import numpy as np
import matplotlib.pyplot as plt

L = 100
X0 = np.array([L,0])
t = 48*60*60
h = 1
h_list = np.linspace(10,3600,num = 10)
n = t*h

def euler(X0,h,t):
    x0 = X0[0]
    y0 = X0[1]
    T = 24*60*60
    w_list_x = np.zeros(t*h)
    w_list_y = np.zeros(t*h)
    w_list_x[0] = x0
    w_list_y[0] = y0
    for i in range(1,n):
        R = np.sqrt(w_list_x[i-1]**2+w_list_y[i-1]**2)
        w_list_x[i] = w_list_x[i-1] + h*(2*np.pi*R/T)*(-w_list_y[i-1]/R)
        w_list_y[i] = w_list_y[i-1] + h*(2*np.pi*R/T)*(w_list_x[i-1]/R)

    return w_list_x,w_list_y

'''def analyticEndPosition(t_end):
    T = 24*60*60
    x_end = L/(1+(4*(np.pi**2)*(t**2))/T)
    y_end = (2*np.pi*t/T)*x_end
    return x_end, y_end'''

def calcError(h):
    wx,wy= euler(X0,h,t)
    errorSquared = np.abs(wx[0]-wx[t*h-1])**2+np.abs(wy[0]-wy[t*h-1])**2
    return np.sqrt(errorSquared)

wx,wy= euler(X0,h,t)

print(wx)
print(wy)