CvxFit is a package which provides classes for fitting convex functions to given data. Typical usage looks like this:
#!/usr/bin/env python
from cvxfit import CvxFit
import scipy as sp
#Generate data
N = 100
n = 4
def f_actual(x):
return sp.sum(x*x)
X = sp.randn(N, n)
Y = sp.array([f_actual(pt) for pt in X])
#Initialize object with 5 affine functions
fit_object = CvxFit(X=X, Y=Y, type='pwl', k=5)
#Perform fit
fit_object.fit()
#Compare fits at (1,1,1,1)
pt = sp.ones((1, n))
print 'Actual value: ' + f_actual(pt)
print 'Approximate value: ' + fit_object.evaluate(pt)
Acknowledgements
This package came out of a course project for EE364b at Stanford University, Spring 2013-14, taught by Prof. Stephen Boyd. We would like to thank all members of the awesome teaching staff for their useful feedback and constructive suggestions.
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Release files for cvxfit 0.1.1
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