spistats package

Subpackages

• spistats.collision package
  • Module contents
    • Collision
      • Collision.__init__()
      • Collision.cdf()
      • Collision.cdfinv()
      • Collision.mass()
      • Collision.mean()
• spistats.desynchronization package
  • Submodules
  • spistats.desynchronization.dsync_count module
    • NumberOfDsync
      • NumberOfDsync.__init__()
      • NumberOfDsync.cdf()
      • NumberOfDsync.cdf_position()
      • NumberOfDsync.mass()
  • spistats.desynchronization.law module
    • Law
      • Law.__init__()
      • Law.cdf()
      • Law.cdf_inv()
      • Law.cdf_multin()
      • Law.cdf_position()
      • Law.eigenvalues()
      • Law.mass()
      • Law.mean()
  • spistats.desynchronization.law_multi module
    • Law_multip
      • Law_multip.__init__()
      • Law_multip.cdf()
      • Law_multip.cdf_position()
  • Module contents
• spistats.plot package
  • Submodules
  • spistats.plot.cdf module
    • cdf()
  • Module contents

Module contents

This module generates the graphs of the paper https://inria.hal.science/hal-04525080. Based on Markov chains we compute the average number of packet sent before desynchronization. Executing this module with python -m generates the plots in a directory named “plot” in the current working directory.

spistats.markov.Ef(p, m)

Expectation of the number of packet before desynchronization based on Markov chains theory. :param p: Packet loss rate. :type p: float in [0,1] :param m: Size if the identifier list. :type m: int :return: Expectation of the number of packet before desynchronization. :rtype: float