In [9]:

    

import random

sf_height = [random.randint(80, 160) for x in range(200)]
ny_height = [random.randint(130, 200) for x in range(200)]


    

In [34]:

    

data = map(lambda x: (x,1), sf_height)
data += map(lambda x: (x,0), ny_height)

datamap = {}
for (x, y) in data:
    datamap[x] = y


    

In [30]:

    

import numpy as np
theta = np.array([[1],[1]])


    

In [28]:

    

def hypo(x):
    vecx = np.array([[1],[x]])
    return np.dot(np.transpose(theta), vecx)[0][0]


    

In [36]:

    

def get_y(x):
    return datamap[x]


    

In [41]:

    

def errorfn(x):
    return (hypo(x) - get_y(x))


    

In [43]:

    

def calcu():
    tmp = theta[:]


    

In [ ]: