test_P(g, g_prms, q, p, time_like, expected):
P = _P(g, g_prms, q, p, time_like)
assert_allclose(P, expected, atol=1e-8, rtol=1e-8)
@pytest.mark.parametrize(
"x",
[
(
[0., 2.5, np.pi / 6, np.pi / 2],
),
(
[0., 25, np.pi / 2, 0.],
),
(
[0., 5.5, np.pi / 4, 0.],
),
],
)
def test_metrics(x):
x = x[0]
# a = Q = 0.
s = _sch(x).astype(float)
k = _kerr(x, 0.).astype(float)
kn = _kerrnewman(x, 0., 0.).astype(float)
assert_allclose(s, k, atol=1e-8, rtol=1e-8)
assert_allclose(k, kn, atol=1e-8, rtol=1e-8)
assert_allclose(kn, s, atol=1e-8, rtol=1e-8)
# Non-zero Spin
k = _kerr(x, 0.4).astype(float)
kn = _kerrnewman(x, 0.4, 0.).astype(float)
assert_allclose(k, kn, atol=1e-8, rtol=1e-8)
|
