Data Generator
We can create a simple python script to generate a stream of Gaussian noise at the
frequency of one message per second as a python script which should be saved at
~/rand_gen.py
:
#!/usr/bin/python import random import sys import time def main(): mu = float(sys.argv[1]) sigma = float(sys.argv[2]) freq_s = int(sys.argv[3]) while True: print str(random.gauss(mu, sigma)) sys.stdout.flush() time.sleep(freq_s) if __name__ == '__main__': main()
This script will take the following as arguments:
The mean of the data generated
The standard deviation of the data generated
The frequency (in seconds) of the data generated
If, however, you'd like to test a longer tailed distribution, like the student
t-distribution and have numpy installed, you can use the following as
~/rand_gen.py
:
#!/usr/bin/python import random import sys import time import numpy as np def main(): df = float(sys.argv[1]) freq_s = int(sys.argv[2]) while True: print str(np.random.standard_t(df)) sys.stdout.flush() time.sleep(freq_s) if __name__ == '__main__': main()
This script will take the following as arguments:
The degrees of freedom for the distribution
The frequency (in seconds of the data generated