Package jline.lang.constant

Enum ProcessType

java.lang.Object
java.lang.Enum<ProcessType>
jline.lang.constant.ProcessType
All Implemented Interfaces:
Serializable, Comparable<ProcessType>, java.lang.constant.Constable
public enum ProcessType extends Enum<ProcessType> implements Serializable
Constants for specifying a point process type

  • Enum Constant Details

  • Method Details

    • values

      public static ProcessType[] values()
      Returns an array containing the constants of this enum type, in the order they are declared.
      Returns:
      an array containing the constants of this enum type, in the order they are declared

    • valueOf

      public static ProcessType valueOf(String name)
      Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)
      Parameters:
      name - the name of the enum constant to be returned.
      Returns:
      the enum constant with the specified name
      Throws:
      IllegalArgumentException - if this enum type has no constant with the specified name
      NullPointerException - if the argument is null

    • fromDistribution

      public static ProcessType fromDistribution(Distribution d)

    • isMarkovian

      public static boolean isMarkovian(ProcessType t)
      True when sn.proc carries an exact matrix representation of a process of this type: a genuine (D0,D1) pair, or its matrix-exponential analogue for ME/RAP.

      The distinction is about sn.proc, NOT about what

      invalid reference 
      jline.lang.processes.Distribution#getProcess()
      returns. getProcess hands back raw distribution PARAMETERS for several non-Markovian families -- Gamma, Weibull, Lognormal, Pareto and Uniform return two scalars (Pareto {alpha,k}, Uniform {min,max}) -- and the network refresh replaces those with map_erlang(mean, n) before storing them in sn.proc, where n = ceil(1/SCV) capped at 100 (n = 20 when SCV < CoarseTol). That fit matches the mean, and matches the SCV only when SCV <= 1: Pareto with SCV 64 gives n = 1, a single exponential of SCV 1. So for these types sn.proc is an approximation, not the law that was requested, and nothing on the cell says so -- the only signal is sn.procid.

      Solvers that read sn.proc as if it were the exact law must gate on this predicate. It is the procid-level counterpart of Distribution.isMarkovian(), i.e. of the Markovian class hierarchy, so the two must stay in step.

      Parameters:
      t - process type
      Returns:
      true if sn.proc holds the exact law for this type

    • fromText

      public static ProcessType fromText(String name)

    • toText

      public static String toText(ProcessType type)