import numpy as np
import sys
from numpy import genfromtxt

train_file = sys.argv[1]
dev_file = sys.argv[2]
learning = sys.argv[3]

X_train = np.genfromtxt(train_file, dtype='f', delimiter = ',', skip_header
= 1,filling_values  = 0, usecols =
(3,4,5,6,8,9,10,11,12,13,14,15,17,18,19,20))
y_train = np.genfromtxt(train_file, dtype='f', delimiter = ',', skip_header
= 1,filling_values = 0, usecols = (2))

training_examples = X_train.shape[0]
total_featues = X_train.shape[1]

Wprime = np.asarray([0]*total_featues)
W = Wprime.reshape(-1,1)


k = 0
while k<total_featues :
    i=0
    temp_sum = 0
    #print(X_train[i][k])
    while i< training_examples:
        A = Wprime
        B = X_train[i]
        #print(y_train[i])
        f = abs(np.dot(A,B)-y_train[i])
        #print("this is f"+str(f))
        f = f*X_train[i][k]
        temp_sum = temp_sum + f
        i=i+1
    print("this is temp sum " + str(temp_sum))
    update = temp_sum*0.0001/training_examples
    print("this is update "+str(update))
    Wprime[k] = Wprime[k] - update
    print(Wprime)
    k = k+1