Veusz is a scientific plotting package, designed to create publication-ready Postscript, PDF, or SVG output. It features an easy to use graphical interface as well as a command line interface and can be scripted or embedded in Python scripts. Graphs are constructed in a modular fashion from separate components. Datasets can be interactively modified or created from within the program.
katso is a library to score binary-categorized data: [low for anti-conformist data], [mean for conformist data], and [high for eclectic data: data that is quite normal (has a lot in common with other data but has a few unusual attributes)]. Data looks like (0, 0, 1, 0, 0, 1, 1) or like (1, 0, 0, 0, 0, 1, 0), all of the same size and corresponding to predefined criteria.
Tracer is a package for ray-tracing in Python. Its main application area is solar energy, and the architecture focuses on extensibility and programmability, so it can be used as a part of other programs. For example, it could be used for optimization algorithms or annual performance simulations.
Milk is a machine learning toolkit in Python. Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, and decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. For unsupervised learning, milk supports k-means clustering and affinity propagation.
pitch perfect is a tool for generating and playing audio tones. The mouse controls pitch and volume, while the keyboard allows persistent notes to be added for chord structure. A separate mode toggles between full note interpolation (off-key) and chromatic notes. It currently supports three common waveforms, in addition to allowing short .wav samples to be played.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano features tight integration with numpy, transparent use of a GPU, efficient symbolic differentiation, speed and stability optimizations, dynamic C code generation, and extensive unit-testing and self-verification. Theano has been powering large-scale computationally intensive scientific investigations since 2007. But it is also approachable enough to be used in the classroom (IFT6266 at the University of Montreal).