def test_slicing(self):
tensor = pyskip.Tensor((3, 3), 0)
tensor[1, 0:2] = 1
tensor[0:2, 0] = 2
tensor[2:3, 2:3] = 3
expected = np.array([[2, 2, 0], [0, 1, 0], [0, 0, 3]], dtype=int)
self.assertTrue(np.all(tensor.to_numpy() == np.array(expected)))
def test_operations(self):
tensor = pyskip.Tensor(3, 1)
tensor *= 3
tensor[0] = 2 * tensor[1]
tensor[0] += tensor[2] * 3
tensor[1] += tensor[0] * tensor[2]
self.assertEqual(tensor[0], 15)
self.assertEqual(tensor[1], 48)
self.assertEqual(tensor[2], 3)
tensor = pyskip.Tensor(shape=(4, 4), val=0)
tensor[0::2, 0::2] = 1
tensor[1::2, 0::2] = 2
tensor[0::2, 1::2] = 3
tensor[1::2, 1::2] = 4
expected = np.array([[1, 2, 1, 2], [3, 4, 3, 4], [1, 2, 1, 2], [3, 4, 3, 4]], dtype=int)
self.assertTrue(np.all(tensor.to_numpy() == np.array(expected)))
expected = np.array([2, 2, 2, 2], dtype=int)
self.assertTrue(np.all(tensor[1:4:2, 0:4:2].to_numpy().flatten() == np.array(expected)))
def make_disc(cls):
D = 4096
R = D // 4
disc = pyskip.Tensor((D, D), 0)
for y in range(D):
discriminant = R**2 - (y - D // 2 + 0.5)**2
if discriminant < 0:
continue
x_0 = int(D // 2 - 0.5 - discriminant**0.5)
x_1 = int(D // 2 - 0.5 + discriminant**0.5)
disc[x_0:x_1, y] = 1
return disc
def load_default_model(self):
# Initialize the voxel geometry.
t = pyskip.Tensor(shape=(3, 3, 3), val=0)
t[0, 0, 0] = 1
t[1, 0, 0] = 2
t[1, 1, 0] = 1
t[1, 2, 0] = 2
# Define the color of each voxel type.
config = voxels.VoxelConfig()
config[0] = voxels.EmptyVoxel()
config[1] = voxels.ColorVoxel(128, 0, 0)
config[2] = voxels.ColorVoxel(0, 0, 128)
# Map the tensor onto a mesh.
mesh = voxels.to_mesh(t, config)
# Load the mesh into a panda geometry node.
self.model = GeomNode('mesh_node')
self.model.addGeom(create_geometry_from_mesh(mesh))
render.attachNewNode(self.model)
def megatensor(self):
dim_1, dim_2, dim_3 = self._xyz_to_pyskip_col(self.dense_dimensions(),
self.column_order)
megatensor = pyskip.Tensor(shape=(dim_1, dim_2, dim_3), dtype=int)
for chunk in self.chunk_list:
start_x = chunk.coord[0] - self.bbox[0][0]
start_y = chunk.coord[1] - self.bbox[1][0]
start_z = chunk.coord[2] - self.bbox[2][0]
xyz_tensor_shape = self._pyskip_col_to_xyz(chunk.tensor.shape,
self.column_order)
end_x = start_x + xyz_tensor_shape[0]
end_y = start_y + xyz_tensor_shape[1]
end_z = start_z + xyz_tensor_shape[2]
rng = (slice(start_x, end_x,
1), slice(start_y, end_y,
1), slice(start_z, end_z, 1))
try:
megatensor[self._xyz_to_pyskip_col(
rng, self.column_order)] = chunk.tensor
except ValueError:
print(rng)
raise
return megatensor
def test_tensor_3d(self):
tensor = pyskip.Tensor((100, 100, 100), 0)
self.assertIsNotNone(tensor)