scientific-programming-exer.../ex_33.py

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2019-01-09 13:19:33 +00:00
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)
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)
return self._xs, self._ys
if( __name__ == "__main__"):
data = np.array([i for i in BrownIterator(1000, 321)])
print(data)
p1, = plt.plot(data[20,0], data[20,1], "ro", label="t = 20")
p2, = plt.plot(data[80,0], data[80,1], "bo", label="t = 80")
p3, = plt.plot(data[320,0], data[320,1], "go", label="t = 320")
plt.legend(handles=[p1, p2, p3])
plt.show()