def assert_warns_message(expected_warning, expected_message, *args, **kwargs):
"""Assert that the correct warning message is raised.
Handles regex better than the default.
"""
expected_regex = re.escape(expected_message)
return assert_warns_regex(expected_warning, expected_regex, *args, **kwargs)
def test_duplicate_data_many():
with assert_warns_regex(
RuntimeWarning,
"Detected zero distance between ([0-9]*) pairs of samples. Consider removing duplicates to avoid errors in downstream processing.",
):
build_graph(np.vstack([data, data[:21]]),
n_pca=20,
decay=10,
thresh=1e-4)
def assert_warns(exception=Warning,
*args,
glob=None,
regex=None,
match_case=None,
**kwargs):
if glob is None and regex is None:
return tools.assert_warns(exception, *args, **kwargs)
pattern = get_pattern(glob, regex, match_case)
return tools.assert_warns_regex(exception, pattern, *args, **kwargs)
def test_hrg():
ID, info = random.choice(list(species_dict.items()))
m = info['mass']
g = info['degen']
sign = -1 if info['boson'] else 1
prefactor = g / (2 * np.pi**2 * hbarc**3)
if info['has_anti']:
prefactor *= 2
T = random.uniform(.13, .15)
hrg = HRG(T, species=[ID], res_width=False)
assert_almost_equal(hrg.T, T, delta=1e-15, msg='incorrect temperature')
n = np.arange(1, 50)
density = prefactor * m * m * T * (
(-sign)**(n - 1) / n * special.kn(2, n * m / T)).sum()
assert_almost_equal(hrg.density(),
density,
delta=1e-12,
msg='incorrect density')
def integrand(p):
E = np.sqrt(m * m + p * p)
return p * p * E / (np.exp(E / T) + sign)
energy_density = prefactor * integrate.quad(integrand, 0, 10)[0]
assert_almost_equal(hrg.energy_density(),
energy_density,
delta=1e-12,
msg='incorrect energy density')
def integrand(p):
E = np.sqrt(m * m + p * p)
return p**4 / (3 * E) / (np.exp(E / T) + sign)
pressure = prefactor * integrate.quad(integrand, 0, 10)[0]
assert_almost_equal(hrg.pressure(),
pressure,
delta=1e-12,
msg='incorrect pressure')
with assert_warns_regex(Warning, 'high particlization temperature'):
HRG(.193)
def assert_warns_message(expected_warning, expected_message, *args, **kwargs):
expected_regex = re.escape(expected_message)
return assert_warns_regex(expected_warning, expected_regex, *args,
**kwargs)
def test_surface():
volume = np.random.uniform(10, 100)
tau = np.random.uniform(.5, 5.)
x = np.atleast_2d([tau, 0., 0.])
sigma = np.atleast_2d([volume/tau, 0., 0.])
v = np.zeros((1, 2))
surf = Surface(x, sigma, v)
assert surf.boost_invariant, 'Surface should be boost-invariant.'
assert_almost_equal(
surf.volume, volume, delta=1e-12,
msg='incorrect volume'
)
ymax = np.random.uniform(.5, 2.)
surf = Surface(x, sigma, v, ymax=ymax)
assert_almost_equal(
surf.volume, 2*ymax*volume, delta=1e-12,
msg='incorrect volume'
)
x = np.random.uniform(0, 10, size=(1, 4))
# ensure sigma is timelike (sigma^2 > 0) so that the volume is positive
sigma = np.random.uniform([3, -1, -1, -1], [4, 1, 1, 1], size=(1, 4))
v = np.random.uniform(-.5, .5, size=(1, 3))
surf = Surface(x, sigma, v)
assert not surf.boost_invariant, 'Surface should not be boost-invariant.'
u = np.insert(v, 0, 1) / np.sqrt(1 - (v*v).sum())
volume = np.inner(sigma, u)
assert_almost_equal(
surf.volume, volume, delta=1e-12,
msg='incorrect volume'
)
with assert_warns_regex(Warning, 'ymax has no effect for 3D surfaces'):
Surface(x, sigma, v, ymax=1.)
with assert_warns_regex(Warning, 'total freeze-out volume is negative'):
Surface(x, np.concatenate([[[0]], -v], axis=1), v)
with assert_raises_regex(ValueError, 'invalid shape'):
Surface(
np.ones((1, 1)),
np.ones((1, 1)),
np.ones((1, 1)),
)
with assert_raises_regex(ValueError, 'invalid shape'):
Surface(
np.ones((1, 4)),
np.ones((1, 3)),
np.ones((1, 2)),
)
with assert_raises_regex(ValueError, 'invalid shape'):
Surface(
np.ones((2, 4)),
np.ones((2, 4)),
np.ones((3, 3)),
)
def test_surface():
volume = np.random.uniform(10, 100)
tau = np.random.uniform(.5, 5.)
x = [tau, 0, 0]
sigma = [volume/tau, 0, 0]
v = [0, 0]
surf = Surface(x, sigma, v)
assert surf.boost_invariant, 'Surface should be boost-invariant.'
assert_almost_equal(
surf.volume, volume, delta=1e-12,
msg='incorrect volume'
)
ymax = np.random.uniform(.5, 2.)
surf = Surface(x, sigma, v, ymax=ymax)
assert_almost_equal(
surf.volume, 2*ymax*volume, delta=1e-12,
msg='incorrect volume'
)
x = np.random.uniform(0, 10, size=(1, 4))
# ensure sigma is timelike (sigma^2 > 0) so that the volume is positive
sigma = np.random.uniform([3, -1, -1, -1], [4, 1, 1, 1], size=(1, 4))
v = np.random.uniform(-.5, .5, size=(1, 3))
surf = Surface(x, sigma, v)
assert not surf.boost_invariant, 'Surface should not be boost-invariant.'
u = np.insert(v, 0, 1) / np.sqrt(1 - (v*v).sum())
volume = np.inner(sigma, u)
assert_almost_equal(
surf.volume, volume, delta=1e-12,
msg='incorrect volume'
)
with assert_warns_regex(Warning, 'ymax has no effect for a 3D surface'):
Surface(x, sigma, v, ymax=np.random.rand())
with assert_warns_regex(Warning, 'total freeze-out volume is negative'):
Surface(x, np.concatenate([[[0]], -v], axis=1), v)
with assert_raises_regex(
ValueError,
'number of spacetime dimensions of x, sigma, and/or v'
):
Surface([1, 0], [1, 0], 0)
with assert_raises_regex(
ValueError,
'number of spacetime dimensions of x, sigma, and/or v'
):
Surface(
np.ones((1, 4)),
np.ones((1, 3)),
np.ones((1, 2)),
)
with assert_raises_regex(
ValueError,
'number of elements of x, sigma, and/or v do not match'
):
Surface(
np.ones((2, 4)),
np.ones((2, 4)),
np.ones((3, 3)),
)
with assert_raises_regex(
ValueError,
'number of elements of pi components do not match'
):
Surface(
np.ones((3, 4)),
np.ones((3, 4)),
np.ones((3, 3)),
pi=dict(
xx=np.ones(3),
yy=np.ones(3),
xy=np.ones(3),
xz=np.ones(3),
yz=np.ones(4),
)
)
with assert_raises_regex(
ValueError,
'number of elements of Pi do not match'
):
Surface(
np.ones((3, 4)),
np.ones((3, 4)),
np.ones((3, 3)),
Pi=np.ones(4)
)
def test_duplicate_data():
with assert_warns_regex(
RuntimeWarning,
r"Detected zero distance between samples ([0-9and,\s]*). Consider removing duplicates to avoid errors in downstream processing.",
):
build_graph(np.vstack([data, data[:10]]), n_pca=20, decay=10, thresh=0)
