def test_lookup(self):
model = SplineModel(3, 3)
v = Volume().refine(1, 1, 1)
model.add(v)
model.add(v + (1, 0, 0))
model.add(v + (0, 0, 1))
q = Volume().refine(1, 1, 1)
self.assertIs(model[q].node, model[v].node)
q = Volume().refine(1, 1, 1).reverse('u').swap('u', 'v')
self.assertIs(model[q].node, model[v].node)
self.assertIs(model[v.section(w=-1)].node,
model[(v + (0, 0, 1)).section(w=0)].node)
def test_faces(self):
model = SplineModel(3, 3)
v = Volume().refine(1, 1, 1)
vr = v + (1, 0, 0)
vu = v + (0, 0, 1)
model.add([v, vr, vu])
model[v.section(u=0)].name = 'uneg'
model[vr.section(u=-1)].name = 'upos'
model[vu.section(u=0)].name = 'uneg'
model[vu.section(u=-1)].name = 'upos'
for vv in [v, vr, vu]:
model[vv.section(v=0)].name = 'vneg'
model[vv.section(v=-1)].name = 'vpos'
model[v.section(w=0)].name = 'wneg'
model[vr.section(w=0)].name = 'wneg'
model[vr.section(w=-1)].name = 'wpos'
model[vu.section(w=-1)].name = 'wpos'
model.generate_cp_numbers()
model.generate_cell_numbers()
faces = model.faces()
self.assertEqual(len(faces), 100)
# The owner should always be the lower numbered cell
self.assertTrue(((faces['owner'] < faces['neighbor']) |
(faces['neighbor'] == -1)).all())
# Where the boundary is named, the neighbor is always -1
self.assertTrue((faces[faces['name'] != None]['neighbor'] == -1).all())
# On internal faces, the neighbor is always > 0
self.assertTrue((faces[faces['name'] == None]['neighbor'] > 0).all())
# Boundaries occur the expected number of times
self.assertEqual(np.sum(faces['name'] == None), 44)
self.assertEqual(np.sum(faces['name'] == 'uneg'), 8)
self.assertEqual(np.sum(faces['name'] == 'upos'), 8)
self.assertEqual(np.sum(faces['name'] == 'vneg'), 12)
self.assertEqual(np.sum(faces['name'] == 'vpos'), 12)
self.assertEqual(np.sum(faces['name'] == 'wneg'), 8)
self.assertEqual(np.sum(faces['name'] == 'wpos'), 8)
# Every cell is mentioned by exactly six faces
nmentions = [0] * 24
for face in faces:
nmentions[face['owner']] += 1
if face['neighbor'] > 0:
nmentions[face['neighbor']] += 1
self.assertEqual(nmentions, [6] * 24)
# Face normals always point toward the neighbor
# In this case, that means in a positive axial direction,
# except possibly for boundary faces
cps = model.cps()
for face in faces:
for I in [face['nodes'][:-1], face['nodes'][1:]]:
vertices = cps[I]
z = np.cross(vertices[1] - vertices[0],
vertices[2] - vertices[1])
# Should be zero, zero and +/- 0.25
self.assertAlmostEqual(sum(np.abs(z)), 0.25)
# j = index of the 0.25
j = np.argmax(np.abs(z))
others = {0: [1, 2], 1: [0, 2], 2: [0, 1]}[j]
np.testing.assert_almost_equal(z[others], 0.0)
# Check that the 0.25 has the right sign
if face['name'] is None or face['name'][1:] == 'pos':
np.testing.assert_almost_equal(z[j], 0.25)
else:
np.testing.assert_almost_equal(z[j], -0.25)
# And that it occurs in the expected index (for boundary faces)
if face['name'] is not None:
self.assertEqual(j, 'uvw'.index(face['name'][0]))
