Package jline.lang.processes

Class Replayer

java.lang.Object
jline.lang.processes.Distribution
jline.lang.processes.Replayer
All Implemented Interfaces:
Serializable, Copyable
Direct Known Subclasses:
Trace
public class Replayer extends Distribution
A distribution that replays empirical data values from trace files.

The Replayer distribution reads real-world trace data from files and reproduces the exact sequence of observations. This is essential for trace-driven simulation, workload characterization, and model validation against real data patterns.

Key capabilities:

  • Reading trace data from text files (one value per line)
  • Sequential replay of empirical observations
  • Empirical CDF computation from trace data
  • Statistical moment calculation (mean, variance, skewness)
  • Support for both file paths and direct data arrays

Common applications include reproducing real arrival processes, service time patterns, and validating analytical models against measurements from production systems.

Since:
1.0
See Also:

  • Constructor Details

    • Replayer

      public Replayer(Object data)

  • Method Details

    • evalCDF

      public double evalCDF(double t)
      Description copied from class: Distribution
      Evaluates the cumulative distribution function (CDF) at the given point.
      Specified by:
      evalCDF in class Distribution
      Parameters:
      t - the point at which to evaluate the CDF
      Returns:
      the CDF value at point t

    • evalLST

      public double evalLST(double s)
      Description copied from class: Distribution
      Evaluate the Laplace-Stieltjes Transform at s
      Specified by:
      evalLST in class Distribution
      Parameters:
      s - the Laplace domain variable
      Returns:
      the LST value at s

    • fitAPH

      public APH fitAPH()

    • getFileName

      public String getFileName()

    • getMean

      public double getMean()
      Description copied from class: Distribution
      Gets the mean (expected value) of this distribution.
      Specified by:
      getMean in class Distribution
      Returns:
      the mean value

    • getRate

      public double getRate()
      Description copied from class: Distribution
      Gets the rate of this distribution (inverse of mean).
      Overrides:
      getRate in class Distribution
      Returns:
      the rate value (1/mean)

    • getSCV

      public double getSCV()
      Description copied from class: Distribution
      Gets the squared coefficient of variation (SCV) of this distribution. SCV = Var(X) / E[X]^2.
      Specified by:
      getSCV in class Distribution
      Returns:
      the squared coefficient of variation

    • getSkewness

      public double getSkewness()
      Description copied from class: Distribution
      Gets the skewness of this distribution. Skewness measures the asymmetry of the probability distribution.
      Specified by:
      getSkewness in class Distribution
      Returns:
      the skewness value

    • getVar

      public double getVar()
      Description copied from class: Distribution
      Gets the variance of this distribution. Computed as SCV * mean^2.
      Overrides:
      getVar in class Distribution
      Returns:
      the variance

    • getData

      public double[] getData()
      Returns the raw data array backing this Replayer distribution.
      Returns:
      the trace data as a double array

    • isNHPP

      public Map<String,Double> isNHPP()
      Test whether the trace is a sample path of a NON-HOMOGENEOUS POISSON process, by the conditional-uniform KS test with the Lewis refinement (InferNhppKs.infer_nhpp_ks(double[], double)).

      WHY THE QUESTION IS WORTH ASKING. A Replayer is used wherever a measured stream is fed to a solver, and every analytical method that consumes it as an arrival process assumes SOMETHING about its dependence structure. This test says whether the Poisson assumption -- independent increments, whatever the rate does with time -- survives contact with the data, which is the assumption a time-varying analysis (SolverFluid's 'mtginf', 'mol', 'tvms') rests on. A small p-value says the stream is not Poisson at any rate function, so those methods are answering a different process.

      The trace holds INTER-ARRIVAL times, so the arrival epochs are their cumulative sum and the horizon is the last of them.

      Returns:
      the map of infer_nhpp_ks: statistic, pvalue and n

    • sample

      public double[] sample(int n)
      Description copied from class: Distribution
      Generates random samples from this distribution using default random generator.
      Overrides:
      sample in class Distribution
      Parameters:
      n - the number of samples to generate
      Returns:
      array of random samples

    • sample

      public double[] sample(int n, Random random)
      Description copied from class: Distribution
      Generates random samples from this distribution using the specified random generator.
      Specified by:
      sample in class Distribution
      Parameters:
      n - the number of samples to generate
      random - the random number generator to use
      Returns:
      array of random samples