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        "author": "Mainak Chowdhury, Alon Kipnis, Milind Rao",
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            "Development Status :: 3 - Alpha",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python :: 2.7",
            "Topic :: Utilities"
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        "description": "===========\nCvxFit\n===========\n\nCvxFit is a package which provides classes for fitting convex functions to\ngiven data. Typical usage looks like this::\n\n    #!/usr/bin/env python\n\n    from cvxfit import CvxFit\n    import scipy as sp\n\n    #Generate data\n    N = 1000\n    n = 3\n    \n    def f_actual(x):\n        return sp.sum(x*x)\n\n    X = sp.randn(N, n)\n    Y = sp.array([f_actual(pt) for pt in X]) \n\n    #Initialize object with 10 affine functions\n    #with regularization 0.001, and maximum\n    #number of iterations 20\n    fit_object = CvxFit(X=X, Y=Y, type='pwl', extra_param=[10, 0.001, 20])\n    \n    #Perform fit \n    fit_object.fit()\n\n    #See training error; repeat fit if high\n    print 'Training error: ' + str(fit_object.mean_training_error)\n\n    #Compare quality of fit at a random point\n    pt = sp.randn(1, n)\n    print 'Actual value: ' + str(f_actual(pt))\n    print 'Approximate value: ' + str(fit_object.evaluate(pt)[0])\n\n\n\nAuthors\n=========\n\nThis package was written and tested by Mainak Chowdhury, Alon Kipnis and Milind\nRao.\n\nAcknowledgements \n================\n\nThis package came out of a course project for `EE364b\n<http://www.stanford.edu/class/ee364b/>`_ at Stanford University, Spring\n2013-14, taught by Prof. Stephen Boyd. We would like to thank all members of\nthe awesome teaching staff for their useful feedback and constructive\nsuggestions.",
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