from pandas import read_csv
from math import exp
from numpy.numarray import dot
from math import sqrt, pow

data = read_csv('data-logistic.csv', header=None)

y = data[0]
X = data.iloc[:, 1:]
l = len(X)
w = (0, 0)
k = 0.1
border = 1e-5
C = 10

print zip(X,y)

#def fn(y, x, w, i)

def update_weight(X, Y, w, i):
        return w[i] + k/l*sum([(Y[j]*X[j][i]*(1-1/(1+exp((-Y[j])*dot(X[j], w))))-k*C*w[i]) for j in xrange(len(Y))])

def distance(w1, w2):
    return sqrt(pow(w2[0]-w1[0], 2) + pow(w2[1]-w1[1], 2))

for j in xrange(10000):
    new_w = (update_weight(X, y, w, 0), update_weight(X, y, w, 1))
    dist = distance(w, new_w)
    if dist < border:
        break
    w = new_w

print w