def test_poisson_model_update():
model = PoissonModel(shape=0.001, rate=0.001)
data = np.array([5, 4, 4, 4, 2])
model.update(data)
assert model.n_samples_ == 5
def test_poisson_mv_check_model_input():
modelA = PoissonModel(shape=25, rate=1000)
modelB = PoissonModel(shape=25, rate=1000)
with raises(TypeError):
PoissonMVTest(models=[modelA, modelB])
def test_poisson_ab_check_models():
modelA = PoissonModel(shape=25, rate=1000)
modelB = ExponentialModel(shape=25, rate=1000)
with raises(TypeError):
PoissonABTest(modelA=modelA, modelB=modelB)
def test_poisson_model_stats():
model = PoissonModel(shape=25, rate=1000)
assert model.ppmean() == approx(0.025)
assert model.ppvar() == approx(0.025025)
def test_poisson_model_pppdf_x():
model = PoissonModel(shape=25, rate=1000)
assert model.pppdf([-1, 0, 2, 20]) == approx(
[0, 0.975322095, 0.000316346671, 1.683587039e-48])
def test_uniform_ab_check_models():
modelA = UniformModel()
modelB = PoissonModel()
with raises(TypeError):
UniformABTest(modelA=modelA, modelB=modelB)