- CsvResult and Result classes for improved iteration and CSV output; - update SimulationBuilder to include confidence index handling - rename setRuns to setMaxRuns for clarity
182 lines
6.1 KiB
Java
182 lines
6.1 KiB
Java
package net.berack.upo.valpre;
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import java.io.FileNotFoundException;
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import java.io.IOException;
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import java.util.List;
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import java.util.concurrent.ExecutionException;
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import com.esotericsoftware.kryo.KryoException;
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import net.berack.upo.valpre.sim.ConfidenceIndices;
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import net.berack.upo.valpre.sim.EndCriteria;
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import net.berack.upo.valpre.sim.Net;
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import net.berack.upo.valpre.sim.SimulationMultiple;
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import net.berack.upo.valpre.sim.stats.CsvResult;
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import net.berack.upo.valpre.sim.stats.NodeStats;
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/**
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* This class is responsible for running the simulation. It parses the arguments
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* and runs the simulation with the given parameters.
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*/
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public class SimulationBuilder {
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private String csv;
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private int runs;
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private long seed;
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private boolean parallel;
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private Net net;
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private EndCriteria[] endCriteria;
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private ConfidenceIndices confidences;
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/**
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* Create a new simulation for the given net.
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*
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* @param netFile the net file to load
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* @throws IOException if the file has a problem
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*/
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public SimulationBuilder(String netFile) throws IOException {
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try {
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var file = Parameters.getFileOrExample(netFile);
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this.net = Net.load(file);
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this.confidences = new ConfidenceIndices(this.net);
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file.close();
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} catch (FileNotFoundException e) {
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throw new IllegalArgumentException("Net file needed!");
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} catch (KryoException e) {
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throw new IllegalArgumentException("Net file is not valid or corrupted!");
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}
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}
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/**
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* Create a new simulation for the given net.
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*
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* @param net the net
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* @throws IllegalArgumentException if the net is null
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*/
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public SimulationBuilder(Net net) {
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if (net == null)
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throw new IllegalArgumentException("Net needed!");
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this.net = net;
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this.confidences = new ConfidenceIndices(net);
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}
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/**
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* Set the maximum number of runs for the simulation.
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*
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* @param runs the number of runs
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* @throws IllegalArgumentException if the runs are less than 1
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* @return this simulation
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*/
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public SimulationBuilder setMaxRuns(int runs) {
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if (runs <= 0)
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throw new IllegalArgumentException("Runs must be greater than 0!");
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this.runs = runs;
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return this;
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}
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/**
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* Set the seed for the simulation.
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*
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* @param seed the seed
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* @return this simulation
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*/
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public SimulationBuilder setSeed(long seed) {
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this.seed = seed;
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return this;
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}
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/**
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* Set if the simulation should run in parallel.
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* The parallelization is done by running each simulation in a separate thread.
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*
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* @param parallel if the simulation should run in parallel
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* @return this simulation
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*/
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public SimulationBuilder setParallel(boolean parallel) {
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this.parallel = parallel;
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return this;
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}
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/**
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* Set the CSV file to save the results.
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*
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* @param csv the CSV file
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* @return this simulation
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*/
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public SimulationBuilder setCsv(String csv) {
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this.csv = csv;
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return this;
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}
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/**
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* Set the end criteria for the simulation.
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* Can be an empty array if no criteria are needed.
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* Cannot be null.
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*
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* @param criterias the end criteria
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* @return this simulation
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* @throws IllegalArgumentException if the criteria are null
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*/
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public SimulationBuilder setEndCriteria(EndCriteria... criterias) {
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if (criterias == null)
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throw new IllegalArgumentException("End criteria cannot be null!");
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this.endCriteria = criterias;
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return this;
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}
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/**
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* Add a confidence index for the given node and stat.
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* The confidence index is used to determine when the simulation should stop.
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*
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*
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* @param node the node
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* @param stat the stat to calculate the confidence index for
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* @param confidence the confidence level expressed as a percentage [0,1]
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* @param relError the relative error expressed as a percentage [0,1]
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* @return this simulation
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* @throws IllegalArgumentException if the node is invalid
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* @throws IllegalArgumentException if the stat is invalid
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* @throws IllegalArgumentException if the confidence is invalid
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* @throws IllegalArgumentException if the relative error is invalid
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*/
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public SimulationBuilder addConfidenceIndex(String node, String stat, double confidence, double relError) {
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if (!List.of(NodeStats.getOrderOfApply()).contains(stat))
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throw new IllegalArgumentException("Invalid statistic: " + stat);
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if (confidence <= 0 || confidence > 1)
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throw new IllegalArgumentException("Confidence must be between 0 and 1");
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if (relError <= 0 || relError > 1)
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throw new IllegalArgumentException("Relative error must be between 0 and 1");
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var index = this.net.getNodeIndex(node);
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if (index < 0)
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throw new IllegalArgumentException("Invalid node: " + node);
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this.confidences.add(index, stat, confidence, relError);
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return this;
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}
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/**
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* Run the simulation with the given parameters.
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* At the end it prints the results and saves them to a CSV file if requested.
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*
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* @throws InterruptedException If the simulation is interrupted.
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* @throws ExecutionException If the simulation has an error.
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* @throws IOException If the CSV file has a problem.
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*/
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public void run() throws InterruptedException, ExecutionException, IOException {
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var nano = System.nanoTime();
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var sim = new SimulationMultiple(this.net);
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var summary = this.parallel
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? sim.runParallel(this.seed, this.runs, this.endCriteria)
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: sim.run(this.seed, this.runs, this.endCriteria);
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nano = System.nanoTime() - nano;
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System.out.print(summary);
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System.out.println("Final time " + nano / 1e6 + "ms");
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if (csv != null) {
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new CsvResult(this.csv).saveResults(summary.getRuns());
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System.out.println("Data saved to " + this.csv);
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}
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}
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}
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