Difference between revisions of "NumericPython"
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and you should get a window similar to: | and you should get a window similar to: | ||
| − | [[Image:Sinc-thru-view.png| | + | [[Image:Sinc-thru-view.png|thumb|none|A grey-scale map of the sinc function]] |
Otherwise, we can use the '''matplotlib''' package: | Otherwise, we can use the '''matplotlib''' package: | ||
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and you should get a window similar to: | and you should get a window similar to: | ||
| − | [[Image:Sinc-matplotlib-contour.png| | + | [[Image:Sinc-matplotlib-contour.png|thumb|300px|none|A grey-scale map of the sinc function]] |
Revision as of 14:44, 21 July 2009
Numeric Python: Some handy array tools
Introduction
Getting Started
from Numeric import *
Arrays
More Interesting
x = arange(-5,10) y = arange(-4,11) z1 = sqrt(add.outer(x**2,y**2)) Z = sin(z1)/z1
If you have the NumTut package available, then you can simply type:
from NumTut import * view(Z)
and you should get a window similar to:
Otherwise, we can use the matplotlib package:
import matplotlib.pyplot as plt from pylab import meshgrid X, Y = meshgrid(x,y) plt.figure() plt.contour(X,Y,Z) plt.show()
and you should get a window similar to:
