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

colorList = json.load(open('color/config.json','r'))["color"]


xList = np.array([37496,19077,37829,53740,59158])
yList = np.array([103225389,62723855,78383883,119520965,134631332])

plt.scatter(xList,yList,color=colorList[0])

from scipy.optimize import curve_fit
def quadratic(x,a,b,c):
    return a*x*x+b*x+c
vala,valb,valc = curve_fit(quadratic,xList,yList)[0]
residuals = yList - quadratic(xList,vala,valb,valc)
ss_res = np.sum(residuals**2)
ss_tot = np.sum((yList-np.mean(yList))**2)
r_squared = 1 - (ss_res / ss_tot)
print("R-squared:", r_squared)

plt.plot(np.arange(0,80000,1000),quadratic(np.arange(0,80000,1000),vala,valb,valc),color=colorList[1])
plt.xlabel('Ferry Passenger Count (Number of Passengers)')
plt.ylabel('Hotel & Motel Gross Business Sales (USD)')

target=np.array([32071,33439,34677,35603,35906])
result=quadratic(target,vala,valb,valc)+np.random.normal(0,2000000,5)
plt.scatter(target,result,color=colorList[2],marker='*',s=100)
for i in range(len(target)):
    print(result[i])

plt.legend()
plt.show()