def test_compute_N_03(self):
k = 0.0
p = np.array([0.0, 0.05], dtype=np.float32)
normal_p = np.array([-np.sqrt(0.5), -np.sqrt(0.5)])
a = np.array([0.0, 0.00], dtype=np.float32)
b = np.array([0.0, 0.10], dtype=np.float32)
pOnElement = True
zPy = IH2.compute_n(k, p, normal_p, a, b, pOnElement)
zC = IH2C.compute_n(k, p, normal_p, a, b, pOnElement)
self.assertAlmostEqual(zPy, zC, msg="{} != {}".format(zPy, zC))
def test_compute_N_04(self):
k = 10.0
p = np.array([0.0, 0.05], dtype=np.float32)
normal_p = np.array([-np.sqrt(0.5), -np.sqrt(0.5)])
a = np.array([0.0, 0.00], dtype=np.float32)
b = np.array([0.0, 0.10], dtype=np.float32)
pOnElement = True
zPy = IH2.compute_n(k, p, normal_p, a, b, pOnElement)
zC = IH2C.compute_n(k, p, normal_p, a, b, pOnElement)
# note, how accuracy here is reduced to only 3 digits after the decimal dot.
# I don't believe this is because of buggy code but because of error accumulation
# being different for the C and the Python codes.
self.assertAlmostEqual(zPy, zC, 3, msg="{} != {}".format(zPy, zC))