def test_dataset_transpose(self):
ds = Dataset({'a': (('x', 'y'), np.random.randn(3, 4)),
'b': (('y', 'x'), np.random.randn(4, 3))})
actual = ds.transpose()
expected = ds.apply(lambda x: x.transpose())
self.assertDatasetIdentical(expected, actual)
actual = ds.T
self.assertDatasetIdentical(expected, actual)
actual = ds.transpose('x', 'y')
expected = ds.apply(lambda x: x.transpose('x', 'y'))
self.assertDatasetIdentical(expected, actual)
ds = create_test_data()
actual = ds.transpose()
for k in ds:
self.assertEqual(actual[k].dims[::-1], ds[k].dims)
new_order = ('dim2', 'dim3', 'dim1', 'time')
actual = ds.transpose(*new_order)
for k in ds:
expected_dims = tuple(d for d in new_order if d in ds[k].dims)
self.assertEqual(actual[k].dims, expected_dims)
with self.assertRaisesRegexp(ValueError, 'arguments to transpose'):
ds.transpose('dim1', 'dim2', 'dim3')
with self.assertRaisesRegexp(ValueError, 'arguments to transpose'):
ds.transpose('dim1', 'dim2', 'dim3', 'time', 'extra_dim')
