@Test
public void optimizeTest() throws IOException {
List<Map> maps = mapper.readValue(json, new TypeReference<List<Map>>() {});
Optimizer optimizer = new Optimizer();
List<Vol> optimize = optimizer.optimize4(Vol.fromMaps(maps));
System.out.println(optimizer.formatString(optimize));
}
@Test
public void optimizeRand() throws IOException {
Optimizer optimizer = new Optimizer();
long start;
List<Vol> optimize;
for (int i = 0; i < 1; i++) {
List<Vol> list = randList(100000);
start = System.currentTimeMillis();
// optimize = optimizer.optimize3(null, list);
// System.out.println(optimizer.formatString(optimize));
// System.out.println(System.currentTimeMillis() - start);
// System.out.println(Vol.toString(optimize));
start = System.currentTimeMillis();
List<Vol> optimize2 = optimizer.optimize4(list);
long duration = System.currentTimeMillis() - start;
System.out.println(optimizer.formatString(optimize2));
System.out.println(duration);
// System.out.println(Vol.toString(optimize2));
//
// assertThat(Optimizer.price(optimize)).isLessThanOrEqualTo(Optimizer.price(optimize2));
Iterator<Vol> iterator = optimize2.iterator();
Vol vol = iterator.next();
while (iterator.hasNext()) {
Vol next = iterator.next();
assertThat(vol.isNext(next)).isTrue();
vol = next;
}
}
}
@Override
protected T compute() {
Optimizer<T> optimizer =
optimizerFactory.create(
new TemperatureFunction() {
@Override
public double temperature(int currentStep, int nSteps) {
return tempScale * subTempFun.temperature(currentStep, nSteps);
}
});
return optimizer.iterate(subOptimizerSteps, initial);
}
private double preparePlan() {
TableFilter[] topArray = topFilters.toArray(new TableFilter[topFilters.size()]);
for (TableFilter t : topArray) {
t.setFullCondition(condition);
}
Optimizer optimizer = new Optimizer(topArray, condition, session);
optimizer.optimize();
topTableFilter = optimizer.getTopFilter();
double planCost = optimizer.getCost();
setEvaluatableRecursive(topTableFilter);
topTableFilter.prepare();
return planCost;
}
protected void checkGraph(String fileName, String dirName)
throws IOException, SyntaxFormatException {
Parser parser = new Parser(fileName);
parser.parse();
Optimizer optimizer = new Optimizer(Optimizer.LEVEL.ALL);
// optimizer.copyPropagate(parser.getRootBlock());
// optimizer.commonExpressionChangeToMove(parser.getRootBlock());
optimizer.optimize(parser.getRootBlock());
for (Function func : Function.getAllFunction()) {
// optimizer.copyPropagate(func.getBody().getFirstBlock());
// optimizer.commonExpressionChangeToMove(func.getBody().getFirstBlock());
optimizer.optimize(func.getBody().getFirstBlock());
}
Block blk = parser.getRootBlock();
PrintWriter writer =
new PrintWriter(fileName.replaceAll("testprogs", dirName) + ".vcg", "UTF-8");
writer.print(GraphPrinter.printCFGBody(blk, "main", true));
writer.close();
}
/** Run the literal op upgrader */
private void run() {
final TranslationAdvice advice = Optimizer.getAdvice();
ssaMeth.forEachInsn(
new SsaInsn.Visitor() {
public void visitMoveInsn(NormalSsaInsn insn) {
// do nothing
}
public void visitPhiInsn(PhiInsn insn) {
// do nothing
}
public void visitNonMoveInsn(NormalSsaInsn insn) {
Insn originalRopInsn = insn.getOriginalRopInsn();
Rop opcode = originalRopInsn.getOpcode();
RegisterSpecList sources = insn.getSources();
// Replace insns with constant results with const insns
if (tryReplacingWithConstant(insn)) return;
if (sources.size() != 2) {
// We're only dealing with two-source insns here.
return;
}
if (opcode.getBranchingness() == Rop.BRANCH_IF) {
/*
* An if instruction can become an if-*z instruction.
*/
if (isConstIntZeroOrKnownNull(sources.get(0))) {
replacePlainInsn(
insn, sources.withoutFirst(), RegOps.flippedIfOpcode(opcode.getOpcode()), null);
} else if (isConstIntZeroOrKnownNull(sources.get(1))) {
replacePlainInsn(insn, sources.withoutLast(), opcode.getOpcode(), null);
}
} else if (advice.hasConstantOperation(opcode, sources.get(0), sources.get(1))) {
insn.upgradeToLiteral();
} else if (opcode.isCommutative()
&& advice.hasConstantOperation(opcode, sources.get(1), sources.get(0))) {
/*
* An instruction can be commuted to a literal operation
*/
insn.setNewSources(RegisterSpecList.make(sources.get(1), sources.get(0)));
insn.upgradeToLiteral();
}
}
});
}
// --------------------------------------------------------------------
private int[] allocateBuckets(List<BucketTree.Branch> branches, char nBuckets, int nTrials) {
double errors[][] = new double[branches.size()][nTrials];
// int parentPaths[] = parentReachPaths(branches);
BUCKETIZER.setThorough(false);
for (int branchIndex = 0; branchIndex < branches.size(); branchIndex++) {
BucketTree.Branch branch = branches.get(branchIndex);
LOG.debug("allocating branch " + (branchIndex + 1) + " of " + branches.size());
for (byte nBucketTrial = 0; nBucketTrial < nTrials; nBucketTrial++) {
errors[branchIndex][nBucketTrial] = BUCKETIZER.bucketize(branch, (byte) (nBucketTrial + 1));
}
}
return Optimizer.optimize(errors, nBuckets);
}
// Maakt een random dienstregeling aan
// || In deze methode zou je je algoritme kunnen plaatsen in plaats van de
// 'domme'
// random methode die nu gebruikt wordt
public Dienstregeling maakDienstregeling() {
// Dienstregeling d = new Dienstregeling(true);
// Dienstregeling d = Optimizer.Optimize(10000,1000,2);
Dienstregeling d = new Dienstregeling();
int resultaatArray[] = new int[1000];
int min = 9999999;
int max = 0;
double avg = 0;
for (int i = 0; i < 1000; i++) {
d = Optimizer.Optimize2(100, 100, 0.1, 0.01);
int temp = d.telPassagiersKilometers();
avg += temp / 1000;
if (temp > max) {
max = temp;
}
if (temp < min) {
min = temp;
}
resultaatArray[i] = temp;
}
System.out.println("min: " + min + " max: " + max + " avg: " + avg);
return d;
}
@Override
public Serializable generate(SharedSessionContractImplementor session, Object object)
throws HibernateException {
return optimizer.generate(databaseStructure.buildCallback(session));
}
/* lossesList contains couples (Effect, Losses) */
public double[][] createLossesList(boolean bMonotonous, boolean bTheoretical) {
System.out.println("Creating losses list (Security Class -> Losses)... ");
Hashtable<Double, Double> htLossesList = new Hashtable<Double, Double>();
Hashtable<Integer, Double> htLossesLookup = new Hashtable<Integer, Double>();
Hashtable<Integer, Double> htEffectLookup = new Hashtable<Integer, Double>();
double[][] mdLossesList;
double dLosses;
// for every SecClass combination, calculate Losses, ReqLvls and Effectiveness
for (int i = 0; i < _iNrComb; i++) {
dLosses = 0;
int[] viSecClass = intToSecClass(i);
for (int j = 0; j < _viLvlsNbr.length; j++) {
dLosses +=
(Double)
ee.ioc.cs.vsle.api.ProgramContext.queryTable(
_sLossesTableID, Character.toString((_vsGoals[j]).charAt(0)), viSecClass[j]);
}
int[] reqLvlList = createReqLvlList(viSecClass, false);
double dEffect = Optimizer.calcEffect(reqLvlList);
// in case of duplicates use average value for losses
if (!htLossesList.containsKey(dEffect)) htLossesList.put(dEffect, dLosses);
else htLossesList.put(dEffect, (dLosses + htLossesList.get(dEffect)) / 2);
// create a lookup table for (secClass - losses) couples
htLossesLookup.put(i, dLosses);
// create a lookup table for (secClass - effect) couples
htEffectLookup.put(i, dEffect);
}
// if asked to, create a monotonously decreasing version of the losses information do
if (bMonotonous) {
mdLossesList = new double[_iNewNbrComb][2];
int[] viSecClass = new int[_vsGoals.length];
Arrays.fill(viSecClass, 0);
double dLossesRef, dMaxDiff, dTmpDiff;
int iIndex;
for (int i = 0; i < _iNewNbrComb; i++) {
mdLossesList[i][0] = htEffectLookup.get(secClassToInt(viSecClass));
mdLossesList[i][1] = htLossesLookup.get(secClassToInt(viSecClass));
dLossesRef = htLossesLookup.get(secClassToInt(viSecClass));
iIndex = 0;
dMaxDiff = 0;
dTmpDiff = 0;
for (int j = 0; j < _vsGoals.length; j++) {
if ((viSecClass[j] + 1) < _viLvlsNbr[j]) {
viSecClass[j] += 1;
dTmpDiff = dLossesRef - htLossesLookup.get(secClassToInt(viSecClass));
viSecClass[j] -= 1;
}
if (dTmpDiff > dMaxDiff) {
iIndex = j;
dMaxDiff = dTmpDiff;
}
}
viSecClass[iIndex] += 1;
}
}
// else, sort the Hashtable htLossesList with regard to the effectiveness values
else {
Vector<Double> vec = new Vector<Double>(htLossesList.keySet());
Collections.sort(vec);
Iterator<Double> it = vec.iterator();
mdLossesList = new double[htLossesList.size()][2];
int iI = 0;
while (it.hasNext()) {
double dOrdered = it.next();
mdLossesList[iI][0] = dOrdered;
mdLossesList[iI][1] = htLossesList.get(dOrdered);
iI++;
}
}
// if asked to add the theoretical point (Effect=1 - losses=0) do the following
if (bTheoretical) {
double[][] mdLossesListTemp = new double[mdLossesList.length + 1][2];
for (int i = 0; i < mdLossesList.length; i++) {
mdLossesListTemp[i][0] = mdLossesList[i][0];
mdLossesListTemp[i][1] = mdLossesList[i][1];
}
mdLossesListTemp[mdLossesListTemp.length - 1][0] = 1;
mdLossesListTemp[mdLossesListTemp.length - 1][1] = 0;
mdLossesList = new double[mdLossesListTemp.length][2];
for (int i = 0; i < mdLossesList.length; i++) {
mdLossesList[i][0] = mdLossesListTemp[i][0];
mdLossesList[i][1] = mdLossesListTemp[i][1];
}
}
System.out.println(Arrays.deepToString(mdLossesList));
System.out.println("... done");
return mdLossesList;
}
/**
* Goal-driven recursive (depth-first, exhaustive) search with backtracking
*
* @param problem
* @param algorithm
* @param subtaskRelsInPath
* @param depth
*/
private boolean subtaskPlanningImpl(
PlanningContext context,
Set<Rel> relsWithSubtasks,
EvaluationAlgorithm algorithm,
LinkedList<Rel> subtaskRelsInPath,
int depth) {
Set<Rel> relsWithSubtasksCopy = new LinkedHashSet<Rel>(relsWithSubtasks);
Set<Rel> relsWithSubtasksToRemove = new LinkedHashSet<Rel>();
boolean firstMLB = true;
// start building Maximal Linear Branch (MLB)
MLB:
while (!relsWithSubtasksCopy.isEmpty()) {
if (isSubtaskLoggingOn()) {
String print = p(depth) + "Starting new MLB with: ";
for (Rel rel : relsWithSubtasksCopy) {
print +=
"\n" + p(depth) + " " + rel.getParent().getFullName() + " : " + rel.getDeclaration();
}
/*
print += "\n" + p( depth ) + " All remaining rels in problem:";
for ( Rel rel : problem.getAllRels() ) {
print += "\n" + p( depth ) + " " + rel.getParentObjectName() + " : " + rel.getDeclaration();
}
print += "\n" + p( depth ) + "All found variables: ";
for ( Var var : problem.getFoundVars() ) {
print += "\n" + p( depth ) + " " + var.toString();
}
*/
logger.debug(print);
}
// if this is a first attempt to construct an MLB to solve a subtask(i.e. depth>0),
// do not invoke linear planning because it has already been done
if ((depth == 0) || !firstMLB) {
boolean solvedIntermediately = linearForwardSearch(context, algorithm, true);
// Having constructed some MLBs the (sub)problem may be solved
// and there is no need in wasting precious time planning unnecessary branches
if (solvedIntermediately
&& ( // on the top level optimize only if computing goals
(depth == 0 && !computeAll)
// otherwise (inside subtasks) always optimize
|| (depth != 0))) {
// If the problem is solved, optimize and return
if (!isOptDisabled) Optimizer.optimize(context, algorithm);
return true;
}
} else {
firstMLB = false;
}
// or children
OR:
for (Iterator<Rel> subtaskRelIterator = relsWithSubtasksCopy.iterator();
subtaskRelIterator.hasNext(); ) {
Rel subtaskRel = subtaskRelIterator.next();
if (isSubtaskLoggingOn())
logger.debug(
p(depth)
+ "OR: depth: "
+ (depth + 1)
+ " rel - "
+ subtaskRel.getParent().getFullName()
+ " : "
+ subtaskRel.getDeclaration());
if (subtaskRel.equals(subtaskRelsInPath.peekLast())
|| (!context.isRelReadyToUse(subtaskRel))
|| context.getFoundVars().containsAll(subtaskRel.getOutputs())
|| (!isSubtaskRepetitionAllowed && subtaskRelsInPath.contains(subtaskRel))) {
if (isSubtaskLoggingOn()) {
logger.debug(p(depth) + "skipped");
if (!context.isRelReadyToUse(subtaskRel)) {
logger.debug(p(depth) + "because it has unknown inputs"); // TODO print unknown
} else if (context.getFoundVars().containsAll(subtaskRel.getOutputs())) {
logger.debug(p(depth) + "because all outputs in FoundVars");
} else if (subtaskRel.equals(subtaskRelsInPath.peekLast())) {
logger.debug(p(depth) + "because it is nested in itself");
} else if (!isSubtaskRepetitionAllowed && subtaskRelsInPath.contains(subtaskRel)) {
logger.debug(
p(depth)
+ "This rel with subtasks is already in use, path: "
+ subtaskRelsInPath);
}
}
continue OR;
}
LinkedList<Rel> newPath = new LinkedList<Rel>(subtaskRelsInPath);
newPath.add(subtaskRel);
PlanningResult result = new PlanningResult(subtaskRel, true);
// this is true if all subtasks are solvable
boolean allSolved = true;
// and children
AND:
for (SubtaskRel subtask : subtaskRel.getSubtasks()) {
if (isSubtaskLoggingOn()) logger.debug(p(depth) + "AND: subtask - " + subtask);
EvaluationAlgorithm sbtAlgorithm = null;
////////////////////// INDEPENDENT SUBTASK////////////////////////////////////////
if (subtask.isIndependent()) {
if (isSubtaskLoggingOn()) logger.debug("Independent!!!");
if (subtask.isSolvable() == null) {
if (isSubtaskLoggingOn())
logger.debug("Start solving independent subtask " + subtask.getDeclaration());
// independent subtask is solved only once
Problem problemContext = subtask.getContext();
DepthFirstPlanner planner = new DepthFirstPlanner();
planner.indSubtasks = indSubtasks;
planner.nested = true;
sbtAlgorithm = planner.invokePlaning(problemContext, isOptDisabled);
PlanningContext indCntx = problemContext.getCurrentContext();
boolean solved = indCntx.getFoundVars().containsAll(indCntx.getAllGoals());
if (solved) {
subtask.setSolvable(Boolean.TRUE);
indSubtasks.put(subtask, sbtAlgorithm);
if (isSubtaskLoggingOn()) logger.debug("Solved " + subtask.getDeclaration());
} else {
subtask.setSolvable(Boolean.FALSE);
if (RuntimeProperties.isLogInfoEnabled()) {
logger.debug("Unable to solve " + subtask.getDeclaration());
}
}
allSolved &= solved;
} else if (subtask.isSolvable() == Boolean.TRUE) {
if (isSubtaskLoggingOn()) logger.debug("Already solved");
allSolved &= true;
sbtAlgorithm = indSubtasks.get(subtask);
} else {
if (isSubtaskLoggingOn()) logger.debug("Not solvable");
allSolved &= false;
}
if (isSubtaskLoggingOn()) logger.debug("End of independent subtask " + subtask);
if (!allSolved) {
continue OR;
}
assert sbtAlgorithm != null;
result.addSubtaskAlgorithm(subtask, sbtAlgorithm);
}
////////////////////// DEPENDENT SUBTASK//////////////////////////////////////
else {
// lets clone the environment
PlanningContext newContext = prepareNewContext(context, subtask);
sbtAlgorithm = new EvaluationAlgorithm();
// during linear planning, if some goals are found, they are removed from the set
// "goals"
boolean solved =
linearForwardSearch(
newContext,
sbtAlgorithm,
// do not optimize here, because the solution may require additional rels with
// subtasks
true);
if (solved) {
if (isSubtaskLoggingOn()) logger.debug(p(depth) + "SOLVED subtask: " + subtask);
if (!isOptDisabled) {
// if a subtask has been solved, optimize its algorithm
Optimizer.optimize(newContext, sbtAlgorithm);
}
result.addSubtaskAlgorithm(subtask, sbtAlgorithm);
allSolved &= solved;
continue AND;
} else if (!solved && (depth == maxDepth)) {
if (isSubtaskLoggingOn())
logger.debug(p(depth) + "NOT SOLVED and cannot go any deeper, subtask: " + subtask);
continue OR;
}
if (isSubtaskLoggingOn()) logger.debug(p(depth) + "Recursing deeper");
solved =
subtaskPlanningImpl(newContext, relsWithSubtasks, sbtAlgorithm, newPath, depth + 1);
if (isSubtaskLoggingOn()) logger.debug(p(depth) + "Back to depth " + (depth + 1));
// the linear planning has been performed at the end of MLB on the depth+1,
// if the problem was solved, there is no need to run linear planning again
if ((solved || (solved = linearForwardSearch(newContext, sbtAlgorithm, true)))
&& !isOptDisabled) {
// if solved, optimize here with full list of goals in order to get rid of
// unnecessary subtask instances and other relations
Optimizer.optimize(newContext, sbtAlgorithm);
}
if (isSubtaskLoggingOn())
logger.debug(p(depth) + (solved ? "" : "NOT") + " SOLVED subtask: " + subtask);
allSolved &= solved;
// if at least one subtask is not solvable, try another
// branch
if (!allSolved) {
continue OR;
}
result.addSubtaskAlgorithm(subtask, sbtAlgorithm);
}
} // AND
if (allSolved) {
algorithm.add(result);
Set<Var> newVars = new LinkedHashSet<Var>();
unfoldVarsToSet(subtaskRel.getOutputs(), newVars);
context.getKnownVars().addAll(newVars);
context.getFoundVars().addAll(newVars);
subtaskRelIterator.remove();
if (isSubtaskLoggingOn()) {
logger.debug(
p(depth)
+ "SOLVED ALL SUBTASKS for "
+ subtaskRel.getParent().getFullName()
+ " : "
+ subtaskRel.getDeclaration());
logger.debug(p(depth) + "Updating the problem graph and continuing building new MLB");
}
// this is used for incremental dfs
if (depth == 0) {
relsWithSubtasksToRemove.add(subtaskRel);
}
continue MLB;
}
if (isSubtaskLoggingOn())
logger.debug(
p(depth)
+ "NOT SOLVED ALL subtasks, removing from path "
+ subtaskRel.getParent().getFullName()
+ " : "
+ subtaskRel.getDeclaration());
newPath.remove(subtaskRel);
} // end OR
// exit loop because there are no more rels with subtasks to be
// applied
// (i.e. no more rels can introduce new variables into the
// algorithm)
if (isSubtaskLoggingOn()) logger.debug(p(depth) + "No more MLB can be constructed");
break MLB;
}
// incremental dfs, remove solved subtasks
if (depth == 0) {
relsWithSubtasks.removeAll(relsWithSubtasksToRemove);
}
return false;
}
/**
* Linear forward search algorithm
*
* @param p
* @param algorithm
* @param targetVars
* @param _computeAll
* @return
*/
private boolean linearForwardSearch(
PlanningContext context, EvaluationAlgorithm algorithm, boolean _computeAll) {
/*
* while iterating through hashset, items cant be removed from/added to
* that set. Theyre collected into these sets and added/removedall
* together after iteration is finished
*/
Set<Var> newVars = new LinkedHashSet<Var>();
Set<Var> relOutputs = new LinkedHashSet<Var>();
Set<Var> removableVars = new LinkedHashSet<Var>();
boolean changed = true;
if (isLinearLoggingOn())
logger.debug(
"------Starting linear planning with (sub)goals: "
+ context.getRemainingGoals()
+ "--------");
if (isLinearLoggingOn()) logger.debug("Algorithm " + algorithm);
int counter = 1;
while ((!_computeAll && changed && !context.getRemainingGoals().isEmpty())
|| (changed && _computeAll)) {
if (isLinearLoggingOn()) logger.debug("----Iteration " + counter + " ----");
counter++;
changed = false;
// iterate through all knownvars
if (isLinearLoggingOn()) logger.debug("Known:" + context.getKnownVars());
for (Var var : context.getKnownVars()) {
if (isLinearLoggingOn()) logger.debug("Current Known: " + var);
// Check the relations of all components
for (Rel rel : var.getRels()) {
if (isLinearLoggingOn()) logger.debug("And its rel: " + rel);
if (context.isAvailableRel(rel)) {
context.removeUnknownInput(rel, var);
if (isLinearLoggingOn()) logger.debug("problem contains it " + rel);
removableVars.add(var);
if (context.isRelReadyToUse(rel) && rel.getType() != RelType.TYPE_METHOD_WITH_SUBTASK) {
if (isLinearLoggingOn()) logger.debug("rel is ready to be used " + rel);
boolean relIsNeeded = false;
if (isLinearLoggingOn()) logger.debug("its outputs " + rel.getOutputs());
for (Var relVar : rel.getOutputs()) {
if (!context.getFoundVars().contains(relVar)) {
relIsNeeded = true;
}
}
if (rel.getOutputs().isEmpty()) {
relIsNeeded = true;
}
if (isLinearLoggingOn()) logger.debug("relIsNeeded " + relIsNeeded);
if (relIsNeeded) {
if (isLinearLoggingOn()) logger.debug("needed rel: " + rel);
if (!rel.getOutputs().isEmpty()) {
relOutputs.clear();
unfoldVarsToSet(rel.getOutputs(), relOutputs);
newVars.addAll(relOutputs);
context.getFoundVars().addAll(relOutputs);
}
algorithm.addRel(rel);
if (isLinearLoggingOn()) logger.debug("algorithm " + algorithm);
}
context.removeRel(rel);
changed = true;
}
}
}
}
// remove targets if they have already been found
for (Iterator<Var> targetIter = context.getRemainingGoals().iterator();
targetIter.hasNext(); ) {
Var targetVar = targetIter.next();
if (context.getFoundVars().contains(targetVar)) {
targetIter.remove();
}
}
if (isLinearLoggingOn()) logger.debug("foundvars " + context.getFoundVars());
context.getKnownVars().addAll(newVars);
context.getKnownVars().removeAll(removableVars);
newVars.clear();
}
if (isLinearLoggingOn()) logger.debug("algorithm " + algorithm);
if (!_computeAll) {
Optimizer.optimize(context, algorithm);
if (isLinearLoggingOn()) logger.debug("optimized algorithm " + algorithm);
}
if (isLinearLoggingOn()) logger.debug("\n---!!!Finished linear planning!!!---\n");
return context.getRemainingGoals().isEmpty()
|| context.getFoundVars().containsAll(context.getAllGoals());
}
public static void main(final String[] args) throws Exception {
new RPClassGenerator().createRPClasses();
final CreatureGroupsXMLLoader loader = new CreatureGroupsXMLLoader("/data/conf/creatures.xml");
final List<DefaultCreature> creatures = loader.load();
Collections.sort(
creatures,
new Comparator<DefaultCreature>() {
@Override
public int compare(final DefaultCreature o1, final DefaultCreature o2) {
return o1.getLevel() - o2.getLevel();
}
});
final int[] atkLevels = new int[HIGHEST_LEVEL + 1];
final int[] defLevels = new int[HIGHEST_LEVEL + 1];
for (int level = 0; level < atkLevels.length; level++) {
// help newbies a bit, so don't start at real stats, but a bit lower
atkLevels[level] = (int) Math.round(Math.log(level + 4) * 9 - 10);
defLevels[level] = (int) Math.round(Math.log(level + 4) * 20 + level - 26);
}
final EntityManager em = SingletonRepository.getEntityManager();
final Item shield = em.getItem("wooden shield");
final Item armor = em.getItem("dress");
final Item helmet = em.getItem("leather helmet");
final Item legs = em.getItem("leather legs");
final Item boots = em.getItem("leather boots");
player = (Player) new PlayerTransformer().transform(new RPObject());
player.equip("lhand", shield);
player.equip("rhand", em.getItem("club"));
player.equip("armor", armor);
player.equip("head", helmet);
player.equip("legs", legs);
player.equip("feet", boots);
// Setup the list of creatures to balance
Collection<DefaultCreature> creaturesToBalance;
if (args.length > 0) {
Collection<String> names = Arrays.asList(args);
creaturesToBalance = new ArrayList<DefaultCreature>();
for (DefaultCreature creature : creatures) {
if (names.contains(creature.getCreatureName())) {
creaturesToBalance.add(creature);
}
}
} else {
// default to all of them
creaturesToBalance = creatures;
}
for (final DefaultCreature creature : creaturesToBalance) {
final int level = creature.getLevel();
if (creature.getLevel() > HIGHEST_LEVEL) {
continue;
}
final Creature target = creature.getCreature();
final Optimizer optimizer = new Optimizer(target);
player.setLevel(level);
player.setBaseHP(100 + 10 * level);
player.setAtk(atkLevels[level]);
player.setDef(defLevels[level]);
equip(player, level);
System.out.println("Player(" + level + ") vs " + creature.getCreatureName());
durationThreshold = DEFAULT_DURATION_THRESHOLD;
boolean balanced = false;
int tries = 0;
while (!balanced) {
final Pair<Integer, Integer> results = combat(player, target, ROUNDS);
final int meanTurns = results.first();
final int meanLeftHP = results.second();
final int proposedXPValue = (int) ((2 * creature.getLevel() + 1) * (meanTurns / 2.0));
creature.setLevel(creature.getLevel(), proposedXPValue);
System.out.println(
"Target ATK: "
+ target.getAtk()
+ "/DEF: "
+ target.getDef()
+ "/HP: "
+ target.getBaseHP()
+ "\t Turns: "
+ meanTurns
+ "\tLeft HP:"
+ meanLeftHP);
if (isCorrectResult(level, meanTurns, meanLeftHP / (double) player.getBaseHP())) {
balanced = true;
} else {
optimizer.step(meanLeftHP, meanTurns);
System.out.println(
"New ATK: "
+ target.getAtk()
+ "/DEF: "
+ target.getDef()
+ "/HP: "
+ target.getBaseHP());
}
// relax convergence criteria for pathological cases
tries++;
if (tries % 200 == 0) {
durationThreshold *= 1.1;
System.out.println(target.getName() + ": changed threshold to " + durationThreshold);
}
}
boolean changed = false;
if (creature.getAtk() != target.getAtk()) {
changed = true;
}
if (creature.getDef() != target.getDef()) {
changed = true;
}
if (creature.getHP() != target.getBaseHP()) {
changed = true;
}
System.out.print("BALANCED: ");
final StringBuilder stringBuilder = new StringBuilder();
stringBuilder.append(creature.getCreatureName());
stringBuilder.append("(");
stringBuilder.append(creature.getLevel());
stringBuilder.append(")\t");
if (changed) {
stringBuilder.append("*\t");
} else {
stringBuilder.append(" \t");
}
stringBuilder.append("ATK: ");
stringBuilder.append(target.getAtk());
stringBuilder.append("\t\tDEF: ");
stringBuilder.append(target.getDef());
stringBuilder.append("\t\tHP: ");
stringBuilder.append(target.getBaseHP());
System.out.println(stringBuilder.toString());
}
}
public void optimize(Declaration declaration) throws XPathException {
Expression exp = compiledFunction.getBody();
ExpressionVisitor visitor = makeExpressionVisitor();
Expression exp2 = exp;
Optimizer opt = getConfiguration().obtainOptimizer();
try {
if (opt.getOptimizationLevel() != Optimizer.NO_OPTIMIZATION) {
exp2 = exp.optimize(visitor, null);
}
} catch (XPathException err) {
err.maybeSetLocation(this);
compileError(err);
}
// Try to extract new global variables from the body of the function
if (opt.getOptimizationLevel() != Optimizer.NO_OPTIMIZATION) {
Expression exp3 = opt.promoteExpressionsToGlobal(exp2, visitor);
if (exp3 != null) {
exp2 = visitor.optimize(exp3, null);
}
}
// Add trace wrapper code if required
exp2 = makeTraceInstruction(this, exp2);
allocateSlots(exp2);
if (exp2 != exp) {
compiledFunction.setBody(exp2);
}
int tailCalls =
ExpressionTool.markTailFunctionCalls(exp2, getObjectName(), getNumberOfArguments());
if (tailCalls != 0) {
compiledFunction.setTailRecursive(tailCalls > 0, tailCalls > 1);
compiledFunction.setBody(new TailCallLoop(compiledFunction));
}
// Generate byte code if appropriate
if (getConfiguration().isGenerateByteCode(Configuration.XSLT)) {
try {
Expression cbody =
opt.compileToByteCode(
compiledFunction.getBody(),
nameAtt,
Expression.PROCESS_METHOD | Expression.ITERATE_METHOD);
if (cbody != null) {
compiledFunction.setBody(cbody);
}
} catch (Exception e) {
System.err.println("Failed while compiling function " + nameAtt);
e.printStackTrace();
throw new XPathException(e);
}
}
compiledFunction.computeEvaluationMode();
if (isExplaining()) {
exp2.explain(getConfiguration().getStandardErrorOutput());
}
}
