added exam exercise 08
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exam/ex08/main.py
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49
exam/ex08/main.py
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import numpy as np
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import matplotlib.pyplot as plt
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class BrownIterator(object):
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def __init__(self, N, m):
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self._N = N
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self._max_m = m
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self._i = 0
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self._xs = None
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self._ys = None
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def __iter__(self):
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self._xs = np.zeros(self._N) + 1.5
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self._ys = np.zeros(self._N)
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self._i = 0
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return self
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def __next__(self):
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self._i += 1
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if(self._i > self._max_m):
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raise StopIteration()
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if(self._i == 1):
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return self._xs, self._ys
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theta = np.random.uniform(0, np.pi * 2, self._N)
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self._xs = self._xs + np.cos(theta)
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self._ys = self._ys + np.sin(theta)
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# Reflect the particles
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self._xs[self._xs > 3] += 1.5 * (3 - self._xs[self._xs > 3])
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self._ys[self._ys > 3] += 1.5 * (3 - self._ys[self._ys > 3])
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self._xs[self._xs < -3] += 1.5 * (-3 - self._xs[self._xs < -3])
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self._ys[self._ys < -3] += 1.5 * (-3 - self._ys[self._ys < -3])
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return self._xs, self._ys
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if( __name__ == "__main__"):
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data = np.array([i for i in BrownIterator(1000, 251)])
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print(data)
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p1, = plt.plot(data[5,0], data[5,1], "r.", label="t = 5")
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p2, = plt.plot(data[25,0], data[25,1], "y.", label="t = 25")
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p3, = plt.plot(data[50,0], data[50,1], "b.", label="t = 50")
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p4, = plt.plot(data[250,0], data[250,1], "g.", label="t = 250")
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plt.legend(handles=[p1, p2, p3, p4])
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plt.show()
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