def _norm(distribution_unnormalized):
"""
Integrate distribution over all values
Use min of K+/Pi- system mass as momentum is undefined below this
"""
return bmfi.trapezoid(distribution_unnormalized,
mass_k_plus + mass_pi_minus, integration_max,
integration_dt)
def integrate_decay_rate(coeffs):
"""
Integrate previously angle integrated decay rate function over q^2 for particular amplitude coefficients
"""
return bmfi.trapezoid(
lambda q2: decay_rate_angle_integrated(coeffs, q2),
q2_min,
q2_max,
integration_dt
)
def test_trapezoid_supports_float64(self):
"""
Check that trapezoid() supports integrals that return tf.float64
"""
actual = bmfi.trapezoid(
lambda x: tf.cast(x + 3.0, dtype=tf.float64),
-5.0,
5.0,
0.1,
)
self.assertEqual(tf.float64, actual.dtype,
'Check returned dtype is float64')
# Check within tolerance as we're using bins
nt.assert_allclose(30.0, actual.numpy(), atol=1e-4, rtol=0.001)
def test_trapezoid(self):
"""
Check that trapezoid() returns expected values. Uses 10_000 bins for each.
"""
# Check for different lists of coefficients
for name, integral, start, stop, expected in self.test_integrals:
with self.subTest(name=name):
actual = bmfi.trapezoid(
integral,
start,
stop,
(stop - start) / 1e4,
)
# Check within tolerance as we're using bins
nt.assert_allclose(expected,
actual.numpy(),
atol=1e-4,
rtol=0.001)
def test_trapezoid_supports_complex64(self):
"""
Check that trapezoid() supports integrals that return tf.complex64
"""
actual = bmfi.trapezoid(
lambda x: tf.complex(x + 3.0, x + 4.0),
-5.0,
5.0,
0.1,
)
self.assertEqual(tf.complex64, actual.dtype,
'Check returned dtype is complex64')
# Check within tolerance as we're using bins
nt.assert_allclose(30.0,
tf.math.real(actual).numpy(),
atol=1e-4,
rtol=0.001)
nt.assert_allclose(40.0,
tf.math.imag(actual).numpy(),
atol=1e-4,
rtol=0.001)
def _integrate_distribution_around_k892(distribution):
"""Integrate distribution between +/- 100 MeV of K892 mass"""
return bmfi.trapezoid(distribution, mass_k892 - 0.1, mass_k892 + 0.1,
integration_dt)