# Inverses and pseudoinverses. Numerical issues, speed, symmetry.

The matrix inverse is a cornerstone of linear algebra, taught, along with its applications, since high school. The inverse of a matrix $latex A$, if it exists, is the matrix $latex A\^{-1}$ such that $latex AA\^{-1} = A\^{-1}A = I_n$. Based on the requirement that the left and …

# Memory benchmarking with vbench

Category: benchmarking
#memit #memory #vbench #python #scikit-learn

The scikit-learn-speed project now has memory usage benchmarking!

This was accomplished by building on what I described in my recent posts, specifically the extensions to Fabian’s [memory_profiler][] that you can find in my fork, but they will be merged upstream soon. The key element is the %magic_memit function whose …

# On why my %memit fails on OSX

Category: benchmarking
#IPython #magic #memit #mprun #benchmarking #python

In my last post I mentioned that I’m not satisfied with the current state of %memit, because some more complicated numerical function calls make it crash. I will start this post with a reminder of a pretty important bug:

[On MacOS X (10.7 but maybe more), after forking …