def test_generator_input(self):
"""Tests that ``np.random.default_rng`` passes through a Generator when its passed as input."""
rng1 = random.default_rng()
rng2 = random.default_rng(rng1)
assert rng1 == rng2
def test_no_input(self):
"""Tests that np.random.default_rng() returns a generator object when
no input is passed."""
rng = random.default_rng()
assert isinstance(rng, random.Generator)
output = rng.random((3, ))
assert isinstance(output, np.tensor)
def test_seed_reproducible(self):
"""Tests that setting a seed to ``default_rng`` gives reproducible results."""
seed = 42
size = (3, 2)
rng1 = random.default_rng(seed)
rng2 = random.default_rng(seed)
assert isinstance(rng1, random.Generator)
assert isinstance(rng2, random.Generator)
mat1 = rng1.random(size=size)
mat2 = rng2.random(size=size)
assert np.all(mat1 == mat2)
mat1_2 = rng1.normal(size=size)
mat2_2 = rng2.normal(size=size)
assert np.all(mat1_2 == mat2_2)
def test_bit_generators(self, bitgen_cls):
"""Tests that np.random.default_rng() returns a generator when passed a bit
generator. Also checks that the bit generators are imported into the namespace."""
bitgen = bitgen_cls()
rng = random.default_rng(bitgen)
assert isinstance(rng, random.Generator)
assert isinstance(rng.bit_generator, bitgen_cls)
output = rng.random((3, ))
assert isinstance(output, np.tensor)
"logistic",
"lognormal",
"normal",
"poisson",
"rayleigh",
"standard_cauchy",
"standard_exponential",
"standard_normal",
"uniform",
]
bit_generator_classes = [
random.MT19937, random.PCG64, random.Philox, random.SFC64
]
general_gen = random.default_rng()
class TestGeneratorDistributions:
@pytest.mark.parametrize("distribution", distributions_no_extra_input)
def test_generator_distributions(self, distribution):
"""Tests the distributions from a generator object that don't require
additional distribution-specific parameters to make sure they have a
``requires_grad`` attribute."""
size = (3, )
output = getattr(general_gen, distribution)(size=size)
assert isinstance(output, np.tensor)
assert output.shape == size
assert output.requires_grad == True