cvxfit 0.1.1

A package for fitting convex functions to data.

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)

Authors

This package was written and tested by Mainak Chowdhury, Alon Kipnis and Milind Rao.

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.