Log message:
Add SHA512 digests for distfiles for math category

Problems found locating distfiles:
	Package dfftpack: missing distfile dfftpack-20001209.tar.gz
	Package eispack: missing distfile eispack-20001130.tar.gz
	Package fftpack: missing distfile fftpack-20001130.tar.gz
	Package linpack: missing distfile linpack-20010510.tar.gz
	Package minpack: missing distfile minpack-20001130.tar.gz
	Package odepack: missing distfile odepack-20001130.tar.gz
	Package py-networkx: missing distfile networkx-1.10.tar.gz
	Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
	Package quadpack: missing distfile quadpack-20001130.tar.gz

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.

Log message:
Add liblinear.
LIBLINEAR is a linear classifier for data with millions of instances
and features. It supports
    L2-regularized classifiers
    L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR)
    L1-regularized classifiers (after version 1.4)
    L2-loss linear SVM and logistic regression (LR)
    L2-regularized support vector regression (after version 1.9)
    L2-loss linear SVR and L1-loss linear SVR.
Main features of LIBLINEAR include
    Same data format as LIBSVM, our general-purpose SVM solver,
        and also similar usage
    Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
    Cross validation for model selection
    Probability estimates (logistic regression only)
    Weights for unbalanced data
    MATLAB/Octave, Java, Python, Ruby interfaces