PyMCubes is an implementation of the marching cubes algorithm to extract
isosurfaces from volumetric data. The volumetric data can be given as a
three-dimensional NumPy array or as a Python function f(x, y, z). The first
option is much faster, but it requires more memory and becomes unfeasible for
very large volumes.
PyMCubes also provides a function to export the results of the marching cubes as
COLLADA (.dae) files. This requires the
PyCollada library.
Just as any standard Python package, clone or download the project and run:
$ cd path/to/PyMCubes $ python setup.py build $ python setup.py install
If you do not have write permission on the directory of Python packages,
install with the --user option:
$ python setup.py install --user
The following example creates a data volume with spherical isosurfaces and
extracts one of them (i.e., a sphere) with PyMCubes. The result is exported as
sphere.dae:
>>> import numpy as np >>> import mcubes # Create a data volume (30 x 30 x 30) >>> X, Y, Z = np.mgrid[:30, :30, :30] >>> u = (X-15)**2 + (Y-15)**2 + (Z-15)**2 - 8**2 # Extract the 0-isosurface >>> vertices, triangles = mcubes.marching_cubes(u, 0) # Export the result to sphere.dae >>> mcubes.export_mesh(vertices, triangles, "sphere.dae", "MySphere")
The second example is very similar to the first one, but it uses a function to represent the volume instead of a NumPy array:
>>> import numpy as np >>> import mcubes # Create the volume >>> f = lambda x, y, z: x**2 + y**2 + z**2 # Extract the 16-isosurface >>> vertices, triangles = mcubes.marching_cubes_func((-10,-10,-10), (10,10,10), ... 100, 100, 100, f, 16) # Export the result to sphere2.dae >>> mcubes.export_mesh(vertices, triangles, "sphere2.dae", "MySphere")