Laplace Distribution Histogram   [Back] The following simulates a Laplace Distribution: Options Normal- μ: Exponential decay.- λ: Samples: Bins: Determine Try an example μ=0.25, λ=0.3, Samples=100 Calc μ=0.25, λ=0.3, Samples=1,000 Calc μ=5, λ=3, Samples=1,000 Calc μ=10, λ=3, Samples=1,000 Calc Laplace (first 10): [ 5.71851824 8.73827378 8.34508066 9.6166861 8.55707101 8.93650226 8.80374797 8.02282014 8.8964981 8.20688654] [View]

Source code

The following outlines the Python code used:

import matplotlib.pyplot as plt
import numpy as np
import sys
import random

file ='1111'
mu=9.0
sig=2.0
samples=10000
bins=100


fontsize=8


fig = plt.figure()
ax = fig.add_subplot(111)

loc, scale = 0., 1.

lapSamples = [np.random.laplace(mu, sig, samples)]

ax.hist(lapSamples, bins=bins,  color='green',normed=True)
ax.set_title(r"Laplace distribution Histogram RNG",fontsize=fontsize)
ax.set_xlabel("x",fontsize=fontsize)
ax.set_ylabel("Frequency of occurrence",fontsize=fontsize)
   
#print "Laplace: ",lapSamples[0:10]  #Take a look at the first 10

file = +file+".svg"
plt.savefig(file)