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): [ 7.35713233 8.9275002 7.62453393 9.62287873 8.63377373 9.81923881 11.82417437 11.4571719 8.69114747 5.91675951] [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)