Talk Scipy: An Introduction to scientific computing



Ability to edit and run Python scripts, familiarity with NumPy arrays

Software requirements:

IPython, NumPy, SciPy, Cython (optional) [1], matplotlib

Make sure that you can execute the following commands before the tutorial:

import numpy
print numpy.__version__

import scipy
print scipy.__version__

import matplotlib.pyplot as plt
plt.plot([1, 2, 3])


We give a brief overview of the SciPy tool stack: numpy, scipy, matplotlib and IPython. We then interactively explore different components of SciPy, such as optimisation, integration, clustering, image processing and elementary linear algebra. To conclude, we briefly discuss some external tools that form part of the eco-system, such as nosetests, Cython and Sphinx.

[1] or for one-click installers
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