def test_outerproduct_transpose(dtype, num_legs, num_charges):
np.random.seed(10)
Ds1 = np.arange(2, 2 + num_legs)
Ds2 = np.arange(2 + num_legs, 2 + 2 * num_legs)
is1 = [
Index(
BaseCharge(np.random.randint(-5, 6, (num_charges, Ds1[n])),
charge_types=[U1Charge] * num_charges), False)
for n in range(num_legs)
]
is2 = [
Index(
BaseCharge(np.random.randint(-5, 6, (num_charges, Ds2[n])),
charge_types=[U1Charge] * num_charges), False)
for n in range(num_legs)
]
o1 = np.arange(num_legs)
o2 = np.arange(num_legs)
np.random.shuffle(o1)
np.random.shuffle(o2)
a = BlockSparseTensor.random(is1, dtype=dtype).transpose(o1)
b = BlockSparseTensor.random(is2, dtype=dtype).transpose(o2)
abdense = ncon([a.todense(), b.todense()], [
-np.arange(1, num_legs + 1, dtype=np.int16),
-num_legs - np.arange(1, num_legs + 1, dtype=np.int16)
])
ab = outerproduct(a, b)
np.testing.assert_allclose(ab.todense(), abdense)
def test_outerproduct_transpose_reshape(dtype, num_legs, num_charges):
np.random.seed(10)
Ds1 = np.arange(2, 2 + num_legs)
Ds2 = np.arange(2 + num_legs, 2 + 2 * num_legs)
is1 = [
Index(
BaseCharge(np.random.randint(-5, 6, (Ds1[n], num_charges)),
charge_types=[U1Charge] * num_charges), False)
for n in range(num_legs)
]
is2 = [
Index(
BaseCharge(np.random.randint(-5, 6, (Ds2[n], num_charges)),
charge_types=[U1Charge] * num_charges), False)
for n in range(num_legs)
]
o1 = np.arange(num_legs)
o2 = np.arange(num_legs)
np.random.shuffle(o1)
np.random.shuffle(o2)
a = BlockSparseTensor.random(is1, dtype=dtype).transpose(o1)
b = BlockSparseTensor.random(is2, dtype=dtype).transpose(o2)
a = a.reshape([np.prod(a.shape)])
b = b.reshape([np.prod(b.shape)])
abdense = ncon([a.todense(), b.todense()], [[-1], [-2]])
ab = outerproduct(a, b)
assert ab.ndim == 2
np.testing.assert_allclose(ab.todense(), abdense)