def test_array_interface(self):
# Extended version of Pandas TestPandasInterface.test_array_interface
# Test scalar value
s = TensorArray(3)
result = np.array(s)
self.assertTupleEqual(result.shape, (1,))
expected = np.stack([np.asarray(i) for i in s])
npt.assert_array_equal(result, expected)
# Test scalar list
s = TensorArray([1, 2, 3])
result = np.array(s)
self.assertTupleEqual(result.shape, (3,))
expected = np.stack([np.asarray(i) for i in s])
npt.assert_array_equal(result, expected)
# Test 2d array
s = TensorArray([[1], [2], [3]])
result = np.array(s)
self.assertTupleEqual(result.shape, (3, 1))
expected = np.array([np.asarray(i) for i in s])
npt.assert_array_equal(result, expected)
# Test TensorElement
x = [1, 2, 3]
elements = [TensorElement(np.array(i)) for i in x]
result = np.array([np.asarray(e) for e in elements])
self.assertTupleEqual(result.shape, (3,))
expected = np.array(x)
npt.assert_array_equal(result, expected)
def test_create_from_scalar(self):
s = TensorArray(2112)
self.assertEqual(len(s), 1)
self.assertTupleEqual(s.numpy_shape, (1,))
self.assertEqual(s[0], 2112)
s = TensorArray(np.int64(2112))
self.assertEqual(len(s), 1)
self.assertTupleEqual(s.numpy_shape, (1,))
self.assertEqual(s[0], 2112)
x = np.array([1, 2112, 3])
e = TensorElement(x[1])
s = TensorArray(e)
self.assertTupleEqual(s.numpy_shape, (1,))
self.assertEqual(s[0], 2112)
def test_create_from_scalar_list(self):
x = [1, 2, 3, 4, 5]
s = TensorArray(x)
self.assertTupleEqual(s.numpy_shape, (len(x),))
expected = np.array(x)
npt.assert_array_equal(s.to_numpy(), expected)
# Now with TensorElement values
e = [TensorElement(np.array(i)) for i in x]
s = pd.array(e, dtype=TensorDtype())
npt.assert_array_equal(s.to_numpy(), expected)
# Now with list of 1d tensors
x = [np.array([i]) for i in x]
s = pd.array(x, dtype=TensorDtype())
self.assertTupleEqual(s.to_numpy().shape, (len(x), 1))
npt.assert_array_equal(s.to_numpy(), np.array([[e] for e in expected]))
# Pandas will create list of copies of the tensor element for the given indices
s = pd.Series(np.nan, index=[0, 1, 2], dtype=TensorDtype())
self.assertEqual(len(s), 3)
self.assertTupleEqual(s.to_numpy().shape, (3,))
result = s.isna()
self.assertTrue(np.all(result.to_numpy()))