def test_validate(self):
# python list
obs = _validate([0, 2, 1, 3])
npt.assert_array_equal(obs, np.array([0, 2, 1, 3]))
self.assertEqual(obs.dtype, int)
# numpy array (no copy made)
data = np.array([0, 2, 1, 3])
obs = _validate(data)
npt.assert_array_equal(obs, data)
self.assertEqual(obs.dtype, int)
self.assertTrue(obs is data)
# single element
obs = _validate([42])
npt.assert_array_equal(obs, np.array([42]))
self.assertEqual(obs.dtype, int)
self.assertEqual(obs.shape, (1,))
# suppress casting to int
obs = _validate([42.2, 42.1, 0], suppress_cast=True)
npt.assert_array_equal(obs, np.array([42.2, 42.1, 0]))
self.assertEqual(obs.dtype, float)
# all zeros
obs = _validate([0, 0, 0])
npt.assert_array_equal(obs, np.array([0, 0, 0]))
self.assertEqual(obs.dtype, int)
# all zeros (single value)
obs = _validate([0])
npt.assert_array_equal(obs, np.array([0]))
self.assertEqual(obs.dtype, int)
def test_validate_invalid_input(self):
# wrong dtype
with self.assertRaises(TypeError):
_validate([0, 2, 1.2, 3])
# wrong number of dimensions (2-D)
with self.assertRaises(ValueError):
_validate([[0, 2, 1, 3], [4, 5, 6, 7]])
# wrong number of dimensions (scalar)
with self.assertRaises(ValueError):
_validate(1)
# negative values
with self.assertRaises(ValueError):
_validate([0, 0, 2, -1, 3])
