def test_randlin():
randlin = SG.Randlin(n_samples=100, n_features=10, n_informative=3,
effective_rank=5, coef=True, bias=0.0, noise=1.0, random_state=0)
X, y = randlin.regression_task()
tasks.assert_regression(X, y, 100)
assert_equal(X.shape, (100, 10), "X shape mismatch")
assert_equal(y.shape, (100, 1), "y shape mismatch")
c = randlin.ground_truth
assert_equal(c.shape, (10,), "coef shape mismatch")
assert_equal(sum(c != 0.0), 3, "Unexpected number of informative features")
# Test that y ~= np.dot(X, c) + bias + N(0, 1.0)
assert_approx_equal(np.std(y[:,0] - np.dot(X, c)), 1.0, significant=2)
def test_assert_regression(self):
# things that work:
tasks.assert_regression(
rnd('float32', 4, 2), rnd('float64', 4, 1))
tasks.assert_regression(
rnd('float64', 4, 2), rnd('float32', 4, 3))
tasks.assert_regression(
rnd('float64', 4, 2), rnd('float32', 4, 3), 4)
# things that break:
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('int8', 4, 2), rnd('float32', 4, 1)) # X not float
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float32', 4, 2), rnd('int32', 4, 1)) # y not float
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float32', 4, 2), rnd('float32', 5, 1)) # y wrong len
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float32', 4, 2), rnd('float32', 4)) # y wrong rank
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float32', 4, 2), rnd('float32', 4, 7, 3)) # y wrong rank
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float32', 4, 2, 2), rnd('float32', 4, 1)) # X wrong rank
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float64', 4), rnd('float32', 4, 1)) # X wrong rank
self.assertRaises(AssertionError, tasks.assert_regression,
rnd('float64', 4, 3), rnd('float32', 4, 1), 5) # N mismatch
def check_regression_XY(X, Y, N=None):
assert_regression(X, y, N)
def test_sparse_uncorrelated():
X, y = SG.SparseUncorrelated(n_samples=5, n_features=10,
random_state=0).regression_task()
tasks.assert_regression(X, y)
assert_equal(X.shape, (5, 10), "X shape mismatch")
assert_equal(y.shape, (5, 1), "y shape mismatch")
