# -*- coding: utf-8 -*-
"""
Created on Sat Oct  5 09:12:57 2019

@author: CS41FC1
"""

import matplotlib.pyplot as plt
import numpy as np
import math

e = 2.71828182846

#x value
#cost = [20000, 40000, 60000, 80000, 100000, 120000, 140000, 160000]
#cost = [1,2,3,4,5,6,7,8]
cost = [4.2, 5.1, 5.5, 8.2, 9, 9.1]



#y value
result = [0,0,0,1,1,1]
#predict result when 50000 is added

xi =sum(cost)/len(cost)
yi =sum(result)/len(result)


#z = (x-xi)
a=[]
for i in cost:
    a.append(i-xi)


#w = (y-yi)
b=[]
for i in result:
    bsub=float(i-yi)
    b.append(bsub)

c =[]
for i in a:
   csub=float(i*i)
   c.append(csub)


product = []
for i in range(len(cost)):
    mult=b[i]*a[i]
    product.append(mult)


cSum=(sum(c))
productSum =(sum(product))

m = productSum/cSum
c = yi-(m*xi)


val = []

for i in cost:
    val.append(i)

data = float(input("Enter a number: "))
val.append(data)
val.sort()


linearRegY=[]
for i in val:
    ysub= m*i+c
    linearRegY.append(ysub)


print("Output: \t\t\t Linear Regression ")

for i in range (len(val)):
    print(str(val[i])+"\t\t\t\t"+str(linearRegY[i]))



p = []
for i in linearRegY:
    x = 1 / (1+(math.exp(-i) ))
    p.append(x)

p2 = []
for i in p:
    p2.append(i/ (1-i))

newY =[]
for i in p2:
    newY.append( np.log(i) )

xV = [1,2,3,4,5,6,7]


plotY = []
for i in newY:
    if i > .5:
       plotY.append("passed")
    else:
        plotY.append("failed")


plt.plot(xV,newY, 'ro-')