from pySVM import *
import sys

v1 = SparseVector( (-1,-1))
v2 = SparseVector( (0,1))
v3 = SparseVector( (1,0))

cp = ClassificationProblem()
cp.append(ClassificationExample(v1, True))
cp.append(ClassificationExample(v2, False))
cp.append(ClassificationExample(v3, False))

kk = LinearKernel()
klass = ClassifierCSVM(cp, kk)

info = klass.train(1.0)
if abs(.33333+ klass.getThreshold()) > .0001:
    sys.exit(1)

for ex in cp:
    if (klass(ex.vector) > 0.0)  != ex.label:
        sys.exit(1)

from math import sin,cos,pi
from random import uniform

del cp

# circle as example
cp = ClassificationProblem()
for i in range(100):
    phi=uniform(0,2*pi)
    r  =uniform(0,2)
    if abs(r-1.0)<.1: continue
    x = r * cos(phi)
    y = r * sin(phi)
    label = r <=1.0
    cp.append(ClassificationExample(SparseVector([x,y]), label))

klass = ClassifierCSVM(cp, PolynomialKernel(1.0,2))
klass.train()
for ex in cp:
    if (klass(ex.vector) > 0.0)  != ex.label:
        sys.exit(1)


cp.append(ClassificationExample(SparseVector([0,0]),True))
klass =ClassifierCSVM(cp, RadialKernel())
klass.train()
for ex in cp:
    if (klass(ex.vector) > 0.0)  != ex.label:
        sys.exit(1)