import matplotlib.pyplot as plt
import random
import numpy as np
area_of_house = [10]
prices=[10]
for i in range(1,10):
    value = random.randint(0,100)
    area_of_house.append(value)
    prices.append(value*100)
area_of_house.sort()
prices.sort()
n = len(area_of_house)
theta_0 = 0
theta_1 = 0
alpha = 0.00009

def cal_error(theta_0,theta_1, n,area_of_price,prices):
    new_theta_0 = 0
    new_theta_1 = 0
    for i in range(n):
        new_theta_0 += ( theta_0 + theta_1 *area_of_house[i]) - prices[i]
        new_theta_1 += ((theta_0 + theta_1 * area_of_house[i])- prices[i])* area_of_house[i]
    return (new_theta_0/n, new_theta_1/n)


def gradient_descent():
    theta_0_ = 0
    theta_1_ = 0
    list_theta_0 = []
    list_theta_1 = []
    counter = 0
    arraycounter=[]

    while True:
        counter+=1
        arraycounter.append(counter)


        error_1,error_2 = cal_error(theta_0_,theta_1_, n, area_of_house,prices)
        theta_0_ = theta_0_ - alpha * (error_1)
        theta_1_ = theta_1_ - alpha * (error_2)
        list_theta_0.append(theta_0_)
        list_theta_1.append(theta_1_)

        print(error_1, "  ",error_2)
        if error_1<=0.01 or error_2 <=0.01 or counter == 300:
            list_theta_0 = np.asarray(list_theta_0)
            list_theta_1 = np.asarray(list_theta_1)
            plt.figure(figsize=(10, 6), dpi=80)
            plt.plot(list_theta_0, arraycounter, color="blue", linewidth=2.5, linestyle="-")
            plt.plot(list_theta_1,arraycounter, color="red",  linewidth=2.5, linestyle="-")
            break
    return

gradient_descent()