In [33]:
import numpy as np
import matplotlib.pyplot as plt
N = 1000
x = np.linspace(0,100,N)
true_map = [0.0] * len(x)
true_map[100] = 1/3
true_map[200] = 1/3
true_map[800] = 1/3
gx = np.linspace(-3, 3, 30)
gaussian = np.exp(-(gx/sigma)**2/2)
uncertain_map = np.convolve(gaussian, true_map, mode='same')
maximum_confusion = [1.0/N] * len(x)
plt.figure()
plt.plot(x,maximum_confusion)
#plt.plot(x, uncertain_map, "r-")
after_first_measurement = np.multiply(maxiumum_confusion, uncertain_map)
plt.plot(x, after_first_measurement, "k.")
print(np.max(uncertain_map), np.max(after_first_measurement), np.max(maximum_confusion))
In [ ]:
In [ ]: