I have found a few tools over the years that I find extremely useful for developing software. Python is my language of choice at the moment, but I’m sure these tools will be handy for any language. Subversion is an open-source version-control system. Version control was designed to allow multiple programmers to work on the […]
Tools for Python software development Read More »
Numerical programming frequently requires the use of look-up tables. A look-up table is a collection of pre-computed values. When given an “x” value, the table returns a pre-computed “y” value. Look-up tables can be used to speed up numerical codes, when it is faster to look up a value in the table than it is
A lookup table for fast Python math Read More »
NOTE: these instructions are obsolete. Please see Building NumPy on a 64-bit Red Hat Cluster with Intel MKL. In a previous post I described how I built Numpy with Intel compilers and the Math Kernel Library on a 64-bit cluster. Today I upgraded to Numpy-1.2.1 and I made a few improvements to my install process. Please
Update 2: building 64-bit Numpy with Intel compilers and MKL Read More »
VTK is an open-source software system for “3D computer graphics, image processing, and visualization” developed by by Kitware. VTK is the foundation of Paraview, an industrial-strength CFD visualization tool that I have found to be very useful. I generate “second generation” XML-based files from my Python code and import them into Paraview for visualization. I
Using Python to generate XML files for visualization in Paraview Read More »
I wasted some time today tracking down a bug in one of my programs. It turned out to be “unexpected behavior” rather than a bug. I was aware of this aspect of the language, but I made an assumption and got bit. Read on for a valuable lesson. Python handles integer math differently than floating
Unexpected integer/float math behavior in Python Read More »
“Speed” is a complicated term when used in the context of software. Does it mean raw speed of execution, or reducing the amount of time until a correct result is obtained? Python is not the first language that comes to mind when people think of “fast software.” It is true that pure Python will usually
Profiling Python code Read More »
I had to re-build Numpy because our cluster was upgraded and the Intel compilers and libraries were moved to a different directory. This turned out to be a half-day affair of trial-and-error. I learned a few important things, which I will try to list here: Delete the numpy-1.0.4/build directory after every build attempt. Doing “python
Updated: building 64-bit Numpy with Intel compilers (icc) Read More »
Last night, in the shower, I realized that my collision detection routine could be even faster. Here is a representative snippet of code from my previous post: d2 = (x-self.x[0:i])*(x-self.x[0:i]) + (y-self.y[0:i])*(y-self.y[0:i]) + (z-self.z[0:i])*(z-self.z[0:i]) For some reason, I used the code (x-self.x)*(x-self.x) instead of (x-self.x)**2. Upon further reflection, I realized that (x-self.x)*(x-self.x) computes the difference
Even faster collision detection in Python using Numpy Read More »
We recently learned the hard way that the use of haze can lead to reliability problems for some LCD projectors. We have two rather large LCD projectors (don’t know the specs offhand) permanently mounted to the ceiling, projecting onto the front of screens located on both sides of the stage. A third LCD projector hits
Haze damages LCD projectors Read More »
Python is a very-high-level language. That makes it easy to write code quickly, but the program may not be as fast as a program compiled from a lower-level language. For this reason, many scientific programs are written in Fortran or C++. However, it has always been my experience that the majority of time on a
Speeding up Python math with Numpy: collision detection example Read More »