exec/unitproc/sleepRand.py

   1 #!/usr/bin/env python3
   2 # Desc: Pauses a random amount of time. Random distribution is inverse gaussian.
   3 # Version: 0.0.6
   4 # Depends: python 3.7.3
   5 # Usage: ./sleepRand.py [-v] [-p P] SECONDS
   6 # Input: SECONDS: float seconds (mean of inverse gaussian distribution)
   7 #        P:       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 parser.add_argument('--upper','-u',
  38                     action='store',
  39                     metavar='U',
  40                     nargs=1,
  41                     default=[None],
  42                     type=float,
  43                     help='Upper bound for possible delays (default: no bound). Without bound, extremely high delays are unlikely but possible.');
  44 args = parser.parse_args();
  45
  46 # Define functions
  47 def setup_logging(verbosity):
  48     '''Sets up logging'''
  49     # Depends: module: argparse
  50     # Ref/Attrib: Haas, Florian; Configure logging with argparse; https://xahteiwi.eu/resources/hints-and-kinks/python-cli-logging-options/
  51     base_loglevel = 30;
  52     verbosity = min(verbosity, 2);
  53     loglevel = base_loglevel - (verbosity * 10);
  54     logging.basicConfig(level=loglevel,
  55                         format='%(message)s');
  56
  57 def randInvGau(mu, lam):
  58     """Returns random variate of inverse gaussian distribution"""
  59     # input: mu:  mean of inverse gaussian distribution
  60     #        lam: shape parameter
  61     # output: float sampled from inv. gaus. with range 0 to infinity, mean mu
  62     # example: sample = float(randInvGau(1.0,4.0));
  63     # Ref/Attrib: Michael, John R. "Generating Random Variates Using Transformations with Multiple Roots" https://doi.org/10.2307/2683801
  64     nu = random.gauss(0,1);
  65     y = nu ** 2;
  66     xTerm1 = mu;
  67     xTerm2 = mu ** 2 * y / (2 * lam);
  68     xTerm3 = (- mu / (2 * lam)) * math.sqrt(4 * mu * lam * y + mu ** 2 * y ** 2);
  69     x = xTerm1 + xTerm2 + xTerm3;
  70     z = random.uniform(0.0,1.0);
  71     if z <= (mu / (mu + x)):
  72         return x;
  73     else:
  74         return (mu ** 2 / x);
  75
  76 # Process input
  77 ## Start up logger
  78 setup_logging(args.verbosity);
  79 logging.debug('DEBUG:Debug logging output enabled.');
  80 logging.debug('DEBUG:args.verbosity:' + str(args.verbosity));
  81 logging.debug('DEBUG:args:' + str(args));
  82
  83 ## Receive input arguments
  84 try:
  85     ### Get desired mean
  86     desMean = args.mean[0];
  87     logging.debug('DEBUG:Desired mean:' + str(desMean));
  88
  89     ### Get lambda precision factor
  90     lambdaFactor = args.precision[0];
  91     logging.debug('DEBUG:Lambda precision factor:' + str(lambdaFactor));
  92
  93     ### Get upper bound
  94     if isinstance(args.upper[0], float):
  95         logging.debug('DEBUG:args.upper[0] is float:' + str(args.upper[0]));
  96         upperBound = args.upper[0];
  97     elif args.upper[0] is None:
  98         logging.debug('DEBUG:args.upper[0] is None:' + str(args.upper[0]));
  99         upperBound = None;
 100     else:
 101         raise TypeError('Upper bound not set correctly.');
 102     logging.debug('DEBUG:Upper bound:' + str(upperBound));
 103
 104     ### Reject negative floats.
 105     if desMean < 0:
 106         logging.error('ERROR:Desired mean is negative:' + str(desMean));
 107         raise ValueError('Negative number error.');
 108     if lambdaFactor < 0:
 109         logging.error('ERROR:Lambda precision factor is negative:' + str(lambdaFactor));
 110         raise ValueError('Negative number error.');
 111 except ValueError:
 112     sys.exit(1);
 113
 114 # Calculate delay
 115 rawDelay = randInvGau(desMean, desMean * lambdaFactor);
 116 logging.debug('DEBUG:rawDelay(seconds):' + str(rawDelay));
 117 if isinstance(upperBound,float):
 118     delay = min(upperBound, rawDelay);
 119 elif upperBound is None:
 120     delay = rawDelay;
 121 logging.debug('DEBUG:delay(seconds)   :' + str(delay));
 122
 123 # Sleep
 124 time.sleep(float(delay));
 125
 126 # Author: Steven Baltakatei Sandoal
 127 # License: GPLv3+