Python(x,y): diving into scientific Python
summary
Demonstrates the python(x,y) Windows distribution and a Spider/IPython workflow, with concrete examples: creating and reshaping numpy arrays, using boolean indexing and masked arrays, and showing measured speedups from vectorized code versus pure Python. Builds figures with matplotlib (line plots, subplots, pseudocolor and contour maps, date formatting), reads/writes MAT, Excel and netCDF files, and runs signal and image‑processing examples (FFT smoothing, morphology, object labeling). Ends by wiring simple GUI controls with matplotlib widgets and embedding plots in PyQt4+matplotlib.
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chapters (8)
- 0:00Introduction and setup
- 2:51Workshop outline
- 6:18Coding environment
- 8:23Numpy and array processing
- 10:14Visualization with Matplotlib
- 13:11Input and output
- 15:01Scientific applications
- 16:50Q&A session
