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")