def test_poisson():
"""Test basic functionality of UoI_Lasso and that it finds right model"""
n_features = 20
n_inf = 10
X, y, w, b = make_poisson_regression(n_samples=200,
n_features=n_features,
n_informative=n_inf,
random_state=10)
poisson = UoI_Poisson(comm=MPI.COMM_WORLD)
poisson.fit(X, y)
assert (np.sign(abs(w)) == np.sign(abs(poisson.coef_))).mean() >= .6
def test_UoI_Poisson_all_zeros():
"""Test that UoI Poisson correctly fits the data when the response variable
is all zeros."""
n_features = 5
n_samples = 100
X = np.random.normal(size=(n_samples, n_features))
y = np.zeros(n_samples)
poisson = UoI_Poisson()
poisson.fit(X, y)
assert_equal(poisson.intercept_, -np.inf)
assert_equal(poisson.coef_, np.zeros(n_features))
def test_UoI_Poisson():
"""Tests the UoI Poisson fitter with lbfgs solver."""
n_features = 3
n_samples = 5000
# create data
X, y, beta, _ = make_poisson_regression(n_samples=n_samples,
n_features=n_features,
n_informative=n_features,
beta=np.array([0., 1.0, 1.5]),
random_state=2332)
# lbfgs
poisson = UoI_Poisson(n_lambdas=48, n_boots_sel=30, n_boots_est=30,
alphas=np.array([1.0]), warm_start=False)
poisson.fit(X, y)
assert_allclose(poisson.coef_, beta, atol=0.5)