Scientific computing, mathematical modeling, and computer simulation
The format method for Python strings (introduced in 2.6) is very flexible and powerful. It’s also easy to use, but the documentation is not very clear. It all makes sense with a few examples. I’ll add more as I have time: Formatting Numbers in Python Strings Formatting a floating-point number The result is the following […]
Python string format examples Read More »
EDIT: added –enable-shared to configure script for building Python, and added /home/yourname/lib to shared library path. This is necessary for building some packages such as pycairo (which you may need to build pygtk and matplotlib). EDIT 2: you should use the –prefix=/home/yourusername instead of –user. The prefix option places packages in the standard location: /home/yourusername/lib/python2.7/site-packages.
How to build ScipPy with Python 2.7.2 on CentOS5 Read More »
Sometimes, the frame around a matplotlib plot can detract from the information you are trying to convey. How do you remove the frame, ticks, or axes from a matplotlib plot? Some books you may find useful when working with matplotlib: The full example is available on github.
Removing an axis or both axes from a matplotlib plot Read More »
The Jmol applet (or Java application) is widely used to visualize the structure of molecules. It is very powerful, but not that well documented. If you don’t have Jmol running, open the page for Glucose Oxidase (1CF3) from the Protein Databank so you can follow the instructions for finding the size of the bounding box.
Finding dimensions of a bounding box in Jmol Read More »
I’ve just released a self-contained Fortran module that solves a system of linear equations using the LU decomposition. Download the Fortran linear solver from github This module is based on code that was implemented and released on the Web by Jean-Pierre Moreau. His implementation was based on one of the Numerical Recipes books. I updated
A self-contained Fortran linear equation solver Read More »
I have been optimizing some Fortran code that involved searching for an integer value in an unordered array (we know the value occurs only once). Since there is no intrinsic procedure to accomplish this, I thought I’d try a couple of approaches to see which was fastest. The simple answer is that, in this case,
Finding a value in an unordered Fortran array Read More »
I’ve recently gained a lot of experience with Sage, an open-source alternative to MATLAB, Mathematica, Maple, MuPAD, and Magma. Here are a couple of links to check out: Public notebook servers–try it online right now! Interactive examples with Sage Mathematical publications citing Sage
Sage: open-source mathematical software Read More »
Linear time-invariant (LTI) systems are widely used in the field of signal processing. Scipy contains powerful tools for simulating LTI systems in the scipy.signal package, but they are not well documented. I will provide a simple example that demonstrates how to use a few of the core classes and functions in scipy.signal for simulating LTI
Linear system simulation with Python Read More »
Microsoft Word is not the best tool for doing technical writing. However, sometimes we are required to use Word because we need to collaborate with others who want to use Word. Right now, I am using Word 2007 on Windows XP to write several mathematical papers. In general, it is a big improvement from previous
Using Microsoft Word for Technical Documents Read More »
Scipy contains a good least-squares fitting routine, leastsq(), which implements a modified Levenberg-Marquardt algorithm. I just learned that it also has a constrained least-squared routine called fmin_slsqp(). I am using simple upper and lower bound constraints, but it’s also possible to specify more complex functional constraints. What I did not realize, at first, is that
Constrained least-squares fitting with Python Read More »