PyDistMesh: A Simple Mesh Generator in Python
PyDistMesh is a simple Python code for generating unstructured triangular and tetrahedral meshes using signed distance functions. It intends to have the same functionality as and similar interface to the MATLABbased DistMesh. Like DistMesh, upon which it is based, PyDistMesh is distributed under the GNU GPL.
2D Examples

Uniform Mesh on Unit Circle:
>>> import distmesh as dm >>> import numpy as np >>> fd = lambda p: np.sqrt((p**2).sum(1))1.0 >>> p, t = dm.distmesh2d(fd, dm.huniform, 0.2, (1,1,1,1))

Rectangle with circular hole, refined at circle boundary:
>>> import distmesh as dm >>> fd = lambda p: dm.ddiff(dm.drectangle(p,1,1,1,1), ... dm.dcircle(p,0,0,0.5)) >>> fh = lambda p: 0.05+0.3*dm.dcircle(p,0,0,0.5) >>> p, t = dm.distmesh2d(fd, fh, 0.05, (1,1,1,1), ... [(1,1),(1,1),(1,1),(1,1)])
3D Examples

3D Unit ball:
>>> import distmesh as dm >>> import numpy as np >>> fd = lambda p: np.sqrt((p**2).sum(1))1.0 >>> p, t = dm.distmeshnd(fd, dm.huniform, 0.2, (1,1,1, 1,1,1))

Cylinder with hole:
>>> import distmesh as dm >>> import numpy as np >>> def fd10(p): ... r, z = np.sqrt(p[:,0]**2 + p[:,1]**2), p[:,2] ... d1, d2, d3 = r1.0, z1.0, z1.0 ... d4, d5 = np.sqrt(d1**2+d2**2), np.sqrt(d1**2+d3**2) ... d = dm.dintersect(dm.dintersect(d1, d2), d3) ... ix = (d1>0)*(d2>0); d[ix] = d4[ix] ... ix = (d1>0)*(d3>0); d[ix] = d5[ix] ... return dm.ddiff(d, dm.dsphere(p, 0,0,0, 0.5)) >>> def fh10(p): ... h1 = 4*np.sqrt((p**2).sum(1))1.0 ... return np.minimum(h1, 2.0) >>> p, t = dm.distmeshnd(fd10, fh10, 0.1, (1,1,1, 1,1,1))
Demos
For a quick demonstration, run:
$ python m distmesh.demo2d
or:
$ python m distmesh.demond
Dependencies
PyDistMesh is compatible with both Python 2 and Python 3. (The author has only tested it in Python 2.7 and Python 3.2). It requires several common Python packages:
 NumPy
 SciPy
 matplotlib (optional)
Building the package requires a C compiler and LAPACK. Cython, if available, can be used to rebuild the extension module bindings.
References
The DistMesh algorithm is described in the following two references. If you use the algorithm in a program or publication, please acknowledge its authors by adding a reference to the first paper below.