def test_poisson_seeding():
poisson1 = Poisson(seed=SEED)
poisson2 = Poisson(seed=SEED)
assert poisson1 != poisson2
assert poisson1.lam == poisson2.lam
assert all(
np.array_equal(i, j) for i, j in zip(poisson1.data, poisson2.data))
def test_poisson_sampling():
poisson = Poisson(seed=SEED, N=7, xlim=(0, 10))
single = poisson.sample()
assert single == 12
sample = poisson.sample(7)
test = [8, 7, 12, 8, 11, 8, 14]
for i, j in zip(sample, test):
assert abs(i - j) < TOLERANCE
def test_poisson_variables():
poisson = Poisson(seed=SEED, N=7, xlim=(-3, 3))
assert poisson.mean == 10.398429625910502
assert poisson.median == 10
assert poisson.mode == 10
assert poisson.variance == 10.398429625910502
assert poisson.skewness == 0.31011025029450545
def test_poisson_printing():
poisson = Poisson(seed=SEED, N=11)
for s in ['N=11', 'rand=0.01']:
assert s in str(poisson)
for s in [
'N=11', 'xlim=(0, 31.195288877731507)', 'seed=31415927',
'lam=10.398429625910502', 'rand=0.01'
]:
assert s in repr(poisson)
def test_poisson_non_random():
poisson = Poisson(rand=None, lam=2, xlim=(0, 10), N=7)
x, y = poisson.data
for i, j in zip(x, [0, 1, 3, 5, 6, 8, 10]):
assert abs(i - j) < TOLERANCE
for i, j in zip(y, [
1.35335283e-01, 2.70670566e-01, 1.80447044e-01, 3.60894089e-02,
1.20298030e-02, 8.59271640e-04, 3.81898506e-05
]):
assert abs(i - j) < TOLERANCE
def test_poisson_random():
x_test = [0, 1, 3, 5, 6, 8, 10]
y_test = [
0.00634749, 0.0054957, 0.00242271, 0.04049159, 0.05722324, 0.10456898,
0.12780699
]
poisson = Poisson(seed=SEED, N=7, xlim=(0, 10))
x, y = poisson.data
assert poisson.lam == 10.398429625910502
for i, j in zip(x, x_test):
assert abs(i - j) < TOLERANCE
for i, j in zip(y, y_test):
assert abs(i - j) < TOLERANCE
def test_poisson_exceptions():
with pytest.raises(GwydionError):
Poisson(lam=2j)
with pytest.raises(GwydionError):
Poisson(lam='1234')
def test_poisson_creation():
poisson = Poisson()
assert poisson