import scipy,pylab,numpy
from numpy import *
from scipy import *
from pylab import *
from urllib import urlopen
from gzip import GzipFile
from scipy.spatial import distance
from scipy.spatial.distance import cdist

data = random_sample((1000,2))
labels = (data[:,0]*0.7+data[:,1]*0.4>0.5)
sum(labels)

d0 = data[labels==False]
d1 = data[labels]
figure(figsize=(6,6)); xlim((0,1)); ylim((0,1))
plot(d0[:,0],d0[:,1],"bo")
plot(d1[:,0],d1[:,1],"ro")
print len(d0),len(d1)

augmented = concatenate([ones((len(data),1)),data],axis=1)
augmented[:3,:]

labels = 2.0*labels-1.0

a = dot(linalg.pinv(augmented),labels)
d,a0,a1 = a
print d,a0,a1

d0 = data[labels<=0]
d1 = data[labels>0]
figure(figsize=(6,6)); xlim((0,1)); ylim((0,1))
plot(d0[:,0],d0[:,1],"bo")
plot(d1[:,0],d1[:,1],"ro")
plot([0,-d/a0],[-d/a1,0],"g")
savefig("tmp.png")
print len(d0),len(d1)

xs = linspace(0.0,1.0,100)[:,newaxis]
ys = linspace(0.0,1.0,100)[newaxis,:]
xs = xs + 0*ys
ys = ys + 0*xs
image = xs*a0+ys*a1+d
imshow(image.T[::-1]); savefig("temp.png")