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()