import liblinear
import pprint

d1 = [ [(0, 1), (1, 1), (2,2) ] , [(0, .9), (1, 1), (2,2) ] ]

d2 = [ [(0, - 1), (1, 1), (2,2) ] , [(0, - .9), (1, 1), (2,2) ] ]

d3 = [ [(0, 0), (1, - 1), (2,2) ] , [(0, 0), (1, - 1.1), (2,2) ] ]


 
print "version is", liblinear.version

def indent(txt):

    lines = txt.split("\n")
    print "\n".join("   "+l for l in lines)

def run(problem):

    print 
    print 50*"-"
    print "run with problem"
    pprint.pprint(problem)

    clfr = liblinear.LinearSVM.train(problem, liblinear.L2LOSS_SVM_DUAL)


    print
    print "clfr.tostring() gives:"
    indent( clfr.tostring())

    print "\nWeights:"

    for w in clfr.get_weights():
        print "   ", w

    print "\nBias:"

    for x in clfr.get_bias():
        print "   ", x




run([d1,d2])
run([d1,d2, d3])