# Draw 100000 samples from Normal distribution with stds of interest: samples_std1, samples_std3, samples_std10
import matplotlib.pyplot as plt
import numpy as np

samples_std1 = np.random.normal(20, 1, size=100000)
samples_std3 = np.random.normal(20, 3, size=100000)
samples_std10 = np.random.normal(20, 10, size=100000)

# Make histograms
plt.hist(samples_std1, bins=100, normed = True, histtype = 'step')
plt.hist(samples_std3,bins=100, normed = True, histtype = 'step')
plt.hist(samples_std10, bins=100,normed = True, histtype = 'step')

# Make a legend, set limits and show plot
plt.legend(('std = 1', 'std = 3', 'std = 10'))
plt.ylim(-0.01, 0.42)
plt.show()


