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Python for Neuroscience

Materials for a workshop at the University of Chicago

Time and Location

Thursday, March 10th, 5:00pm-7:00pm, Grossman Institute room P-403

Setup

First please read our Code of Conduct.

Python 3

Install the Anaconda python distribution for Python 3.5 here.

opening the terminal

Windows

http://windows.microsoft.com/en-US/windows-vista/Open-a-Command-Prompt-window

Mac

http://blog.teamtreehouse.com/introduction-to-the-mac-os-x-command-line

testing your python installation

Test your installation by typing into the command line:

$ python --version

This should return something >= 3.5. Next try

$ jupyter notebook --version

This should return something >= 4

Get the Data

Download and unzip the data.

Further Reading

Useful Packages

  • numpy: numeric computing
  • scipy: variety of scientific funtions -- signal processing, statistics, curve fitting, loading data formats like .wav, .mat
  • matplotlib: plotting
  • seaborn: beautiful plotting with matlab
  • bokeh, mpld3: Interactive figures for html5.
  • scikit-learn: machine learning
  • pandas: higher-level data structure built on numpy, great for
  • brian: simulating biological neural networks
  • sympy: symbolic computation, mathematics
  • networkX: visualizing networks, graphs
  • pillow, opencv, scikit-image: image/video processing
  • pymatbridge: call Matlab function
  • pyqtgraph: For making scientific GUIs
  • wxpython: building GUIs
  • theano, tensor flow: automatic differentiation libraries, useful for deep learning.
  • pip, yolk, virtualenv, conda: package management

IDEs and Editors

  • jupyter notebook: Notebook-style workflow
  • spyder: matlab-like editor
  • sublime text: good general purpose text editor
  • ipython: Not a text editor, but a nice interface for running python on the command-line, use in conjunction with an editor.
  • emacs, vim: classic general purpose editors
  • pycharm: full featured IDE, free for students

Further resources