Package jline.api.spn

Class Spn_rec_enabled

java.lang.Object
jline.api.spn.Spn_rec_enabled

public class Spn_rec_enabled extends Object
Enabling-degree distribution of one mode of a product-form stochastic Petri net, by the masked MDD-rec recursion.

S. Balsamo, A. Marin, I. Stojic, FGCS 111 (2020) 475-490, Sec. 5.3.

The enabling degree of a mode in marking m is e(m) = min_{l : I_l > 0} floor(m_l / I_l), zero when any inhibitor threshold is met. P(e >= k) is therefore the mass of the marking subset in which EVERY input level holds at least k*I_l tokens and no inhibitor fires, which is a per-level restriction and so exactly what Mdd_rec.mdd_rec_masked computes: the paper's second modified recurrence is the same walk under a different mask, not a second algorithm.

The masses returned are UNNORMALISED, as in the paper; divide by G from Mdd_rec.mdd_rec for probabilities. Spn_metrics does that and turns them into the transition measures.

MATLAB twin: spn_rec_enabled.m. Python twin: api/spn/rec_enabled.py.

  • Method Details

    • spn_rec_enabled

      public static Spn_rec_enabled.SpnEnabling spn_rec_enabled(MddStruct mdds, double[][] g, Spn_mdd.SpnMode mde, int nplacelevels)
      Enabling-degree masses of one mode over the reachable set in mdds.
      Parameters:
      mdds - the reachable set built by Spn_mdd
      g - per-level product-form factors, one row per level
      mde - the mode, as returned in SpnInfo.modes
      nplacelevels - how many leading levels are place levels
      Returns:
      the unnormalised enabling-degree masses