def test_exponential_model_update():
model = ExponentialModel(shape=0.001, rate=0.001)
data = np.array([0.4692680, 3.0101214, 1.3167456, 0.9129425, 0.1696248])
model.update(data)
assert model.n_samples_ == 5
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_exponential_mv_check_model_input():
modelA = ExponentialModel(shape=25, rate=1000)
modelB = ExponentialModel(shape=25, rate=1000)
with raises(TypeError):
ExponentialMVTest(models=[modelA, modelB])
def test_exponential_model_mean_var():
model = ExponentialModel(shape=0.001, rate=0.001)
assert np.isnan(model.ppmean())
assert np.isnan(model.ppvar())
def test_exponential_model_stats():
model = ExponentialModel(shape=25, rate=1000)
assert model.ppmean() == approx(41.66666666)
assert model.ppvar() == approx(1887.077294)
def test_exponential_model_pppdf_x():
model = ExponentialModel(shape=25, rate=1000)
assert model.pppdf([-1, 0, 20,
100]) == approx([0, 0.025, 0.0149394821, 0.0020976363])