本文整理汇总了Java中org.deckfour.xes.model.XLog.clear方法的典型用法代码示例。如果您正苦于以下问题：Java XLog.clear方法的具体用法？Java XLog.clear怎么用？Java XLog.clear使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.deckfour.xes.model.XLog的用法示例。
在下文中一共展示了XLog.clear方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: generateNewLog
import org.deckfour.xes.model.XLog; //导入方法依赖的package包/类
@Override
public XLog generateNewLog(XLog log, OutlierIdentifierGenerator<String> outlierIdentifierGenerator, int lookAHead, boolean selectOnlyOneOutlier) {
boolean outlearsFound = false;
if(mapOutliers.size() > 0) {
outlearsFound = true;
}
if(outlearsFound) {
XLog newLog = (XLog) log.clone();
newLog.clear();
for (XTrace t : log) {
XTrace newT = (XTrace) t.clone();
newT.clear();
newT.add((XEvent) t.get(0).clone());
for (int i = 1; i < t.size() - 1; i++) {
if(selectOnlyOneOutlier) {
removeOutlierSelectOnlyOne(t, newT, i);
}else {
removeOutlierSelect(t, newT, i);
}
}
newT.add((XEvent) t.get(t.size()-1).clone());
if(newT.size() > 0) newLog.add(newT);
}
return newLog;
}else {
return log;
}
}
示例2: generateNewLog
import org.deckfour.xes.model.XLog; //导入方法依赖的package包/类
@Override
public XLog generateNewLog(XLog log, OutlierIdentifierGenerator<String> outlierIdentifierGenerator, int lookAHead, boolean selectOnlyOneOutlier) {
boolean outlearsFound = false;
if(mapOutliers.size() > 0) {
outlearsFound = true;
}
if(outlearsFound) {
XLog newLog = (XLog) log.clone();
newLog.clear();
for (XTrace t : log) {
XTrace newT = (XTrace) t.clone();
newT.clear();
for (int i = 0; i < lookAHead && i < t.size(); i++) {
XEvent current = (XEvent) t.get(i).clone();
newT.add(current);
}
for (int i = lookAHead; i < t.size(); i++) {
if(selectOnlyOneOutlier) {
removeOutlierSelectOnlyOne(t, newT, i, lookAHead, true);
}else {
removeOutlierSelect(t, newT, i, lookAHead, true);
}
}
if(newT.size() > 0) newLog.add(newT);
}
return newLog;
}else {
return log;
}
}
示例3: generateNewLogReverse
import org.deckfour.xes.model.XLog; //导入方法依赖的package包/类
@Override
public XLog generateNewLogReverse(XLog log, OutlierIdentifierGenerator<String> outlierIdentifierGenerator, int lookAHead, boolean selectOnlyOneOutlier) {
boolean outlearsFound = false;
if(mapOutliers.size() > 0) {
outlearsFound = true;
}
if(outlearsFound) {
XLog newLog = (XLog) log.clone();
newLog.clear();
for (XTrace t : log) {
XTrace newT = (XTrace) t.clone();
newT.clear();
for (int i = t.size() - 1; i >= t.size() - lookAHead && i >= 0; i--) {
XEvent current = (XEvent) t.get(i).clone();
newT.add(current);
}
for (int i = t.size() - lookAHead - 1; i >= 0; i--) {
if(selectOnlyOneOutlier) {
removeOutlierSelectOnlyOne(t, newT, i, lookAHead, true);
}else {
removeOutlierSelect(t, newT, i, lookAHead, true);
}
}
if(newT.size() > 0) newLog.add(newT);
}
return newLog;
}else {
return log;
}
}
示例4: filterLog
import org.deckfour.xes.model.XLog; //导入方法依赖的package包/类
public XLog filterLog(XLog rawlog) {
XLog log = rawlog;
XFactory factory = new XFactoryNaiveImpl();
LogOptimizer logOptimizer = new LogOptimizer();
log = logOptimizer.optimizeLog(log);
LogModifier logModifier = new LogModifier(factory, XConceptExtension.instance(), XTimeExtension.instance(), logOptimizer);
logModifier.insertArtificialStartAndEndEvent(log);
Automaton<String> automatonOriginal = automatonFactory.generate(log);
Automaton<String> lastAutomaton = null;
Automaton<String> automaton;
double[] arcs = discoverArcs(automatonOriginal, 1.0);
double noiseThreshold = discoverThreshold(arcs, 0.125);
Set<Node<String>> requiredStates = automatonOriginal.getNodes();
double lowerbound = 0.0;
double upperbound = noiseThreshold;
XLog log2 = rawlog;
int events;
int newEvents = countEvents(log2);
UIPluginContext context = new FakePluginContext();
do {
automaton = getFilteredAutomaton(automatonOriginal, requiredStates, noiseThreshold);
if (lastAutomaton == null || !automaton.equals(lastAutomaton)) {
try {
finalLog = AutomatonInfrequentBehaviourRemover.removeInfrequentBehaviour(context, xEventClassifier, log, automaton, lowerbound, upperbound, true, true);
finalThreshold = noiseThreshold;
} catch (HighThresholdException e) {
noiseThreshold = roundNumber(findBestUpperbound(context, log, requiredStates, upperbound/2, upperbound, true));
}
}
if(finalThreshold == noiseThreshold && finalLog != null) {
log2 = finalLog;
}else {
try {
automaton = getFilteredAutomaton(automatonOriginal, requiredStates, noiseThreshold);
log2 = AutomatonInfrequentBehaviourRemover.removeInfrequentBehaviour(context, xEventClassifier, log, automaton, 0, noiseThreshold, true, true);
} catch (HighThresholdException hte) {
log.clear();
return log;
}
}
events = newEvents;
newEvents = countEvents(log2);
}while (newEvents < events);
logModifier.removeArtificialStartAndEndEvent(log2);
return log2;
}