Code cleanups and warnings
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/AdaptiveBagging.java b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/AdaptiveBagging.java
index 6680862..b92ab8a 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/AdaptiveBagging.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/AdaptiveBagging.java
@@ -67,9 +67,6 @@
/** The distributor processor. */
private BaggingDistributorProcessor distributorP;
- /** The input streams for the ensemble, one per member. */
- private Stream[] ensembleStreams;
-
/** The result stream. */
protected Stream resultStream;
@@ -117,7 +114,8 @@
}
}
- ensembleStreams = new Stream[ensembleSize];
+ /* The input streams for the ensemble, one per member. */
+ Stream[] ensembleStreams = new Stream[ensembleSize];
for (int i = 0; i < ensembleSize; i++) {
ensembleStreams[i] = builder.createStream(distributorP);
builder.connectInputShuffleStream(ensembleStreams[i], ensemble[i].getInputProcessor()); // connect streams one-to-one with ensemble members (the type of connection does not matter)
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/Boosting.java b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/Boosting.java
index 6512028..eac3d88 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/Boosting.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/ensemble/Boosting.java
@@ -104,9 +104,6 @@
Stream predictionStream = this.builder.createStream(distributorP);
this.builder.connectInputKeyStream(predictionStream, classifier.getInputProcessor());
-// distributorP.setOutputStream(testingStream);
-// distributorP.setPredictionStream(predictionStream);
-
// Addition to Bagging: stream to train
/* The training stream. */
Stream trainingStream = this.builder.createStream(predictionCombinerP);
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/centralized/AMRulesRegressorProcessor.java b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/centralized/AMRulesRegressorProcessor.java
index 55f0064..685e2f9 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/centralized/AMRulesRegressorProcessor.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/centralized/AMRulesRegressorProcessor.java
@@ -163,7 +163,7 @@
int numberOfRulesCovering = 0;
for (ActiveRule rule : ruleSet) {
- if (rule.isCovering(instance) == true) {
+ if (rule.isCovering(instance)) {
numberOfRulesCovering++;
double[] vote = rule.getPrediction(instance);
double error = rule.getCurrentError();
@@ -179,9 +179,8 @@
double error = defaultRule.getCurrentError();
errorWeightedVote.addVote(vote, error);
}
- double[] weightedVote = errorWeightedVote.computeWeightedVote();
- return weightedVote;
+ return errorWeightedVote.computeWeightedVote();
}
public ErrorWeightedVote newErrorWeightedVote() {
@@ -223,13 +222,13 @@
Iterator<ActiveRule> ruleIterator = this.ruleSet.iterator();
while (ruleIterator.hasNext()) {
ActiveRule rule = ruleIterator.next();
- if (rule.isCovering(instance) == true) {
+ if (rule.isCovering(instance)) {
rulesCoveringInstance = true;
- if (isAnomaly(instance, rule) == false) {
+ if (!isAnomaly(instance, rule)) {
// Update Change Detection Tests
double error = rule.computeError(instance); // Use adaptive mode error
boolean changeDetected = ((RuleActiveRegressionNode) rule.getLearningNode()).updateChangeDetection(error);
- if (changeDetected == true) {
+ if (changeDetected) {
ruleIterator.remove();
} else {
rule.updateStatistics(instance);
@@ -245,10 +244,10 @@
}
}
- if (rulesCoveringInstance == false) {
+ if (!rulesCoveringInstance) {
defaultRule.updateStatistics(instance);
if (defaultRule.getInstancesSeen() % this.gracePeriod == 0.0) {
- if (defaultRule.tryToExpand(this.splitConfidence, this.tieThreshold) == true) {
+ if (defaultRule.tryToExpand(this.splitConfidence, this.tieThreshold)) {
ActiveRule newDefaultRule = newRule(defaultRule.getRuleNumberID(),
(RuleActiveRegressionNode) defaultRule.getLearningNode(),
((RuleActiveRegressionNode) defaultRule.getLearningNode()).getStatisticsOtherBranchSplit()); // other branch
@@ -274,7 +273,7 @@
// AMRUles is equipped with anomaly detection. If on, compute the anomaly
// value.
boolean isAnomaly = false;
- if (this.noAnomalyDetection == false) {
+ if (!this.noAnomalyDetection) {
if (rule.getInstancesSeen() >= this.anomalyNumInstThreshold) {
isAnomaly = rule.isAnomaly(instance,
this.univariateAnomalyprobabilityThreshold,
@@ -308,19 +307,19 @@
}
}
}
- if (statistics != null && ((RuleActiveRegressionNode) r.getLearningNode()).getTargetMean() != null)
+ if (statistics != null && (r.getLearningNode()).getTargetMean() != null)
{
double mean;
if (statistics[0] > 0) {
mean = statistics[1] / statistics[0];
- ((RuleActiveRegressionNode) r.getLearningNode()).getTargetMean().reset(mean, (long) statistics[0]);
+ (r.getLearningNode()).getTargetMean().reset(mean, (long) statistics[0]);
}
}
return r;
}
private ActiveRule newRule(int ID) {
- ActiveRule r = new ActiveRule.Builder().
+ return new ActiveRule.Builder().
threshold(this.pageHinckleyThreshold).
alpha(this.pageHinckleyAlpha).
changeDetection(this.driftDetection).
@@ -329,7 +328,6 @@
learningRatio(this.learningRatio).
numericObserver(numericObserver).
id(ID).build();
- return r;
}
/*
@@ -342,7 +340,7 @@
this.ruleNumberID = 0;
this.defaultRule = newRule(++this.ruleNumberID);
- this.ruleSet = new LinkedList<ActiveRule>();
+ this.ruleSet = new LinkedList<>();
}
/*
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/common/ActiveRule.java b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/common/ActiveRule.java
index d233af0..871cdd7 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/common/ActiveRule.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/common/ActiveRule.java
@@ -38,8 +38,6 @@
private static final long serialVersionUID = 1L;
- private double[] statisticsOtherBranchSplit;
-
private Builder builder;
private RuleActiveRegressionNode learningNode;
@@ -89,10 +87,6 @@
this.learningNode = (RuleActiveRegressionNode) learningNode;
}
- public double[] statisticsOtherBranchSplit() {
- return this.statisticsOtherBranchSplit;
- }
-
public RuleSplitNode getLastUpdatedRuleSplitNode() {
return this.lastUpdatedRuleSplitNode;
}
@@ -104,7 +98,6 @@
private static final long serialVersionUID = 1712887264918475622L;
protected boolean changeDetection;
- protected boolean usePerceptron;
protected double threshold;
protected double alpha;
protected int predictionFunction;
@@ -115,8 +108,6 @@
protected FIMTDDNumericAttributeClassLimitObserver numericObserver;
- protected double lastTargetMean;
-
public int id;
public Builder() {
@@ -182,8 +173,7 @@
*/
public boolean tryToExpand(double splitConfidence, double tieThreshold) {
- boolean shouldSplit = this.learningNode.tryToExpand(splitConfidence, tieThreshold);
- return shouldSplit;
+ return this.learningNode.tryToExpand(splitConfidence, tieThreshold);
}
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRLearnerProcessor.java b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRLearnerProcessor.java
index a718945..06a319c 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRLearnerProcessor.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRLearnerProcessor.java
@@ -50,10 +50,7 @@
*/
private static final long serialVersionUID = -2302897295090248013L;
- private static final Logger logger =
- LoggerFactory.getLogger(AMRLearnerProcessor.class);
-
- private int processorId;
+ private static final Logger logger = LoggerFactory.getLogger(AMRLearnerProcessor.class);
private transient List<ActiveRule> ruleSet;
@@ -105,10 +102,10 @@
ActiveRule rule = ruleIterator.next();
if (rule.getRuleNumberID() == ruleID) {
// Check (again) for coverage
- if (rule.isCovering(instance) == true) {
+ if (rule.isCovering(instance)) {
double error = rule.computeError(instance); // Use adaptive mode error
boolean changeDetected = ((RuleActiveRegressionNode) rule.getLearningNode()).updateChangeDetection(error);
- if (changeDetected == true) {
+ if (changeDetected) {
ruleIterator.remove();
this.sendRemoveRuleEvent(ruleID);
@@ -137,7 +134,7 @@
// AMRUles is equipped with anomaly detection. If on, compute the anomaly
// value.
boolean isAnomaly = false;
- if (this.noAnomalyDetection == false) {
+ if (!this.noAnomalyDetection) {
if (rule.getInstancesSeen() >= this.anomalyNumInstThreshold) {
isAnomaly = rule.isAnomaly(instance,
this.univariateAnomalyprobabilityThreshold,
@@ -167,8 +164,7 @@
@Override
public void onCreate(int id) {
- this.processorId = id;
- this.ruleSet = new LinkedList<ActiveRule>();
+ this.ruleSet = new LinkedList<>();
}
@Override
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRulesStatisticsProcessor.java b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRulesStatisticsProcessor.java
index 86fae3c..0b6fa80 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRulesStatisticsProcessor.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/distributed/AMRulesStatisticsProcessor.java
@@ -49,10 +49,7 @@
*/
private static final long serialVersionUID = 5268933189695395573L;
- private static final Logger logger =
- LoggerFactory.getLogger(AMRulesStatisticsProcessor.class);
-
- private int processorId;
+ private static final Logger logger = LoggerFactory.getLogger(AMRulesStatisticsProcessor.class);
private transient List<ActiveRule> ruleSet;
@@ -98,10 +95,10 @@
if (rule.getRuleNumberID() == ruleID) {
// Check (again) for coverage
// Skip anomaly check as Aggregator's perceptron should be well-updated
- if (rule.isCovering(instance) == true) {
+ if (rule.isCovering(instance)) {
double error = rule.computeError(instance); // Use adaptive mode error
boolean changeDetected = ((RuleActiveRegressionNode) rule.getLearningNode()).updateChangeDetection(error);
- if (changeDetected == true) {
+ if (changeDetected) {
ruleIterator.remove();
this.sendRemoveRuleEvent(ruleID);
@@ -143,8 +140,7 @@
@Override
public void onCreate(int id) {
- this.processorId = id;
- this.ruleSet = new LinkedList<ActiveRule>();
+ this.ruleSet = new LinkedList<>();
}
@Override
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/LocalClustererProcessor.java b/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/LocalClustererProcessor.java
index 163184f..c7bb1ad 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/LocalClustererProcessor.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/LocalClustererProcessor.java
@@ -45,8 +45,7 @@
*
*/
private static final long serialVersionUID = -1577910988699148691L;
- private static final Logger logger = LoggerFactory
- .getLogger(LocalClustererProcessor.class);
+ private static final Logger logger = LoggerFactory.getLogger(LocalClustererProcessor.class);
private LocalClustererAdapter model;
private Stream outputStream;
private int modelId;
@@ -84,7 +83,7 @@
* Set the output streams.
*
* @param outputStream
- * the new output stream {@link PredictionCombinerPE}.
+ * the new output stream {@link Stream}.
*/
public void setOutputStream(Stream outputStream) {
diff --git a/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/SingleLearner.java b/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/SingleLearner.java
index f6173f6..e0fa058 100644
--- a/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/SingleLearner.java
+++ b/samoa-api/src/main/java/org/apache/samoa/learners/clusterers/SingleLearner.java
@@ -69,7 +69,7 @@
protected void setLayout() {
learnerP = new LocalClustererProcessor();
- LocalClustererAdapter learner = (LocalClustererAdapter) this.learnerOption.getValue();
+ LocalClustererAdapter learner = this.learnerOption.getValue();
learner.setDataset(this.dataset);
learnerP.setLearner(learner);
@@ -96,7 +96,6 @@
*/
@Override
public Set<Stream> getResultStreams() {
- Set<Stream> streams = ImmutableSet.of(this.resultStream);
- return streams;
+ return ImmutableSet.of(this.resultStream);
}
}
diff --git a/samoa-api/src/main/java/org/apache/samoa/moa/cluster/Miniball.java b/samoa-api/src/main/java/org/apache/samoa/moa/cluster/Miniball.java
index da2a0e5..3dcdc5f 100644
--- a/samoa-api/src/main/java/org/apache/samoa/moa/cluster/Miniball.java
+++ b/samoa-api/src/main/java/org/apache/samoa/moa/cluster/Miniball.java
@@ -20,7 +20,6 @@
* #L%
*/
-import com.dreizak.miniball.model.ArrayPointSet;
import com.dreizak.miniball.model.PointSet;
import java.util.ArrayList;
import java.util.List;
@@ -62,7 +61,7 @@
public PointStorage(int dimension) {
this.dimension = dimension;
- this.L = new ArrayList<double[]>();
+ this.L = new ArrayList<>();
}
public void add(double[] array) {
diff --git a/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/AbstractClusterer.java b/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/AbstractClusterer.java
index 02a5191..da77d04 100644
--- a/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/AbstractClusterer.java
+++ b/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/AbstractClusterer.java
@@ -20,6 +20,7 @@
* #L%
*/
+import java.util.Collections;
import java.util.LinkedList;
import java.util.List;
import java.util.Random;
@@ -134,21 +135,19 @@
}
public Measurement[] getModelMeasurements() {
- List<Measurement> measurementList = new LinkedList<Measurement>();
+ List<Measurement> measurementList = new LinkedList<>();
measurementList.add(new Measurement("model training instances",
trainingWeightSeenByModel()));
measurementList.add(new Measurement("model serialized size (bytes)",
measureByteSize()));
Measurement[] modelMeasurements = getModelMeasurementsImpl();
if (modelMeasurements != null) {
- for (Measurement measurement : modelMeasurements) {
- measurementList.add(measurement);
- }
+ Collections.addAll(measurementList, modelMeasurements);
}
// add average of sub-model measurements
Clusterer[] subModels = getSubClusterers();
if ((subModels != null) && (subModels.length > 0)) {
- List<Measurement[]> subMeasurements = new LinkedList<Measurement[]>();
+ List<Measurement[]> subMeasurements = new LinkedList<>();
for (Clusterer subModel : subModels) {
if (subModel != null) {
subMeasurements.add(subModel.getModelMeasurements());
@@ -157,9 +156,7 @@
Measurement[] avgMeasurements = Measurement
.averageMeasurements(subMeasurements
.toArray(new Measurement[subMeasurements.size()][]));
- for (Measurement measurement : avgMeasurements) {
- measurementList.add(measurement);
- }
+ Collections.addAll(measurementList, avgMeasurements);
}
return measurementList.toArray(new Measurement[measurementList.size()]);
}
@@ -295,5 +292,5 @@
public Clustering getMicroClusteringResult() {
return null;
- };
+ }
}
diff --git a/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/ClusterGenerator.java b/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/ClusterGenerator.java
index b9f80b5..06c9cff 100644
--- a/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/ClusterGenerator.java
+++ b/samoa-api/src/main/java/org/apache/samoa/moa/clusterers/ClusterGenerator.java
@@ -58,7 +58,6 @@
public FloatOption clusterAddOption = new FloatOption("clusterAdd", 'A',
"Adds additional clusters.", 0, 0, 1);
- private static double err_intervall_width = 0.0;
private ArrayList<DataPoint> points;
private int instanceCounter;
private int windowCounter;
@@ -67,7 +66,7 @@
@Override
public void resetLearningImpl() {
- points = new ArrayList<DataPoint>();
+ points = new ArrayList<>();
instanceCounter = 0;
windowCounter = 0;
random = new Random(227);
@@ -169,8 +168,9 @@
double radius = sourceCluster.getRadius();
// move cluster center
+ double err_interval_width = 0.0;
if (errLevelPosition > 0) {
- double errOffset = random.nextDouble() * err_intervall_width / 2.0;
+ double errOffset = random.nextDouble() * err_interval_width / 2.0;
double errOffsetDirection = ((random.nextBoolean()) ? 1 : -1);
double level = errLevelPosition + errOffsetDirection * errOffset;
double[] vector = new double[center.length];
@@ -203,20 +203,15 @@
}
center = newCenter;
for (int d = 0; d < center.length; d++) {
- if (newCenter[d] >= 0 && newCenter[d] <= 1) {
- }
- else {
- System.out
- .println("This shouldnt have happend, Cluster center out of bounds:" + Arrays.toString(newCenter));
+ if (newCenter[d] < 0 || newCenter[d] > 1) {
+ System.out.println("This shouldnt have happend, Cluster center out of bounds:" + Arrays.toString(newCenter));
}
}
- // System.out.println("new Center "+Arrays.toString(newCenter));
-
}
// alter radius
if (errLevelRadiusDecrease > 0 || errLevelRadiusIncrease > 0) {
- double errOffset = random.nextDouble() * err_intervall_width / 2.0;
+ double errOffset = random.nextDouble() * err_interval_width / 2.0;
int errOffsetDirection = ((random.nextBoolean()) ? 1 : -1);
if (errLevelRadiusDecrease > 0 && (errLevelRadiusIncrease == 0 || random.nextBoolean())) {
@@ -289,9 +284,7 @@
for (int c1 = 0; c1 < clustering.size(); c1++) {
SphereCluster sc1 = (SphereCluster) clustering.get(c1);
double minDist = Double.MAX_VALUE;
- double minOver = 1;
- int maxindexCon = -1;
- int maxindexOver = -1;
+ int maxIndexCon = -1;
for (int c2 = 0; c2 < clustering.size(); c2++) {
SphereCluster sc2 = (SphereCluster) clustering.get(c2);
// double over = sc1.overlapRadiusDegree(sc2);
@@ -303,14 +296,11 @@
double threshold = Math.min(sc1.getRadius(), sc2.getRadius()) * radiusFactor;
if (dist > 0 && dist < minDist && dist < threshold) {
minDist = dist;
- maxindexCon = c2;
+ maxIndexCon = c2;
}
}
- int maxindex = -1;
- if (maxindexOver != -1)
- maxindex = maxindexOver;
- else
- maxindex = maxindexCon;
+ int maxindex;
+ maxindex = maxIndexCon;
if (maxindex != -1 && !merged[c1]) {
merged[c1] = true;
diff --git a/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningCurve.java b/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningCurve.java
index dcc4f50..e4bdb82 100644
--- a/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningCurve.java
+++ b/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningCurve.java
@@ -39,11 +39,11 @@
private static final long serialVersionUID = 1L;
- protected List<String> measurementNames = new ArrayList<String>();
+ protected List<String> measurementNames = new ArrayList<>();
- protected List<String> voteNames = new ArrayList<String>();
+ protected List<String> voteNames = new ArrayList<>();
- protected List<double[]> measurementValues = new ArrayList<double[]>();
+ protected List<double[]> measurementValues = new ArrayList<>();
protected List<String> voteValues = new ArrayList<String>();
@@ -154,7 +154,7 @@
/**
* This method is used to set generate header line of a text file containing predictions and votes (for classification
* only)
- *
+ *
* @return String This returns the text of the header of a file containing predictions and votes.
*/
public String voteHeaderToString() {
@@ -174,7 +174,7 @@
/**
* This method is used to set generate one body line of a text file containing predictions and votes (for
* classification only)
- *
+ *
* @return String This returns the text of one line of a file containing predictions and votes.
*/
public String voteEntryToString() {
diff --git a/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningEvaluation.java b/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningEvaluation.java
index 993667d..3389fda 100644
--- a/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningEvaluation.java
+++ b/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/LearningEvaluation.java
@@ -46,7 +46,7 @@
public LearningEvaluation(Measurement[] evaluationMeasurements,
LearningPerformanceEvaluator cpe, Learner model) {
- List<Measurement> measurementList = new LinkedList<Measurement>();
+ List<Measurement> measurementList = new LinkedList<>();
measurementList.addAll(Arrays.asList(evaluationMeasurements));
measurementList.addAll(Arrays.asList(cpe.getPerformanceMeasurements()));
measurementList.addAll(Arrays.asList(model.getModelMeasurements()));
diff --git a/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/MembershipMatrix.java b/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/MembershipMatrix.java
index 4387c04..3510b4d 100644
--- a/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/MembershipMatrix.java
+++ b/samoa-api/src/main/java/org/apache/samoa/moa/evaluation/MembershipMatrix.java
@@ -35,7 +35,7 @@
int total_entries;
int class_distribution[];
int total_class_entries;
- int initalBuildTimestamp = -1;
+ int initialBuildTimestamp = -1;
public MembershipMatrix(Clustering foundClustering, ArrayList<DataPoint> points) {
classmap = Clustering.classValues(points);
@@ -50,13 +50,13 @@
class_sums = new int[numClasses];
total_entries = 0;
total_class_entries = points.size();
- for (int p = 0; p < points.size(); p++) {
- int worklabel = classmap.get((int) points.get(p).classValue());
+ for (DataPoint point : points) {
+ int worklabel = classmap.get((int) point.classValue());
// real class distribution
class_distribution[worklabel]++;
boolean covered = false;
for (int c = 0; c < numCluster - 1; c++) {
- double prob = foundClustering.get(c).getInclusionProbability(points.get(p));
+ double prob = foundClustering.get(c).getInclusionProbability(point);
if (prob >= 1) {
cluster_class_weights[c][worklabel]++;
class_sums[worklabel]++;
@@ -74,7 +74,7 @@
}
- initalBuildTimestamp = points.get(0).getTimestamp();
+ initialBuildTimestamp = points.get(0).getTimestamp();
}
public int getClusterClassWeight(int i, int j) {
@@ -119,7 +119,7 @@
@Override
public String toString() {
- StringBuffer sb = new StringBuffer();
+ StringBuilder sb = new StringBuilder();
sb.append("Membership Matrix\n");
for (int i = 0; i < cluster_class_weights.length; i++) {
for (int j = 0; j < cluster_class_weights[i].length; j++) {
@@ -128,22 +128,22 @@
sb.append("| " + cluster_sums[i] + "\n");
}
// sb.append("-----------\n");
- for (int i = 0; i < class_sums.length; i++) {
- sb.append(class_sums[i] + "\t ");
+ for (int class_sum : class_sums) {
+ sb.append(class_sum + "\t ");
}
sb.append("| " + total_entries + "\n");
sb.append("Real class distribution \n");
- for (int i = 0; i < class_distribution.length; i++) {
- sb.append(class_distribution[i] + "\t ");
+ for (int aClass_distribution : class_distribution) {
+ sb.append(aClass_distribution + "\t ");
}
sb.append("| " + total_class_entries + "\n");
return sb.toString();
}
- public int getInitalBuildTimestamp() {
- return initalBuildTimestamp;
+ public int getInitialBuildTimestamp() {
+ return initialBuildTimestamp;
}
}
diff --git a/samoa-api/src/main/java/org/apache/samoa/streams/clustering/RandomRBFGeneratorEvents.java b/samoa-api/src/main/java/org/apache/samoa/streams/clustering/RandomRBFGeneratorEvents.java
index 139b8f7..5fe70ea 100644
--- a/samoa-api/src/main/java/org/apache/samoa/streams/clustering/RandomRBFGeneratorEvents.java
+++ b/samoa-api/src/main/java/org/apache/samoa/streams/clustering/RandomRBFGeneratorEvents.java
@@ -37,7 +37,6 @@
import org.apache.samoa.moa.cluster.SphereCluster;
import org.apache.samoa.moa.core.AutoExpandVector;
import org.apache.samoa.moa.core.DataPoint;
-import org.apache.samoa.moa.core.FastVector;
import org.apache.samoa.moa.core.InstanceExample;
import org.apache.samoa.moa.core.ObjectRepository;
import org.apache.samoa.moa.tasks.TaskMonitor;
@@ -48,7 +47,7 @@
import com.github.javacliparser.IntOption;
public class RandomRBFGeneratorEvents extends ClusteringStream {
- private transient Vector listeners;
+ private transient Vector<ClusterEventListener> listeners;
private static final long serialVersionUID = 1L;
@@ -135,10 +134,10 @@
int currentMovementSteps;
boolean isSplitting = false;
- LinkedList<DataPoint> points = new LinkedList<DataPoint>();
- ArrayList<SphereCluster> microClusters = new ArrayList<SphereCluster>();
- ArrayList<ArrayList<DataPoint>> microClustersPoints = new ArrayList();
- ArrayList<Integer> microClustersDecay = new ArrayList();
+ LinkedList<DataPoint> points = new LinkedList<>();
+ ArrayList<SphereCluster> microClusters = new ArrayList<>();
+ ArrayList<ArrayList<DataPoint>> microClustersPoints = new ArrayList<>();
+ ArrayList<Integer> microClustersDecay = new ArrayList<>();
public GeneratorCluster(int label) {
boolean outofbounds = true;
@@ -230,8 +229,7 @@
int minMicroIndex = -1;
double minHullDist = Double.MAX_VALUE;
boolean inserted = false;
- // we favour more recently build clusters so we can remove earlier cluster
- // sooner
+ // we favour more recently build clusters so we can remove earlier cluster sooner
for (int m = microClusters.size() - 1; m >= 0; m--) {
SphereCluster micro = microClusters.get(m);
double hulldist = micro.getCenterDistance(point) - micro.getRadius();
@@ -251,49 +249,25 @@
}
}
// Reseting index choice for alternative cluster building
- int alt = 1;
- if (alt == 1)
- minMicroIndex = -1;
if (!inserted) {
// add to closest cluster and expand cluster
- if (minMicroIndex != -1) {
- microClustersPoints.get(minMicroIndex).add(point);
- // we should keep the miniball instances and just check in
- // new points instead of rebuilding the whole thing
- SphereCluster s = new SphereCluster(microClustersPoints.get(minMicroIndex), numAttsOption.getValue());
- // check if current microcluster is bigger then generating cluster
- if (s.getRadius() > generator.getRadius()) {
- // remove previously added point
- microClustersPoints.get(minMicroIndex).remove(microClustersPoints.get(minMicroIndex).size() - 1);
- minMicroIndex = -1;
- }
- else {
- microClusters.set(minMicroIndex, s);
- microClustersDecay.set(minMicroIndex, numGeneratedInstances);
- }
- }
// minMicroIndex might have been reset above
// create new micro cluster
- if (minMicroIndex == -1) {
- ArrayList<DataPoint> microPoints = new ArrayList<DataPoint>();
- microPoints.add(point);
- SphereCluster s;
- if (alt == 0)
- s = new SphereCluster(microPoints, numAttsOption.getValue());
- else
- s = new SphereCluster(generator.getCenter(), generator.getRadius(), 1);
+ ArrayList<DataPoint> microPoints = new ArrayList<>();
+ microPoints.add(point);
+ SphereCluster s;
+ s = new SphereCluster(generator.getCenter(), generator.getRadius(), 1);
- microClusters.add(s);
- microClustersPoints.add(microPoints);
- microClustersDecay.add(numGeneratedInstances);
- int id = 0;
- while (id < kernels.size()) {
- if (kernels.get(id) == this)
- break;
- id++;
- }
- s.setGroundTruth(id);
+ microClusters.add(s);
+ microClustersPoints.add(microPoints);
+ microClustersDecay.add(numGeneratedInstances);
+ int id = 0;
+ while (id < kernels.size()) {
+ if (kernels.get(id) == this)
+ break;
+ id++;
}
+ s.setGroundTruth(id);
}
}
@@ -301,10 +275,7 @@
private void move() {
if (currentMovementSteps < totalMovementSteps) {
currentMovementSteps++;
- if (moveVector == null) {
- return;
- }
- else {
+ if (moveVector != null) {
double[] center = generator.getCenter();
boolean outofbounds = true;
while (outofbounds) {
@@ -426,24 +397,17 @@
double radius = kernelRadiiOption.getValue();
double avgWeight = 1.0 / numClusterOption.getValue();
double weight = avgWeight + avgWeight * densityRangeOption.getValue() * instanceRandom.nextDouble();
- SphereCluster spcluster = null;
+ SphereCluster spcluster;
double[] center = generator.getCenter();
spcluster = new SphereCluster(center, radius, weight);
- if (spcluster != null) {
- GeneratorCluster gc = new GeneratorCluster(clusterIdCounter++, spcluster);
- gc.isSplitting = true;
- kernels.add(gc);
- normalizeWeights();
- numActiveKernels++;
- return "Split from Kernel " + generator.getId();
- }
- else {
- System.out.println("Tried to split new kernel from C" + generator.getId() +
- ". Not enough room for new cluster, decrease average radii, number of clusters or enable overlap.");
- return "";
- }
+ GeneratorCluster gc = new GeneratorCluster(clusterIdCounter++, spcluster);
+ gc.isSplitting = true;
+ kernels.add(gc);
+ normalizeWeights();
+ numActiveKernels++;
+ return "Split from Kernel " + generator.getId();
}
private String fadeOut() {
@@ -493,18 +457,18 @@
numGeneratedInstances = 0;
clusterIdCounter = 0;
mergeClusterA = mergeClusterB = null;
- kernels = new AutoExpandVector<GeneratorCluster>();
+ kernels = new AutoExpandVector<>();
initKernels();
}
protected void generateHeader() { // 2013/06/02: Noise label
- ArrayList<Attribute> attributes = new ArrayList<Attribute>();
+ ArrayList<Attribute> attributes = new ArrayList<>();
for (int i = 0; i < this.numAttsOption.getValue(); i++) {
attributes.add(new Attribute("att" + (i + 1)));
}
- ArrayList<String> classLabels = new ArrayList<String>();
+ ArrayList<String> classLabels = new ArrayList<>();
for (int i = 0; i < this.numClusterOption.getValue(); i++) {
classLabels.add("class" + (i + 1));
}
@@ -531,7 +495,7 @@
// make room for the classlabel
double[] values_new = new double[numAttsOption.getValue()]; // +1
- double[] values = null;
+ double[] values;
int clusterChoice = -1;
if (instanceRandom.nextDouble() > noiseLevelOption.getValue()) {
@@ -539,7 +503,7 @@
values = kernels.get(clusterChoice).generator.sample(instanceRandom).toDoubleArray();
}
else {
- // get ranodm noise point
+ // get random noise point
values = getNoisePoint();
}
@@ -569,8 +533,8 @@
public Clustering getGeneratingClusters() {
Clustering clustering = new Clustering();
- for (int c = 0; c < kernels.size(); c++) {
- clustering.add(kernels.get(c).generator);
+ for (GeneratorCluster kernel : kernels) {
+ clustering.add(kernel.generator);
}
return clustering;
}
@@ -579,11 +543,11 @@
Clustering clustering = new Clustering();
int id = 0;
- for (int c = 0; c < kernels.size(); c++) {
- for (int m = 0; m < kernels.get(c).microClusters.size(); m++) {
- kernels.get(c).microClusters.get(m).setId(id);
- kernels.get(c).microClusters.get(m).setGroundTruth(kernels.get(c).generator.getId());
- clustering.add(kernels.get(c).microClusters.get(m));
+ for (GeneratorCluster kernel : kernels) {
+ for (int m = 0; m < kernel.microClusters.size(); m++) {
+ kernel.microClusters.get(m).setId(id);
+ kernel.microClusters.get(m).setGroundTruth(kernel.generator.getId());
+ clustering.add(kernel.microClusters.get(m));
id++;
}
}
@@ -595,8 +559,8 @@
/**************************** EVENTS ******************************************/
private void eventScheduler() {
- for (int i = 0; i < kernels.size(); i++) {
- kernels.get(i).updateKernel();
+ for (GeneratorCluster kernel : kernels) {
+ kernel.updateKernel();
}
nextEventCounter--;
@@ -604,8 +568,8 @@
// should this be randomized as well???
if (nextEventCounter % kernelMovePointFrequency == 0) {
// move kernels
- for (int i = 0; i < kernels.size(); i++) {
- kernels.get(i).move();
+ for (GeneratorCluster kernel : kernels) {
+ kernel.move();
// overlapControl();
}
}
@@ -715,8 +679,7 @@
while (kernels.get(id).kill != -1)
id = instanceRandom.nextInt(kernels.size());
- String message = kernels.get(id).fadeOut();
- return message;
+ return kernels.get(id).fadeOut();
}
private String fadeIn() {
@@ -782,9 +745,7 @@
while (kernels.get(id).kill != -1)
id = instanceRandom.nextInt(kernels.size());
- String message = kernels.get(id).splitKernel();
-
- return message;
+ return kernels.get(id).splitKernel();
}
private String mergeKernels(int steps) {
@@ -796,10 +757,7 @@
// System.out.println("DisredDist:"+(2*diseredDist));
for (int i = 0; i < kernels.size(); i++) {
for (int j = 0; j < i; j++) {
- if (kernels.get(i).kill != -1 || kernels.get(j).kill != -1) {
- continue;
- }
- else {
+ if (kernels.get(i).kill == -1 && kernels.get(j).kill == -1) {
double kernelDist = kernels.get(i).generator.getCenterDistance(kernels.get(j).generator);
double d = kernelDist - 2 * diseredDist;
// System.out.println("Dist:"+i+" / "+j+" "+d);
@@ -866,10 +824,10 @@
incluster = false;
if (!noiseInClusterOption.isSet() && counter > 0) {
counter--;
- for (int c = 0; c < kernels.size(); c++) {
- for (int m = 0; m < kernels.get(c).microClusters.size(); m++) {
+ for (GeneratorCluster kernel : kernels) {
+ for (int m = 0; m < kernel.microClusters.size(); m++) {
Instance inst = new DenseInstance(1, sample);
- if (kernels.get(c).microClusters.get(m).getInclusionProbability(inst) > 0) {
+ if (kernel.microClusters.get(m).getInclusionProbability(inst) > 0) {
incluster = true;
break;
}
@@ -904,11 +862,11 @@
private void normalizeWeights() {
double sumWeights = 0.0;
- for (int i = 0; i < kernels.size(); i++) {
- sumWeights += kernels.get(i).generator.getWeight();
+ for (GeneratorCluster kernel : kernels) {
+ sumWeights += kernel.generator.getWeight();
}
- for (int i = 0; i < kernels.size(); i++) {
- kernels.get(i).generator.setWeight(kernels.get(i).generator.getWeight() / sumWeights);
+ for (GeneratorCluster kernel : kernels) {
+ kernel.generator.setWeight(kernel.generator.getWeight() / sumWeights);
}
}
@@ -919,14 +877,14 @@
/** Add a listener */
synchronized public void addClusterChangeListener(ClusterEventListener l) {
if (listeners == null)
- listeners = new Vector();
+ listeners = new Vector<>();
listeners.addElement(l);
}
/** Remove a listener */
synchronized public void removeClusterChangeListener(ClusterEventListener l) {
if (listeners == null)
- listeners = new Vector();
+ listeners = new Vector<>();
listeners.removeElement(l);
}
@@ -940,9 +898,9 @@
// make a copy of the listener list in case
// anyone adds/removes listeners
- Vector targets;
+ Vector<ClusterEventListener> targets;
synchronized (this) {
- targets = (Vector) listeners.clone();
+ targets = (Vector<ClusterEventListener>) listeners.clone();
}
// walk through the listener list and
diff --git a/samoa-api/src/main/java/org/apache/samoa/streams/fs/HDFSFileStreamSource.java b/samoa-api/src/main/java/org/apache/samoa/streams/fs/HDFSFileStreamSource.java
index 67d5e79..07050eb 100644
--- a/samoa-api/src/main/java/org/apache/samoa/streams/fs/HDFSFileStreamSource.java
+++ b/samoa-api/src/main/java/org/apache/samoa/streams/fs/HDFSFileStreamSource.java
@@ -40,7 +40,7 @@
public class HDFSFileStreamSource implements FileStreamSource {
/**
- *
+ *
*/
private static final long serialVersionUID = -3887354805787167400L;
@@ -63,7 +63,7 @@
org.apache.hadoop.hdfs.DistributedFileSystem.class.getName());
config.set("fs.file.impl",
org.apache.hadoop.fs.LocalFileSystem.class.getName());
- this.filePaths = new ArrayList<String>();
+ this.filePaths = new ArrayList<>();
Path hdfsPath = new Path(path);
FileSystem fs;
try {
@@ -72,14 +72,14 @@
if (fileStat.isDirectory()) {
Path filterPath = hdfsPath;
if (ext != null) {
- filterPath = new Path(path.toString(), "*." + ext);
+ filterPath = new Path(path, "*." + ext);
} else {
- filterPath = new Path(path.toString(), "*");
+ filterPath = new Path(path, "*");
}
FileStatus[] filesInDir = fs.globStatus(filterPath);
- for (int i = 0; i < filesInDir.length; i++) {
- if (filesInDir[i].isFile()) {
- filePaths.add(filesInDir[i].getPath().toString());
+ for (FileStatus aFilesInDir : filesInDir) {
+ if (aFilesInDir.isFile()) {
+ filePaths.add(aFilesInDir.getPath().toString());
}
}
} else {
diff --git a/samoa-api/src/main/java/org/apache/samoa/streams/fs/LocalFileStreamSource.java b/samoa-api/src/main/java/org/apache/samoa/streams/fs/LocalFileStreamSource.java
index 129d247..addd232 100644
--- a/samoa-api/src/main/java/org/apache/samoa/streams/fs/LocalFileStreamSource.java
+++ b/samoa-api/src/main/java/org/apache/samoa/streams/fs/LocalFileStreamSource.java
@@ -25,7 +25,6 @@
import java.io.FilenameFilter;
import java.io.IOException;
import java.io.InputStream;
-import java.nio.file.FileSystems;
import java.util.ArrayList;
import java.util.List;
@@ -49,12 +48,12 @@
}
public void init(String path, String ext) {
- this.filePaths = new ArrayList<String>();
+ this.filePaths = new ArrayList<>();
File fileAtPath = new File(path);
if (fileAtPath.isDirectory()) {
File[] filesInDir = fileAtPath.listFiles(new FileExtensionFilter(ext));
- for (int i = 0; i < filesInDir.length; i++) {
- filePaths.add(filesInDir[i].getAbsolutePath());
+ for (File aFilesInDir : filesInDir) {
+ filePaths.add(aFilesInDir.getAbsolutePath());
}
}
else {
diff --git a/samoa-api/src/main/java/org/apache/samoa/streams/generators/HyperplaneGenerator.java b/samoa-api/src/main/java/org/apache/samoa/streams/generators/HyperplaneGenerator.java
index 8274040..3ac68ce 100644
--- a/samoa-api/src/main/java/org/apache/samoa/streams/generators/HyperplaneGenerator.java
+++ b/samoa-api/src/main/java/org/apache/samoa/streams/generators/HyperplaneGenerator.java
@@ -83,8 +83,6 @@
protected int[] sigma;
- public int numberInstance;
-
@Override
protected void prepareForUseImpl(TaskMonitor monitor, ObjectRepository repository) {
monitor.setCurrentActivity("Preparing hyperplane...", -1.0);
@@ -160,7 +158,7 @@
private void addDrift() {
for (int i = 0; i < this.numDriftAttsOption.getValue(); i++) {
- this.weights[i] += (double) ((double) sigma[i]) * ((double) this.magChangeOption.getValue());
+ this.weights[i] += ((double) sigma[i]) * this.magChangeOption.getValue();
if (// this.weights[i] >= 1.0 || this.weights[i] <= 0.0 ||
(1 + (this.instanceRandom.nextInt(100))) <= this.sigmaPercentageOption.getValue()) {
this.sigma[i] *= -1;
diff --git a/samoa-local/src/test/java/org/apache/samoa/AlgosTest.java b/samoa-local/src/test/java/org/apache/samoa/AlgosTest.java
index f621aba..38099a8 100644
--- a/samoa-local/src/test/java/org/apache/samoa/AlgosTest.java
+++ b/samoa-local/src/test/java/org/apache/samoa/AlgosTest.java
@@ -20,7 +20,6 @@
* #L%
*/
-import org.apache.samoa.LocalDoTask;
import org.junit.Test;
import org.apache.samoa.TestParams;
