RunSnakeRun is a small GUI utility that allows you to view (Python) cProfile or Profile profiler dumps in a sortable GUI view. It allows you to explore the profiler information using a "square map" visualization or sortable tables of data.
Great reference with many open-source useful plotting and visualization tools Over the years many different plotting modules and packages have been developed for Python. For most of that time there was no clear favorite package, but recently matplotlib has become the most widely used. Nevertheless, many of the others are still available and may suit your tastes or needs better. Some of these are interfaces to existing plotting libraries while others are Python-centered new implementations.
Veusz is a GUI scientific plotting and graphing package. It is designed to produce publication-ready Postscript or PDF output. SVG, EMF and bitmap formats export are also supported. The program runs under Unix/Linux, Windows or Mac OS X, and binaries are provided. Data can be read from text, CSV or FITS files, and data can be manipulated or examined from within the application.
News: all of the few remaining calls to scipy have been replaced with calls to numpy. Versions 0.1.8 and above do not require scipy as a dependency. Introduction This library provides Python functions for agglomerative clustering. Its features include * generating hierarchical clusters from distance matrices * computing distance matrices from observation vectors * computing statistics on clusters * cutting linkages to generate flat clusters * and visualizing clusters with dendrograms. The interface is very similar to MATLAB's Statistics Toolbox API to make code easier to port from MATLAB to Python/Numpy. The core implementation of this library is in C for efficiency.
ClusterViz is a software to visualize the clustering process using the family of k-means algorithms. The program is free software under the GNU General Public License (GPL). ClusterViz allows to cluster data while visualizing an up to three dimensional projection. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.