pycaster 0.1.1

Background

pycaster is a simple single-module package (module also called pycaster) which contains a rayCaster class. This class allows for ray-casting operations to be performed on any mesh represented by a ‘vtkPolyData’ object.

The rayCaster class acts as a wrapper of the vtkOBBTree class and uses perform ray-casting. It can calculate the coordinates of the entry/exit points between the ray and the surface. It can in addition calculate the distance a ray travels within the closed section of the surface, i.e., within the solid.

The class features a static method ‘fromSTL’ which allows for it to be initialized directly from an STL file which it loads and extracts the polydata from initializing the ray-caster.

Documentation

No extensive documentation of pycaster was written due to its simplicity.

Usage Example

In a nutshell using pycaster it would go as such:

from pycaster import pycaster

# Create a new rayCaster object through the 'fromSTL' static-method thus loading
# the STL file 'sphereHollow.stl' and creating a new rayCaster under 'caster'
caster = pycaster.rayCaster.fromSTL("sphereHollow.stl", scale=1.0)

# Set the source and target coordinate of the ray
pSource = [-50.0, 0.0, 0.0]
pTarget = [50.0, 0.0, 0.0]

# Use the 'castRay' method of the 'rayCaster' class to intersect a ray/line with
# the surface and return a list of coordinates, i.e., the intersection points
pointsIntersection = caster.castRay(pSource, pTarget)

# Use the calcDistanceInSolid to calculate the distance the ray 'travels' within
# the surface
caster.calcDistanceInSolid(pSource, pTarget)

Requirements

vtk >= 5.10.1 nose >= 1.3.3

Installation

This package is already hosted on PyPI here and can be easily installed through pip as such:

pip install pycaster

or straight from the source-code using setuptools as such:

python setup.py install

However, given the vtk requirement of pycaster which doesn’t always build easy with pip I strongly suggest the following:

• Use an Anaconda python distro. I’ve written a blog post about the advantages it offers here.

• Install the dependencies with conda (see the aforementioned post)

• Install pycaster with pip while skipping the dependencies as such:

pip install pycaster --no-deps

Testing & CI

pycaster comes with tests written with unittest and batch-executed with nose. The distribution also comes with several .stl files used for testing the different aspects of the package. After installation you can easily run those tests from within a python session with the following code:

from pycaster.test import test_all
test_all.runTests()

Every commit of pycaster is being built and tested on the Wercker CI system. The application is public and can be accessed through either clicking on the wercker badge at the top of this page or through this link.