Add incremental run support and confidence index handling in simulation

.vscode/launch.json

@@ -25,6 +25,13 @@
             "mainClass": "net.berack.upo.valpre.Main",
             "args": "simulation -net example3.net -runs 1000 -p -seed 0"
         },
+        {
+            "type": "java",
+            "name": "Run Incremental",
+            "request": "launch",
+            "mainClass": "net.berack.upo.valpre.Main",
+            "args": "simulation -net example3.net -runs 1000 -seed 0 -i \"[Service1:throughput=0.98:0.01],[Service2:utilization=0.98:0.01],[Service2:unavailable=0.98:0.01]\""
+        },
         {
             "type": "java",
             "name": "Run10",

src/main/java/net/berack/upo/valpre/Main.java

@@ -24,6 +24,7 @@ public class Main {
                             .setSeed(param.getOrDefault("seed", Long::parseLong, 2007539552L))
                             .setParallel(param.get("p") != null)
                             .setEndCriteria(EndCriteria.parse(param.get("end")))
+                            .parseConfidenceIndices(param.get("i"))
                             .run();
                 }
                 case "plot" -> {
@@ -58,6 +59,7 @@ public class Main {
         arguments.put("net", true);
         arguments.put("end", true);
         arguments.put("csv", true);
+        arguments.put("i", true);
 
         var descriptions = new HashMap<String, String>();
         descriptions.put("p", "Add this if you want the simulation to use threads (one each run).");
@@ -65,6 +67,8 @@ public class Main {
         descriptions.put("runs", "How many runs the simulator should run.");
         descriptions.put("end", "When the simulation should end. Format is [ClassName:param1,..,paramN];[..]");
         descriptions.put("net", "The file net to use. Use example1.net or example2.net for the provided ones.");
+        descriptions.put("i", "The confidence indices to use for the simulation. If active then p is ignored."
+                + "Format is [node:stat:confidence:relativeError];[..]");
 
         var csvDesc = switch (program) {
             case "simulation" -> "The filename for saving every run statistics.";
@@ -85,7 +89,8 @@ public class Main {
             var name = new File(uri).getName();
             System.out.println(message);
             System.out.println("Usage: java -jar " + name + ".jar [simulation|plot|net] [args]");
-            System.out.println("simulation args: -net <net> -csv <csv> [-runs <runs>] [-seed <seed>] [-p]");
+            System.out.println("simulation args: -net <net> [-csv <csv>] [-runs <runs>] [-seed <seed>]"
+                    + "[-p] [-end <end>] [-i <indices>]");
             System.out.println("plot args: -csv <csv>");
             System.out.println("net args: none");
             System.exit(1);

src/main/java/net/berack/upo/valpre/SimulationBuilder.java

@@ -2,7 +2,6 @@ package net.berack.upo.valpre;
 
 import java.io.FileNotFoundException;
 import java.io.IOException;
-import java.util.List;
 import java.util.concurrent.ExecutionException;
 import com.esotericsoftware.kryo.KryoException;
 
@@ -11,7 +10,6 @@ import net.berack.upo.valpre.sim.EndCriteria;
 import net.berack.upo.valpre.sim.Net;
 import net.berack.upo.valpre.sim.SimulationMultiple;
 import net.berack.upo.valpre.sim.stats.CsvResult;
-import net.berack.upo.valpre.sim.stats.NodeStats;
 
 /**
  * This class is responsible for running the simulation. It parses the arguments
@@ -21,10 +19,10 @@ public class SimulationBuilder {
     private String csv;
     private int runs;
     private long seed;
-    private boolean parallel;
     private Net net;
     private EndCriteria[] endCriteria;
     private ConfidenceIndices confidences;
+    private Type type = Type.Normal;
 
     /**
      * Create a new simulation for the given net.
@@ -92,7 +90,8 @@ public class SimulationBuilder {
      * @return this simulation
      */
     public SimulationBuilder setParallel(boolean parallel) {
-        this.parallel = parallel;
+        if (parallel && !this.confidences.isEmpty())
+            this.type = Type.Parallel;
         return this;
     }
 
@@ -133,24 +132,51 @@ public class SimulationBuilder {
      * @param confidence the confidence level expressed as a percentage [0,1]
      * @param relError   the relative error expressed as a percentage [0,1]
      * @return this simulation
-     * @throws IllegalArgumentException if the node is invalid
+     * @throws IllegalArgumentException if any of the input parameters is invalid
-     * @throws IllegalArgumentException if the stat is invalid
-     * @throws IllegalArgumentException if the confidence is invalid
-     * @throws IllegalArgumentException if the relative error is invalid
      */
     public SimulationBuilder addConfidenceIndex(String node, String stat, double confidence, double relError) {
-        if (!List.of(NodeStats.getOrderOfApply()).contains(stat))
-            throw new IllegalArgumentException("Invalid statistic: " + stat);
-        if (confidence <= 0 || confidence > 1)
-            throw new IllegalArgumentException("Confidence must be between 0 and 1");
-        if (relError <= 0 || relError > 1)
-            throw new IllegalArgumentException("Relative error must be between 0 and 1");
-
         var index = this.net.getNodeIndex(node);
         if (index < 0)
             throw new IllegalArgumentException("Invalid node: " + node);
 
         this.confidences.add(index, stat, confidence, relError);
+        this.type = Type.Incremental;
+        return this;
+    }
+
+    /**
+     * Parse the confidence indices from a string and add them to the simulation.
+     * If the string is null then nothing is done and the builder is returned.
+     * The string must be in the following format:
+     * "[node1:stat1=confidence1:relError1],..,[nodeN:statN=confidenceN:relErrorN]".
+     * 
+     * @param indices the indices to parse
+     * @return this simulation
+     * @throws IllegalArgumentException if indices are not in the correct format
+     * @throws IllegalArgumentException if the values are invalid
+     */
+    public SimulationBuilder parseConfidenceIndices(String indices) {
+        if (indices == null)
+            return this;
+
+        for (var index : indices.split(",")) {
+            var parts = index.split("=");
+            if (parts.length != 2)
+                throw new IllegalArgumentException("Invalid confidence index: " + index);
+            var first = parts[0].split(":");
+            if (first.length != 2)
+                throw new IllegalArgumentException("Invalid confidence index: " + index);
+            var second = parts[1].split(":");
+            if (second.length != 2)
+                throw new IllegalArgumentException("Invalid confidence index: " + index);
+
+            var node = first[0].substring(1);
+            var stat = first[1];
+            var confidence = Double.parseDouble(second[0]);
+            var relError = Double.parseDouble(second[1].substring(0, second[1].length() - 1));
+            this.addConfidenceIndex(node, stat, confidence, relError);
+        }
+
         return this;
     }
 
@@ -165,9 +191,11 @@ public class SimulationBuilder {
     public void run() throws InterruptedException, ExecutionException, IOException {
         var nano = System.nanoTime();
         var sim = new SimulationMultiple(this.net);
-        var summary = this.parallel
+        var summary = switch (this.type) {
-                ? sim.runParallel(this.seed, this.runs, this.endCriteria)
+            case Incremental -> sim.runIncremental(this.seed, this.runs, this.confidences, this.endCriteria);
-                : sim.run(this.seed, this.runs, this.endCriteria);
+            case Parallel -> sim.runParallel(this.seed, this.runs, this.endCriteria);
+            case Normal -> sim.run(this.seed, this.runs, this.endCriteria);
+        };
         nano = System.nanoTime() - nano;
 
         System.out.print(summary);
@@ -178,4 +206,11 @@ public class SimulationBuilder {
             System.out.println("Data saved to " + this.csv);
         }
     }
+
+    /**
+     * Inner class to handle the type of simulation.
+     */
+    private static enum Type {
+        Incremental, Parallel, Normal
+    }
 }

src/main/java/net/berack/upo/valpre/sim/ConfidenceIndices.java

@@ -16,6 +16,7 @@ public class ConfidenceIndices {
     private final String[] nodes;
     private final NodeStats[] confidences;
     private final NodeStats[] relativeErrors;
+    private boolean isEmpty = true;
 
     /**
      * Create a new confidence indices object for the given network.
@@ -36,6 +37,15 @@ public class ConfidenceIndices {
         }
     }
 
+    /**
+     * Get the number of confidence indices added to the simulation.
+     * 
+     * @return the number of confidence indices
+     */
+    public boolean isEmpty() {
+        return this.isEmpty;
+    }
+
     /**
      * Add a confidence index to the simulation. The simulation will stop when the
      * relative error of the confidence index is less than the given value.
@@ -44,15 +54,24 @@ public class ConfidenceIndices {
      * @param stat       The statistic to calculate the confidence index for.
      * @param confidence The confidence level of the confidence index.
      * @param relError   The relative error of the confidence index.
+     * @throws IllegalArgumentException If the node is invalid, the confidence is
+     *                                  not between 0 and 1, or the relative error
+     *                                  is not between 0 and 1.
+     * @throws IllegalArgumentException If the statistic is invalid.
      */
     public void add(int node, String stat, double confidence, double relError) {
         if (node < 0 || node >= this.nodes.length)
             throw new IllegalArgumentException("Invalid node: " + node);
+        if (confidence <= 0 || confidence > 1)
+            throw new IllegalArgumentException("Confidence must be between 0 and 1");
+        if (relError <= 0 || relError > 1)
+            throw new IllegalArgumentException("Relative error must be between 0 and 1");
 
         try {
             Field field = NodeStats.class.getField(stat);
             field.set(this.confidences[node], confidence);
             field.set(this.relativeErrors[node], relError);
+            this.isEmpty = false;
         } catch (Exception e) {
             throw new IllegalArgumentException("Invalid statistic: " + stat);
         }
@@ -94,7 +113,7 @@ public class ConfidenceIndices {
 
             error.merge(relError, (err, rel) -> err - rel);
             for (var value : error)
-                if (value > 0)
+                if (!value.isInfinite() && !value.isNaN() && value > 0)
                     return false;
         }
 
@@ -110,20 +129,19 @@ public class ConfidenceIndices {
      * @param errors the relative errors of the statistics
      * @return the errors of the statistics
      */
-    public String[] getErrors(NodeStats[] errors) {
+    public String[] getIndices(NodeStats[] errors) {
         var statistics = NodeStats.getOrderOfApply();
         var retValues = new ArrayList<String>();
 
         for (var i = 0; i < this.relativeErrors.length; i++) {
             var error = errors[i].clone();
-            var relError = this.relativeErrors[i];
-            error.merge(relError, (err, rel) -> err - rel);
 
-            var j = 0;
+            for (var stat : statistics) {
-            for (var value : error) {
+                var err = error.of(stat);
-                if (value > 0)
+                if (!Double.isFinite(err))
-                    retValues.add("%s:%s=%0.3f".formatted(this.nodes[i], statistics[j], value));
+                    continue;
-                j += 1;
+
+                retValues.add("%s:%s=%.3f".formatted(this.nodes[i], stat, err));
             }
         }
 

src/main/java/net/berack/upo/valpre/sim/SimulationMultiple.java

@@ -101,11 +101,11 @@ public class SimulationMultiple {
      * @return The statistics the network.
      * @throws IllegalArgumentException If the confidence is not set.
      */
-    public void runIncremental(long seed, int runs, ConfidenceIndices confidences, EndCriteria... criterias) {
+    public Result.Summary runIncremental(long seed, int runs, ConfidenceIndices confidences, EndCriteria... criterias) {
         if (confidences == null)
             throw new IllegalArgumentException("Confidence must be not null");
 
-        var rng = new Rng(seed);
+        var rng = new Rng(seed); // Only one RNG for all the simulations
         var results = new Result.Summary(rng.getSeed());
         var output = new StringBuilder();
         var stop = false;
@@ -121,7 +121,7 @@ public class SimulationMultiple {
                 var errors = confidences.calcRelativeErrors(results);
                 stop = confidences.isOk(errors);
 
-                var errString = confidences.getErrors(errors);
+                var errString = confidences.getIndices(errors);
                 var oneSting = String.join("], [", errString);
 
                 output.append('[').append(oneSting).append("]");
@@ -129,8 +129,8 @@ public class SimulationMultiple {
             }
         }
 
-        System.out.println("\nSimulation ended");
+        System.out.println(); // remove last printed line
-        System.out.println(results);
+        return results;
     }
 
 }