Generate normal distrubution samples with given mu and sigma

generate_samples.py

#!/usr/bin/env python

import sys
import optparse
import numpy as np
from progress.counter import Counter

def GenerateSamples(mu, sigma, size, delta):
    bar = Counter('Calculating: ')

    while True:
        s = np.random.normal(mu, sigma, size)
        mu_delta = abs(mu - np.mean(s)) / mu
        sigma_delta = abs(sigma - np.std(s)) / sigma

        if mu_delta > delta or sigma_delta > delta:
            bar.next()
            continue

        bar.finish()
        return s

def Main():
    parser = optparse.OptionParser(usage=' %prog --mu <mean> --sigma <std> ')

    parser.add_option('--mu',
                      type='float',
                      action='store',
                      dest='mu',
                      default=1,
                      help='Mean value')
    parser.add_option('--sigma',
                      type='float',
                      action='store',
                      dest='sigma',
                      default=0.1,
                      help='Standard deviation')
    parser.add_option('--size',
                      type='float',
                      action='store',
                      dest='size',
                      default=50,
                      help='Number of samples')
    parser.add_option('--delta',
                      type='float',
                      action='store',
                      dest='delta',
                      default=0.001,
                      help='Delta')

    opts, args = parser.parse_args()

    s = GenerateSamples(opts.mu, opts.sigma, opts.size, opts.delta)
    text = """

%d Samples:\n
%s
Mean: %s
Std: %s
""" % (len(s), s, np.mean(s), np.std(s))

    print text
    Notify("cmn@nau.edu.cn", text)

if '__main__' == __name__:
    sys.exit(Main())