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)))
