def test_compute_dataset_without_processed_variables(self):
dataset = self.get_test_dataset()
computed_dataset = evaluate_dataset(dataset)
self.assertIsNot(computed_dataset, dataset)
self.assertIn('x', computed_dataset)
self.assertIn('y', computed_dataset)
self.assertIn('a', computed_dataset)
self.assertIn('b', computed_dataset)
self.assertIn('c', computed_dataset)
self.assertIn('d', computed_dataset)
self.assertIn('x', computed_dataset.coords)
self.assertIn('y', computed_dataset.coords)
self.assertIn('title', computed_dataset.attrs)
self.assertEqual((2, 4), computed_dataset.a.shape)
self.assertEqual((2, 4), computed_dataset.b.shape)
self.assertEqual((), computed_dataset.c.shape)
self.assertNotIn('expression', computed_dataset.c.attrs)
self.assertEqual((2, 4), computed_dataset.d.shape)
self.assertIn('expression', computed_dataset.d.attrs)
np.testing.assert_array_almost_equal(
computed_dataset.a.values,
np.array([[0.1, 0.2, 0.4, 0.1], [0.5, 0.1, 0.2, 0.3]]))
np.testing.assert_array_almost_equal(
computed_dataset.b.values,
np.array([[nan, 0.3, 0.2, nan], [0.1, nan, 0.5, 0.1]]))
np.testing.assert_array_almost_equal(computed_dataset.c.values,
np.array([1.]))
np.testing.assert_array_almost_equal(
computed_dataset.d.values,
np.array([[0.04, 0.06, 0.08, 0.04], [0.05, 0.02, 0.1, 0.03]]))
def test_compute_dataset_with_processed_variables(self):
dataset = self.get_test_dataset()
computed_dataset = evaluate_dataset(dataset,
processed_variables=[('a', None),
('b', dict(valid_pixel_expression=None)),
('c', dict(expression='a + b')),
('d', dict(valid_pixel_expression='c > 0.4'))])
self.assertIsNot(computed_dataset, dataset)
self.assertIn('x', computed_dataset)
self.assertIn('y', computed_dataset)
self.assertIn('a', computed_dataset)
self.assertIn('b', computed_dataset)
self.assertIn('c', computed_dataset)
self.assertIn('d', computed_dataset)
self.assertIn('x', computed_dataset.coords)
self.assertIn('y', computed_dataset.coords)
self.assertIn('title', computed_dataset.attrs)
self.assertEqual((2, 4), computed_dataset.a.shape)
self.assertEqual((2, 4), computed_dataset.b.shape)
self.assertEqual((2, 4), computed_dataset.c.shape)
self.assertIn('expression', computed_dataset.c.attrs)
self.assertEqual((2, 4), computed_dataset.d.shape)
self.assertIn('expression', computed_dataset.d.attrs)
np.testing.assert_array_almost_equal(computed_dataset.a.values,
np.array([[0.1, 0.2, 0.4, 0.1], [0.5, 0.1, 0.2, 0.3]]))
np.testing.assert_array_almost_equal(computed_dataset.b.values,
np.array([[0.4, 0.3, 0.2, 0.4], [0.1, 0.2, 0.5, 0.1]]))
np.testing.assert_array_almost_equal(computed_dataset.c.values,
np.array([[0.5, 0.5, 0.6, 0.5], [0.6, 0.3, 0.7, 0.4]]))
np.testing.assert_array_almost_equal(computed_dataset.d.values,
np.array([[0.04, 0.06, 0.08, 0.04], [0.05, nan, 0.1, nan]]))
def step2(input_slice):
return evaluate_dataset(input_slice,
processed_variables=processed_variables)