def test_BaseCharge_unique():
D = 3000
B = 5
np.random.seed(10)
q = np.random.randint(-B // 2, B // 2 + 1, (D, 2)).astype(np.int16)
Q = BaseCharge(charges=q, charge_types=[U1Charge, U1Charge])
#this call has to be to custom unique to ensure correct ordering
expected = unique(q,
return_index=True,
return_inverse=True,
return_counts=True)
actual = Q.unique(return_index=True,
return_inverse=True,
return_counts=True)
assert np.all(actual[0].charges == expected[0])
assert np.all(actual[1] == expected[1])
assert np.all(actual[2] == expected[2])
assert np.all(actual[3] == expected[3])
_ = Q.unique_charges # switch internally to unique-labels representation
actual = Q.unique(return_index=True,
return_inverse=True,
return_counts=True)
assert np.all(actual[0].charges == expected[0])
assert np.all(actual[1] == expected[1])
assert np.all(actual[2] == expected[2])
assert np.all(actual[3] == expected[3])
def test_BaseCharge_single_unique():
D = 30
np.random.seed(10)
q = np.ones((D, 2), dtype=np.int16)
Q = BaseCharge(charges=q, charge_types=[U1Charge, U1Charge])
expected = np.unique(q,
return_index=True,
return_inverse=True,
return_counts=True,
axis=0)
actual = Q.unique(return_index=True,
return_inverse=True,
return_counts=True)
assert np.all(actual[0].charges == expected[0])
assert np.all(actual[1] == expected[1])
assert np.all(actual[2] == expected[2])
assert np.all(actual[3] == expected[3])
expected = np.unique(q, axis=0)
actual = Q.unique()
assert np.all(actual.charges == expected)
def test_BaseCharge_unique():
D = 3000
B = 5
np.random.seed(10)
q = np.random.randint(-B // 2, B // 2 + 1, (2, D)).astype(np.int16)
Q = BaseCharge(charges=q, charge_types=[U1Charge, U1Charge])
expected = np.unique(q,
return_index=True,
return_inverse=True,
return_counts=True,
axis=1)
actual = Q.unique(return_index=True,
return_inverse=True,
return_counts=True)
assert np.all(actual[0].charges == expected[0])
assert np.all(actual[1] == expected[1])
assert np.all(actual[2] == expected[2])
assert np.all(actual[3] == expected[3])
