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Use local RNG in MultiTensor tests #1439

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83 changes: 44 additions & 39 deletions src/openfermion/contrib/representability/_multitensor_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,10 +6,15 @@
from openfermion.contrib.representability._dualbasis import DualBasis, DualBasisElement


def test_tmap():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
@pytest.fixture(name='rng')
def rng_fixture() -> np.random.Generator:
return np.random.default_rng(0)


def test_tmap(rng):
a = rng.random((5, 5))
b = rng.random((4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -23,13 +28,13 @@ def test_tmap():
assert np.allclose(iterated_tensor.data, tmp_tensors[idx])


def test_multitensor_init():
def test_multitensor_init(rng):
"""
Testing the generation of a multitensor object with random tensors
"""
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
a = rng.random((5, 5))
b = rng.random((4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -43,10 +48,10 @@ def test_multitensor_init():
assert np.isclose(mt.vec_dim, 5**2 + 4**2 + 3**2)


def test_multitensor_offsetmap():
a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
def test_multitensor_offsetmap(rng):
a = rng.random((5, 5, 5, 5))
b = rng.random((4, 4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -55,10 +60,10 @@ def test_multitensor_offsetmap():
assert mt.off_set_map == {'a': 0, 'b': 5**4, 'c': 5**4 + 4**3}


def test_vectorize_test():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
def test_vectorize_test(rng):
a = rng.random((5, 5))
b = rng.random((4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -67,9 +72,9 @@ def test_vectorize_test():
vec = np.vstack((vec, ct.vectorize()))
assert np.allclose(vec, mt.vectorize_tensors())

a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
a = rng.random((5, 5, 5, 5))
b = rng.random((4, 4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -79,10 +84,10 @@ def test_vectorize_test():
assert np.allclose(vec, mt.vectorize_tensors())


def test_add_dualelement():
a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
def test_add_dualelement(rng):
a = rng.random((5, 5, 5, 5))
b = rng.random((4, 4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -107,9 +112,9 @@ def test_add_dualelement():
assert isinstance(mt.dual_basis[1], DualBasisElement)


def test_multitensor_init_isolation():
def test_multitensor_init_isolation(rng):
# Test that different MultiTensor instances don't share the same dual_basis.
a = np.random.random((2, 2))
a = rng.random((2, 2))
at = Tensor(tensor=a, name='a')
mt1 = MultiTensor([at])
mt2 = MultiTensor([at])
Expand All @@ -122,10 +127,10 @@ def test_multitensor_init_isolation():
assert len(mt2.dual_basis) == 0


def test_synthesis_element():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
def test_synthesis_element(rng):
a = rng.random((5, 5))
b = rng.random((4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -147,10 +152,10 @@ def test_synthesis_element():
assert [at.data[0, 1], at.data[1, 0]] == [at(0, 1), at(1, 0)]


def test_synthesis_dualbasis():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
def test_synthesis_dualbasis(rng):
a = rng.random((5, 5))
b = rng.random((4, 4))
c = rng.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
Expand All @@ -168,7 +173,7 @@ def test_synthesis_dualbasis():
assert c.shape == (1, 1)


def test_dual_basis_element():
def test_dual_basis_element(rng):
de = DualBasisElement()
de_2 = DualBasisElement()
db_0 = de + de_2
Expand All @@ -177,7 +182,7 @@ def test_dual_basis_element():
assert isinstance(db_1, DualBasis)

dim = 2
opdm = np.random.random((dim, dim))
opdm = rng.random((dim, dim))
opdm = (opdm.T + opdm) / 2
opdm = Tensor(tensor=opdm, name='opdm')
rdm = MultiTensor([opdm])
Expand Down Expand Up @@ -206,9 +211,9 @@ def generate_dual_basis_element(i, j):
assert np.allclose(test_oqdm.reshape((dim, dim)), np.eye(dim) - opdm.data)


def test_cover_make_offset_dict():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
def test_cover_make_offset_dict(rng):
a = rng.random((5, 5))
b = rng.random((4, 4))
c = rng.random((3, 3))
with pytest.raises(TypeError):
_ = MultiTensor.make_offset_dict([a, b, c])
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