p = sys.argv.index('-type')
ptemp = sys.argv[p + 1]
type = ptemp
if '-Ntoss' in sys.argv:
p = sys.argv.index('-Ntoss')
Nt = int(sys.argv[p + 1])
if Nt > 0:
Ntoss = Nt
if '-Nexp' in sys.argv:
p = sys.argv.index('-Nexp')
Ne = int(sys.argv[p + 1])
if Ne > 0:
Nexp = Ne
if '-output' in sys.argv:
p = sys.argv.index('-output')
OutputFileName = sys.argv[p + 1]
doOutputFile = True
if doOutputFile:
outfile = open(OutputFileName, 'w')
for e in range(0, Nexp):
for t in range(0, Ntoss):
if type == "nb":
outfile.write(str(random_number.Category6f()) + " ")
if type == "bi":
outfile.write(str(random_number.Category6()) + " ")
outfile.write(" \n")
outfile.close()
#! /usr/bin/env python
from Random import Random
import numpy as np
import matplotlib.pyplot as plt
random_number = Random(77777777)
myx = []
for x in range(1, 10000):
faces = random_number.Category6()
myx.append(faces)
# create histogram of our data
plt.figure()
plt.hist(myx,
6,
density=True,
facecolor='green',
histtype="barstacked",
alpha=0.75)
# plot formating options
plt.xlabel('Dice faces')
plt.ylabel('Probability', fontweight="bold", fontsize="17")
plt.title('Categorical Distribution', fontweight="bold", fontsize="17")
plt.grid(True, color='r')
# save and show figure
plt.savefig("Dice.png")
#plt.show()
