import numpy as np
import matplotlib.pyplot as plt

class BrownIterator(object):
	def __init__(self, N, m):
		self._N = N
		self._max_m = m
		self._i = 0
		self._xs = None
		self._ys = None
	def __iter__(self):
		self._xs = np.zeros(self._N) + 1.5
		self._ys = np.zeros(self._N)
		self._i = 0
		return self
	def __next__(self):
		self._i += 1
		if(self._i > self._max_m):
			raise StopIteration()
		if(self._i == 1):
			return self._xs, self._ys

		theta = np.random.uniform(0, np.pi * 2, self._N)

		self._xs = self._xs + np.cos(theta)
		self._ys = self._ys + np.sin(theta)

		# Reflect the particles
		self._xs[self._xs > 3] += 1.5 * (3 - self._xs[self._xs > 3])
		self._ys[self._ys > 3] += 1.5 * (3 - self._ys[self._ys > 3])
		self._xs[self._xs < -3] += 1.5 * (-3 - self._xs[self._xs < -3])
		self._ys[self._ys < -3] += 1.5 * (-3 - self._ys[self._ys < -3])

		return self._xs, self._ys

if( __name__ == "__main__"):
	data = np.array([i for i in BrownIterator(1000, 251)])
	print(data)

	p1, = plt.plot(data[5,0], data[5,1], "r.", label="t = 5")
	p2, = plt.plot(data[25,0], data[25,1], "y.", label="t = 25")
	p3, = plt.plot(data[50,0], data[50,1], "b.", label="t = 50")
	p4, = plt.plot(data[250,0], data[250,1], "g.", label="t = 250")

	plt.legend(handles=[p1, p2, p3, p4])
	plt.show()