def test_hollweg1999_vals(self, kwargs, expected, desired_beta):
"""
Test calculated values based on Figure 2 of Hollweg1999
(DOI: https://doi.org/10.1029/1998JA900132) using eqn 3 of
Bellan 2012
(DOI: https://doi.org/10.1029/2012JA017856).
The WebPlotDigitizer software was used to determine the test
parameters for k, B, and expected omega from Figure 2 of
Hollweg1999.
- GitHub: https://github.com/ankitrohatgi/WebPlotDigitizer
- Web Version: https://automeris.io/WebPlotDigitizer/
"""
# k values need to be single valued for this test to function correctly
cs = speeds.cs_(kwargs["T_e"], kwargs["T_i"], kwargs["ion"]).value
va = speeds.va_(kwargs["B"], kwargs["n_i"], ion=kwargs["ion"]).value
beta = (cs / va)**2
if not np.isclose(beta, desired_beta, atol=2e-4):
pytest.fail(
f"The Holweg 1999 paper requires a 'beta' value of {desired_beta:0.5f} "
f"and the test parameters yielded {beta:.6f}.")
kz = (np.cos(kwargs["theta"]) * kwargs["k"]).value
w_alfven = (hollweg(**kwargs)["alfven_mode"]).value
big_omega = np.abs(w_alfven / (kz * va))
assert np.allclose(big_omega, expected, atol=1e-2)
def test_on_bellan2012_vals(self, kwargs, expected):
"""
Test calculated values based on Figure 1 of Bellan 2012
(DOI: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2012JA017856).
"""
# theta and k values need to be single valued for this test to function
# correctly
cs = cs_(kwargs["T_e"], kwargs["T_i"], kwargs["ion"])
va = va_(kwargs["B"], kwargs["n_i"], ion=kwargs["ion"])
wci = wc_(kwargs["B"], kwargs["ion"])
beta = (cs / va).value**2
if not np.isclose(beta, 0.4, atol=1e-4):
pytest.fail(
f"The Bellan 2012 paper requires a 'beta' value of 0.4 and the test "
f"parameters yielded {beta:.6f}.")
Lambda = (kwargs["k"] * va / wci).value**2
if not np.isclose(Lambda, 0.4, atol=1e-4):
pytest.fail(
f"The Bellan 2012 paper requires a 'Lambda' value of 0.4 and the test "
f"parameters yielded {Lambda:.6f}.")
ws = two_fluid(**kwargs)
for mode, val in ws.items():
norm = (np.absolute(val) / (kwargs["k"] * va)).value**2
assert np.isclose(norm, expected[mode])
class TestAlfvenSpeed:
"""Test `~plasmapy.formulary.speeds.Alfven_speed`."""
@pytest.mark.parametrize(
"args, kwargs, _error",
[
# scenarios that raise RelativityError
((10 * u.T, 1.0e-10 * u.kg * u.m ** -3), {}, RelativityError),
((np.inf * u.T, 1 * u.m ** -3), {"ion": "p"}, RelativityError),
((-np.inf * u.T, 1 * u.m ** -3), {"ion": "p"}, RelativityError),
#
# scenarios that raise InvalidParticleError
((1 * u.T, 5e19 * u.m ** -3), {"ion": "spacecats"}, InvalidParticleError),
#
# scenarios that raise TypeError
(("not a Bfield", 1.0e-10 * u.kg * u.m ** -3), {}, TypeError),
((10 * u.T, "not a density"), {}, TypeError),
((10 * u.T, 5), {"ion": "p"}, TypeError),
((1 * u.T, 1.0e18 * u.m ** -3), {"ion": ["He"]}, TypeError),
((1 * u.T, 1.0e18 * u.m ** -3), {"ion": "He", "z_mean": "nope"}, TypeError),
#
# scenarios that raise UnitTypeError
((1 * u.T, 1.0e18 * u.cm), {"ion": "He"}, u.UnitTypeError),
((1 * u.T, 5 * u.m ** -2), {"ion": "p"}, u.UnitTypeError),
((1 * u.cm, 1.0e18 * u.m ** -3), {"ion": "He"}, u.UnitTypeError),
((5 * u.A, 5e19 * u.m ** -3), {"ion": "p"}, u.UnitTypeError),
#
# scenarios that raise ValueError
((1 * u.T, -1.0e18 * u.m ** -3), {"ion": "He"}, ValueError),
(
(np.array([5, 6, 7]) * u.T, np.array([5, 6]) * u.m ** -3),
{"ion": "p"},
ValueError,
),
(
(np.array([0.001, 0.002]) * u.T, np.array([-5e19, 6e19]) * u.m ** -3),
{"ion": "p"},
ValueError,
),
],
)
def test_raises(self, args, kwargs, _error):
"""Test scenarios that raise exceptions or warnings."""
with pytest.raises(_error):
Alfven_speed(*args, **kwargs)
@pytest.mark.parametrize(
"args, kwargs, expected, isclose_kw, _warning",
[
# scenarios that issue RelativityWarning
(
(5 * u.T, 5e19 * u.m ** -3),
{"ion": "H"},
15413707.39,
{},
RelativityWarning,
),
(
(5 * u.T, 5e19 * u.m ** -3),
{"ion": "H+"},
15413707.39,
{"rtol": 3.0e-4},
RelativityWarning,
),
(
(5 * u.T, 5e19 * u.m ** -3),
{"ion": "p"},
15413707.39,
{"rtol": 4.0e-4},
RelativityWarning,
),
#
# scenarios that issue UnitsWarning
((0.5, 1.0e18 * u.m ** -3), {"ion": "He"}, 5470657.93, {}, u.UnitsWarning),
],
)
def test_warns(self, args, kwargs, expected, isclose_kw, _warning):
"""Test scenarios that issue warnings"""
with pytest.warns(_warning):
val = Alfven_speed(*args, **kwargs)
assert isinstance(val, u.Quantity)
assert val.unit == u.m / u.s
assert np.isclose(val.value, expected, **isclose_kw)
@pytest.mark.parametrize(
"args, kwargs, expected, isclose_kw",
[
(
(1 * u.T, 1e-8 * u.kg * u.m ** -3),
{"ion": "p"},
8920620.58 * u.m / u.s,
{"rtol": 1e-6},
),
(
(1 * u.T, 1e-8 * u.kg * u.m ** -3),
{},
8920620.58 * u.m / u.s,
{"rtol": 1e-6},
),
(
(0.05 * u.T, 1e18 * u.m ** -3),
{"ion": "He"},
Alfven_speed(0.05 * u.T, 6.64738793e-09 * u.kg * u.m ** -3),
{},
),
(
(0.05 * u.T, 1e18 * u.m ** -3),
{"ion": "He+"},
Alfven_speed(0.05 * u.T, 1e18 * u.m ** -3, ion="He"),
{"rtol": 7e-5},
),
(
(0.05 * u.T, 1e18 * u.m ** -3),
{"ion": "He", "z_mean": 2},
Alfven_speed(0.05 * u.T, 1e18 * u.m ** -3, ion="He +2"),
{"rtol": 1.4e-4},
),
(
(0.05 * u.T, 1e18 * u.m ** -3),
{"ion": Particle("He+")},
Alfven_speed(0.05 * u.T, 1e18 * u.m ** -3, ion="He+"),
{},
),
(
([0.001, 0.002] * u.T, 5e-10 * u.kg * u.m ** -3),
{},
[
va_(0.001 * u.T, 5e-10 * u.kg * u.m ** -3).value,
va_(0.002 * u.T, 5e-10 * u.kg * u.m ** -3).value,
]
* (u.m / u.s),
{},
),
(
([0.001, 0.002] * u.T, [5e-10, 2e-10] * u.kg * u.m ** -3),
{},
[
va_(0.001 * u.T, 5e-10 * u.kg * u.m ** -3).value,
va_(0.002 * u.T, 2e-10 * u.kg * u.m ** -3).value,
]
* (u.m / u.s),
{},
),
(
(0.001 * u.T, [1.0e18, 2e18] * u.m ** -3),
{"ion": "p"},
[
va_(0.001 * u.T, 1e18 * u.m ** -3, ion="p").value,
va_(0.001 * u.T, 2e18 * u.m ** -3, ion="p").value,
]
* (u.m / u.s),
{},
),
],
)
def test_values(self, args, kwargs, expected, isclose_kw):
"""Test expected values."""
assert np.allclose(Alfven_speed(*args, **kwargs), expected, **isclose_kw)
@pytest.mark.parametrize(
"args, kwargs, nan_mask",
[
((np.nan * u.T, 1 * u.kg * u.m ** -3), {}, []),
((0.001 * u.T, np.nan * u.kg * u.m ** -3), {}, []),
(([np.nan, 0.001] * u.T, 1 * u.kg * u.m ** -3), {}, [True, False]),
(
(0.001 * u.T, [np.nan, 1.0, np.nan] * u.kg * u.m ** -3),
{},
[True, False, True],
),
(([np.nan, 0.001] * u.T, [1, np.nan] * u.kg * u.m ** -3), {}, [True, True]),
(
(0.001 * u.T, [np.nan, 1e18, np.nan] * u.m ** -3),
{"ion": "Ar+"},
[True, False, True],
),
],
)
def test_nan_values(self, args, kwargs, nan_mask):
"""Input scenarios that lead to `numpy.nan` values being returned."""
val = Alfven_speed(*args, **kwargs)
if np.isscalar(val.value):
assert np.isnan(val)
else:
nan_arr = np.isnan(val)
assert np.all(nan_arr[nan_mask])
assert np.all(np.logical_not(nan_arr[np.logical_not(nan_mask)]))
def test_handle_nparrays(self):
"""Test for ability to handle numpy array quantities"""
assert_can_handle_nparray(Alfven_speed)