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Open-source constraint solver.
/*
* This file is part of choco-solver, http://choco-solver.org/
*
* Copyright (c) 2022, IMT Atlantique. All rights reserved.
*
* Licensed under the BSD 4-clause license.
*
* See LICENSE file in the project root for full license information.
*/
package org.chocosolver.solver.propagation;
import org.chocosolver.solver.ICause;
import org.chocosolver.solver.Model;
import org.chocosolver.solver.constraints.Propagator;
import org.chocosolver.solver.variables.IntVar;
import org.chocosolver.solver.variables.SetVar;
import org.chocosolver.solver.variables.Variable;
import org.chocosolver.solver.variables.events.IEventType;
import org.chocosolver.solver.variables.events.IntEventType;
import org.chocosolver.solver.variables.events.SetEventType;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.HashMap;
import java.util.stream.Stream;
/**
* This class observes a {@link PropagationEngine} in order to collect
* data relative to propagation.
*
*
* @author Charles Prud'homme
* @since 12/10/2021
*/
public class PropagationProfiler implements PropagationObserver {
private final Model model;
private final long[] propCounters = new long[4];
private final HashMap, Long> coarses;
private final HashMap, Long> fines;
private final HashMap, Long> failures;
private final HashMap, Long> filters;
private final HashMap> changes;
/**
* A propagation engine profiler.
*
* @param model the declaring model
*/
public PropagationProfiler(Model model) {
this.model = model;
this.coarses = new HashMap<>();
this.fines = new HashMap<>();
this.filters = new HashMap<>();
this.failures = new HashMap<>();
this.changes = new HashMap<>();
}
@Override
public void onCoarseEvent(Propagator propagator) {
coarses.compute(propagator, (k, c) -> c == null ? 1 : c + 1);
propCounters[0]++;
}
@Override
public void onFineEvent(Propagator propagator) {
fines.compute(propagator, (k, c) -> c == null ? 1 : c + 1);
propCounters[1]++;
}
@Override
public void onFailure(ICause cause, Propagator propagator) {
failures.compute(propagator, (k, c) -> c == null ? 1 : c + 1);
propCounters[3]++;
}
@Override
public void onFiltering(ICause cause, Propagator propagator) {
if (cause instanceof Propagator && cause.equals(propagator)) {
filters.compute((Propagator) cause, (k, c) -> c == null ? 1 : c + 1);
propCounters[2]++;
}
}
@Override
public void onVariableModification(Variable variable, IEventType type, ICause cause) {
HashMap evt = changes.computeIfAbsent(variable, k -> new HashMap<>());
evt.compute(type, (t, c) -> c == null ? 1 : c + 1);
}
/**
* Write profiling statistics to the file.
* It constructs a {@code FileWriter} given the {@code File} to write,
* then creates a new {@code PrintWriter}.
*
* @param file output file
* @param rawValues set to true to print raw values, false to print normalised values.
* @throws IOException if the file exists but is a directory rather than a regular file,
* does not exist but cannot be created, or cannot be opened for any other reason
*/
public void writeTo(File file, boolean rawValues) throws IOException {
FileWriter fileWriter = new FileWriter(file);
PrintWriter writer = new PrintWriter(fileWriter);
writeTo(writer, rawValues);
writer.close();
}
/**
* Write profiling statistics to the print writer.
* writer is not closed at the end of the call.
*
*
* Example of usages, print profiling data to System.out:
*
* {@code
* PropagationProfiler profiler = solver.profilePropagation();
* solver.findAllSolutions();
* PrintWriter pw = new PrintWriter(System.out);
* profiler.writeTo(pw, true);
* pw.flush();
* }
*
* @param writer a print writer
* @param rawValues set to true to print raw values, false to print normalised values.
*/
public void writeTo(PrintWriter writer, boolean rawValues) {
profilePropagators(writer, rawValues);
profileVariables(writer);
}
private void profilePropagators(PrintWriter writer, boolean rawValues) {
writer.println("Propagators\n" +
" \n" +
"* id : row id\n" +
"* coarse : for a given propagator, number of coarse propagations, i.e., calls to `propagate(int)`\n" +
"* fine : for a given propagator, number of fine propagations, i.e., calls to `propagate(int,int)`\n" +
"* filter : for a given propagator, number of times a call to propagation removes a value from a variable's domain\n" +
"* fails : for a given propagator, number of times it throws a failure\n" +
"* name : name of the given propagator \n" +
" \n" +
" id coarse fine filter fails name");
Propagator[] propagators = Stream.of(model.getCstrs()).flatMap(c -> Stream.of(c.getPropagators())).toArray(Propagator[]::new);
for (int i = 0; i < propagators.length; i++) {
Propagator p = propagators[i];
long c = coarses.getOrDefault(p, 0L);
long fi = fines.getOrDefault(p, 0L);
long fl = filters.getOrDefault(p, 0L);
long fa = failures.getOrDefault(p, 0L);
if (rawValues) {
writer.printf(" %-6d %9d %9d %9d %9d \"%s\"%n",
i, c, fi, fl, fa, p.toString()
);
} else {
writer.printf(" %-6d %8.2f%% %8.2f%% %8.2f%% %8.2f%% \"%s\"%n",
i, c * 100d / propCounters[0], fi * 100d / propCounters[1], fl * 100d / propCounters[2], fa * 100d / propCounters[3], p.toString()
);
}
}
writer.printf("Total %9d %9d %9d %9d%n",
propCounters[0],
propCounters[1],
propCounters[2],
propCounters[3]
);
writer.println();
}
private void profileVariables(PrintWriter writer) {
IntVar[] ivars = model.retrieveIntVars(true);
int k = 0;
if (ivars.length > 0) {
writer.println("Integer variables\n" +
" \n" +
"* id : row id\n" +
"* inst : for a given integer variable, number of instantiation events\n" +
"* lower : for a given integer variable, number of lower bound increasing events\n" +
"* upper : for a given integer variable, number of upper bound decreasing events\n" +
"* bounds : for a given integer variable, number of bounds modification events\n" +
"* remove : for a given integer variable, number of value removal events\n" +
"* name : name of the given variable \n" +
" \n" +
" id inst lower upper bounds remove name");
for (int i = 0; i < ivars.length; i++) {
HashMap evts = changes.getOrDefault(ivars[i], new HashMap<>());
long in = evts.getOrDefault(IntEventType.INSTANTIATE, 0L);
long lb = evts.getOrDefault(IntEventType.INCLOW, 0L);
long ub = evts.getOrDefault(IntEventType.DECUPP, 0L);
long bd = evts.getOrDefault(IntEventType.BOUND, 0L);
long rm = evts.getOrDefault(IntEventType.REMOVE, 0L);
writer.printf(" %-6d %9d %9d %9d %9d %9d \"%s\"%n",
k++, in, lb, ub, bd, rm, ivars[i].getName()
);
}
writer.println();
}
SetVar[] svars = model.retrieveSetVars();
if (svars.length > 0) {
writer.println("Set variables\n" +
" \n" +
"* id : row id\n" +
"* kernel : for a given integer variable, number of instantiation events\n" +
"* envel : for a given integer variable, number of lower bound increasing events\n" +
"* name : name of the given variable \n" +
" \n" +
" id kernel envel name");
writer.println("Set variables");
writer.printf(" id kernel envel name%n");
for (int i = 0; i < svars.length; i++) {
HashMap evts = changes.getOrDefault(svars[i], new HashMap<>());
long ka = evts.getOrDefault(SetEventType.ADD_TO_KER, 0L);
long re = evts.getOrDefault(SetEventType.REMOVE_FROM_ENVELOPE, 0L);
writer.printf(" %-6d %9d %9d \"%s\"%n",
k++, ka, re, svars[i].getName()
);
}
writer.println();
}
}
}