def test_circles_replicable(self): """Test if the data generation is replicable with a specified `seed` Tests: - return the same value if raised with the same seed - return different values if noise or seed is different """ seed = 42 noise = 0.1 circ0 = synthetic.circles(n_samples=100, noise=noise, n_classes=2, seed=seed) circ1 = synthetic.circles(n_samples=100, noise=noise, n_classes=2, seed=seed) np.testing.assert_array_equal(circ0.data, circ1.data) np.testing.assert_array_equal(circ0.target, circ1.target) circ1 = synthetic.circles(n_samples=100, noise=noise, n_classes=2, seed=seed + 1) self.assertRaises(AssertionError, np.testing.assert_array_equal, circ0.data, circ1.data) self.assertRaises(AssertionError, np.testing.assert_array_equal, circ0.target, circ1.target) circ1 = synthetic.circles(n_samples=100, noise=noise / 2., n_classes=2, seed=seed) self.assertRaises(AssertionError, np.testing.assert_array_equal, circ0.data, circ1.data)
def test_circles_replicable(self): """Test if the data generation is replicable with a specified `seed` Tests: - return the same value if raised with the same seed - return different values if noise or seed is different """ seed = 42 noise = 0.1 circ0 = synthetic.circles( n_samples=100, noise=noise, n_classes=2, seed=seed) circ1 = synthetic.circles( n_samples=100, noise=noise, n_classes=2, seed=seed) np.testing.assert_array_equal(circ0.data, circ1.data) np.testing.assert_array_equal(circ0.target, circ1.target) circ1 = synthetic.circles( n_samples=100, noise=noise, n_classes=2, seed=seed + 1) self.assertRaises(AssertionError, np.testing.assert_array_equal, circ0.data, circ1.data) self.assertRaises(AssertionError, np.testing.assert_array_equal, circ0.target, circ1.target) circ1 = synthetic.circles( n_samples=100, noise=noise / 2., n_classes=2, seed=seed) self.assertRaises(AssertionError, np.testing.assert_array_equal, circ0.data, circ1.data)
def test_circles(self): """Test if the circles are generated correctly Tests: - return type is `Dataset` - returned `data` shape is (n_samples, n_features) - returned `target` shape is (n_samples,) - set of unique classes range is [0, n_classes) TODO: - all points have the same radius, if no `noise` specified """ n_samples = 100 n_classes = 2 circ = synthetic.circles(n_samples = n_samples, noise = None, n_classes = n_classes) self.assertIsInstance(circ, datasets.base.Dataset) self.assertTupleEqual(circ.data.shape, (n_samples,2)) self.assertTupleEqual(circ.target.shape, (n_samples,)) self.assertSetEqual(set(circ.target), set(range(n_classes)))
def test_circles(self): """Test if the circles are generated correctly Tests: - return type is `Dataset` - returned `data` shape is (n_samples, n_features) - returned `target` shape is (n_samples,) - set of unique classes range is [0, n_classes) TODO: - all points have the same radius, if no `noise` specified """ n_samples = 100 n_classes = 2 circ = synthetic.circles(n_samples=n_samples, noise=None, n_classes=n_classes) self.assertIsInstance(circ, datasets.base.Dataset) self.assertTupleEqual(circ.data.shape, (n_samples, 2)) self.assertTupleEqual(circ.target.shape, (n_samples, )) self.assertSetEqual(set(circ.target), set(range(n_classes)))