def test_identity_dimension_when_existing_dim_split_with_wildcard(self):
arr = ArrayWithUnits(np.zeros((12, )), [ContrivedDimension(10)])
rs = arr.reshape((2, -1, 3))
self.assertIsInstance(rs, ArrayWithUnits)
self.assertIsInstance(rs.dimensions[0], IdentityDimension)
self.assertIsInstance(rs.dimensions[1], IdentityDimension)
self.assertIsInstance(rs.dimensions[2], IdentityDimension)
def test_can_create_new_array_from_example(self):
arr = ArrayWithUnits(np.zeros((100, 10)),
[ContrivedDimension(10),
ContrivedDimension2(10)])
arr2 = ArrayWithUnits.from_example(np.zeros((90, 5)), arr)
self.assertSequenceEqual(arr.dimensions, arr2.dimensions)
self.assertEqual((90, 5), arr2.shape)
def test_can_add_dimension_of_size_one_to_1d_array(self):
arr = ArrayWithUnits(np.zeros((3, )), [ContrivedDimension(10)])
rs = arr.reshape((1, 1, arr.size))
self.assertIsInstance(rs, ArrayWithUnits)
self.assertIsInstance(rs.dimensions[0], IdentityDimension)
self.assertIsInstance(rs.dimensions[1], IdentityDimension)
self.assertIsInstance(rs.dimensions[2], ContrivedDimension)
def test_zeros(self):
arr = ArrayWithUnits(np.zeros((100, 10)),
[ContrivedDimension(10),
ContrivedDimension2(10)])
arr2 = ArrayWithUnits.zeros(arr)
self.assertEqual(arr.shape, arr2.shape)
self.assertSequenceEqual(arr.dimensions, arr2.dimensions)
np.testing.assert_allclose(arr2, 0)
def test_can_maintain_array_with_units_when_squeezing_2d(self):
arr = ArrayWithUnits(np.zeros((1, 10)),
[ContrivedDimension(10),
ContrivedDimension2(10)])
squeezed = arr.squeeze()
self.assertEqual((10, ), squeezed.shape)
self.assertIsInstance(squeezed, ArrayWithUnits)
self.assertIsInstance(squeezed.dimensions[0], ContrivedDimension2)
def test_can_reshape_and_downgrade_to_identity_dimension(self):
arr = ArrayWithUnits(np.zeros((100, 10)),
[ContrivedDimension(10),
ContrivedDimension2(10)])
flattened = arr.reshape((-1, ))
self.assertEqual((1000, ), flattened.shape)
self.assertIsInstance(flattened, ArrayWithUnits)
self.assertIsInstance(flattened.dimensions[0], IdentityDimension)
def test_size_is_not_modified_on_example_dimensions(self):
arr = ArrayWithUnits(np.zeros((100, 10)),
[ContrivedDimension(10),
ContrivedDimension2(10)])
arr2 = ArrayWithUnits.from_example(np.zeros((90, 5)), arr)
self.assertEqual(100, arr.dimensions[0].size)
self.assertEqual(10, arr.dimensions[1].size)
self.assertEqual(90, arr2.dimensions[0].size)
self.assertEqual(5, arr2.dimensions[1].size)
def test_zeros_like(self):
arr = ArrayWithUnits(np.zeros((3, 2, 10)), [
ContrivedDimension(10),
IdentityDimension(),
ContrivedDimension2(10)
])
zeros = arr.zeros_like()
self.assertEqual(zeros.shape, arr.shape)
self.assertEqual(zeros.dimensions, arr.dimensions)
np.testing.assert_allclose(0, zeros)
def test_can_maintain_array_with_units_when_reshaping_3d(self):
arr = ArrayWithUnits(np.zeros((3, 1, 10)), [
ContrivedDimension(10),
IdentityDimension(),
ContrivedDimension2(10)
])
squeezed = arr.reshape((3, 10))
self.assertEqual((3, 10), squeezed.shape)
self.assertIsInstance(squeezed, ArrayWithUnits)
self.assertIsInstance(squeezed.dimensions[0], ContrivedDimension)
self.assertIsInstance(squeezed.dimensions[1], ContrivedDimension2)
def test_squeeze_with_no_single_dimension_is_unchanged(self):
arr = ArrayWithUnits(np.zeros((3, 2, 10)), [
ContrivedDimension(10),
IdentityDimension(),
ContrivedDimension2(10)
])
squeezed = arr.squeeze()
self.assertEqual((3, 2, 10), squeezed.shape)
self.assertIsInstance(squeezed, ArrayWithUnits)
self.assertIsInstance(squeezed.dimensions[0], ContrivedDimension)
self.assertIsInstance(squeezed.dimensions[1], IdentityDimension)
self.assertIsInstance(squeezed.dimensions[2], ContrivedDimension2)
def test_max_supports_multiple_axes(self):
raw = np.random.random_sample((10, 9, 8, 7))
arr = ArrayWithUnits(raw,
dimensions=[
ContrivedDimension(10),
IdentityDimension(),
IdentityDimension(),
ContrivedDimension2(10)
])
result = arr.max(axis=(1, 2))
self.assertEqual((10, 7), result.shape)
self.assertIsInstance(result, ArrayWithUnits)
self.assertEqual(2, len(result.dimensions))
self.assertIsInstance(result.dimensions[0], ContrivedDimension)
self.assertIsInstance(result.dimensions[1], ContrivedDimension2)
def test_maintain_array_with_units_with_boolean_condition(self):
arr = ArrayWithUnits(
np.random.random_sample((10, 100)) - 0.5,
[ContrivedDimension(10),
ContrivedDimension2(10)])
binary = arr >= 0
self.assertIsInstance(binary, ArrayWithUnits)
self.assertIsInstance(arr.dimensions[0], ContrivedDimension)
self.assertIsInstance(arr.dimensions[1], ContrivedDimension2)
def test_max_supports_keepdims(self):
raw = np.random.random_sample((10, 9, 8, 7))
arr = ArrayWithUnits(raw,
dimensions=[
ContrivedDimension(10),
ContrivedDimension2(10),
ContrivedDimension(10),
ContrivedDimension2(10)
])
result = arr.max(axis=(1, 2), keepdims=True)
self.assertEqual((10, 1, 1, 7), result.shape)
self.assertIsInstance(result, ArrayWithUnits)
self.assertEqual(4, len(result.dimensions))
print result.dimensions
self.assertIsInstance(result.dimensions[0], ContrivedDimension)
self.assertIsInstance(result.dimensions[1], IdentityDimension)
self.assertIsInstance(result.dimensions[2], IdentityDimension)
self.assertIsInstance(result.dimensions[3], ContrivedDimension2)
def __new__(cls, arr, dimensions):
return ArrayWithUnits.__new__(cls, arr, dimensions)
def test_zeros_dtype(self):
arr = ArrayWithUnits(np.zeros((100, 10), dtype=np.complex128),
[ContrivedDimension(10),
ContrivedDimension2(10)])
arr2 = ArrayWithUnits.zeros(arr)
self.assertEqual(arr.dtype, arr2.dtype)
def test_assigns_size_where_appropriate(self):
arr = ArrayWithUnits(np.zeros((100, 10)),
[ContrivedDimension(10),
ContrivedDimension2(10)])
self.assertEqual(10, arr.dimensions[1].size)
