def test_nop__levels_match(self):
vcoord = _make_vcoord(self.z)
self.assertEqual(self.cube.coord(axis='z', dim_coords=True), vcoord)
levels = vcoord.points
result = extract_levels(self.cube, levels, 'linear')
self.assertEqual(result, self.cube)
self.assertEqual(id(result), id(self.cube))
def test_non_monotonic(self):
shape = (2, 2, 1)
data = np.empty(shape)
levels = np.array([10, 10])
result = create_cube(self.cube, data, levels)
expected = _make_cube(data, aux_coord=False, dim_coord=False)
vcoord = _make_vcoord(levels)
expected.add_aux_coord(vcoord, 0)
self.assertEqual(result, expected)
def test_collapse(self):
shape = (1, 2, 1)
data = np.empty(shape)
levels = np.array([123])
result = create_cube(self.cube, data, levels)
expected = _make_cube(data, aux_coord=False, dim_coord=False)[0]
vcoord = _make_vcoord(levels)
expected.add_aux_coord(vcoord)
self.assertEqual(result, expected)
def test(self):
shape = (2, 2, 1)
data = np.empty(shape)
levels = np.array([10, 20])
result = create_cube(self.cube, data,
self.cube.coord(axis='z', dim_coords=True),
levels)
expected = _make_cube(data, aux_coord=False, dim_coord=False)
vcoord = _make_vcoord(levels)
expected.add_dim_coord(vcoord, 0)
self.assertEqual(result, expected)