unitproc/python/sleepRand.py

   1 #!/usr/bin/env python3
   2 # Desc: Pauses a random amount of time. Random distribution is inverse gaussian.
   3 # Version: 0.0.4
   4 # Depends: python 3.7.3
   5 # Usage: ./sleepRand.py [-v] [-p L] SECONDS
   6 # Input: SECONDS: float seconds (mean of inverse gaussian distribution)
   7 #        L:       precision (lambda of inverse gaussian distribution)
   8 # Example: python3 sleepRand.py -vv -p 8.0 60.0
   9
  10 import argparse;
  11 import math, time, random, sys;
  12 import logging;
  13
  14 # Set up argument parser (see https://docs.python.org/3.7/library/argparse.html )
  15 parser = argparse.ArgumentParser(
  16     description='Delay activity for a random number of seconds. Delays sampled from an inverse gaussian distribution.',
  17     epilog="Author: Steven Baltakatei Sandoval. License: GPLv3+");
  18 parser.add_argument('-v','--verbose',
  19                     action='count',
  20                     dest='verbosity',
  21                     default=0,
  22                     help='Verbose output. (repeat for increased verbosity)');
  23 parser.add_argument('mean',
  24                     action='store',
  25                     metavar='SECONDS',
  26                     nargs=1,
  27                     default=1,
  28                     type=float,
  29                     help='Mean seconds of delay. Is the mean of the inverse gaussian distribution.');
  30 parser.add_argument('--precision','-p',
  31                     action='store',
  32                     metavar='P',
  33                     nargs=1,
  34                     default=[4.0],
  35                     type=float,
  36                     help='How concentrated delays are around the mean (default: 4.0). Must be a positive integer or floating point value. Is the lambda factor in the inverse gaussian distribution. High values (e.g. > 10.0) cause random delays to rarely stray far from MEAN. Small values (e.g. < 0.10) result in many small delays plus occasional long delays.');
  37 args = parser.parse_args();
  38
  39 # Define functions
  40 def setup_logging(verbosity):
  41     # Depends: module: argparse
  42     # Ref/Attrib: Haas, Florian; Configure logging with argparse; https://xahteiwi.eu/resources/hints-and-kinks/python-cli-logging-options/
  43     base_loglevel = 30;
  44     verbosity = min(verbosity, 2);
  45     loglevel = base_loglevel - (verbosity * 10);
  46     logging.basicConfig(level=loglevel,
  47                         format='%(message)s');
  48
  49 def randInvGau(mu, lam):
  50     """Returns random variate of inverse gaussian distribution"""
  51     # input: mu:  mean of inverse gaussian distribution
  52     #        lam: shape parameter
  53     # output: float sampled from inv. gaus. with range 0 to infinity, mean mu
  54     # example: sample = float(randInvGau(1.0,4.0));
  55     # Ref/Attrib: Michael, John R. "Generating Random Variates Using Transformations with Multiple Roots" https://doi.org/10.2307/2683801
  56     nu = random.gauss(0,1);
  57     y = nu ** 2;
  58     xTerm1 = mu;
  59     xTerm2 = mu ** 2 * y / (2 * lam);
  60     xTerm3 = (- mu / (2 * lam)) * math.sqrt(4 * mu * lam * y + mu ** 2 * y ** 2);
  61     x = xTerm1 + xTerm2 + xTerm3;
  62     z = random.uniform(0.0,1.0);
  63     if z <= (mu / (mu + x)):
  64         return x;
  65     else:
  66         return (mu ** 2 / x);
  67
  68 # Process input
  69 ## Start up logger
  70 setup_logging(args.verbosity);
  71 logging.debug('DEBUG:Debug logging output enabled.');
  72 logging.debug('DEBUG:args.verbosity:' + str(args.verbosity));
  73 logging.debug('DEBUG:args:' + str(args));
  74 ## Reject negative floats.
  75 try:
  76     ### Get desired mean
  77     desMean = args.mean[0];
  78     logging.debug('DEBUG:Desired mean:' + str(desMean));
  79     ### Get lambda precision factor
  80     lambdaFactor = args.precision[0];
  81     logging.debug('DEBUG:Lambda precision factor:' + str(lambdaFactor));
  82     if desMean < 0:
  83         logging.error('ERROR:Desired mean is negative:' + str(desMean));
  84         raise ValueError('Negative number error.');
  85     if lambdaFactor < 0:
  86         logging.error('ERROR:Lambda precision factor is negative:' + str(lambdaFactor));
  87         raise ValueError('Negative number error.');
  88 except ValueError:
  89     sys.exit(1);
  90
  91 # Calculate delay
  92 delay = randInvGau(desMean, desMean * lambdaFactor);
  93 logging.debug('delay:' + str(delay));
  94
  95 # Sleep
  96 time.sleep(float(delay));
  97
  98 # Author: Steven Baltakatei Sandoal
  99 # License: GPLv3+