eclipse-sailing-analytics/sailing-analytics
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changed from one-dimensional clustering along middle COG to two-dimensional clustering (middle COG / maneuver angle) and starting first tests with this approach

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Axel Uhl committed 2015-01-23 17:29:54 +01:00
1 parent ae16bbc0ba
commit eb8c8b2537
9 files changed
+349 -161
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java/com.sap.sailing.domain.common/src/com/sap/sailing/domain/common/confidence/ConfidenceBasedAverager.java
+5
View File
@@ -1,5 +1,7 @@
package com.sap.sailing.domain.common.confidence;
import java.util.Iterator;
public interface ConfidenceBasedAverager<ValueType, BaseType, RelativeTo> {
/**
* If a non-<code>null</code> weigher has been set for this averager, <code>at</code> must be a valid reference
@@ -15,4 +17,7 @@ public interface ConfidenceBasedAverager<ValueType, BaseType, RelativeTo> {
*/
HasConfidence<ValueType, BaseType, RelativeTo> getAverage(
Iterable<? extends HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo>> values, RelativeTo at);
HasConfidence<ValueType, BaseType, RelativeTo> getAverage(
Iterator<? extends HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo>> values, RelativeTo at);
}
java/com.sap.sailing.domain.common/src/com/sap/sailing/domain/common/confidence/impl/ConfidenceBasedAveragerImpl.java
+20 -6
View File
@@ -1,10 +1,11 @@
package com.sap.sailing.domain.common.confidence.impl;
import java.util.Iterator;
import com.sap.sailing.domain.common.confidence.ConfidenceBasedAverager;
import com.sap.sailing.domain.common.confidence.HasConfidence;
import com.sap.sailing.domain.common.confidence.HasConfidenceAndIsScalable;
import com.sap.sailing.domain.common.confidence.Weigher;
import com.sap.sse.common.Util;
import com.sap.sse.common.scalablevalue.ScalableValue;
@@ -45,13 +46,21 @@ public class ConfidenceBasedAveragerImpl<ValueType, BaseType, RelativeTo> implem
@Override
public HasConfidence<ValueType, BaseType, RelativeTo> getAverage(
Iterable<? extends HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo>> values, RelativeTo at) {
if (values == null || Util.isEmpty(values)) {
return getAverage(values.iterator(), at);
}
@Override
public HasConfidence<ValueType, BaseType, RelativeTo> getAverage(
Iterator<? extends HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo>> values, RelativeTo at) {
if (values == null || !values.hasNext()) {
return null;
} else {
ScalableValue<ValueType, BaseType> numerator = null;
double confidenceSum = 0;
for (HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo> next : values) {
double relativeWeight = (getWeigher() == null ? 1.0 : getWeigher().getConfidence(next.getRelativeTo(), at)) * next.getConfidence();
int count = 0;
while (values.hasNext()) {
HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo> next = values.next();
double relativeWeight = getWeight(next, at);
ScalableValue<ValueType, BaseType> weightedNext = next.getScalableValue().multiply(relativeWeight);
if (numerator == null) {
numerator = weightedNext;
@@ -59,15 +68,20 @@ public class ConfidenceBasedAveragerImpl<ValueType, BaseType, RelativeTo> implem
numerator = numerator.add(weightedNext);
}
confidenceSum += relativeWeight;
count++;
}
// TODO consider greater variance to reduce the confidence
double newConfidence = confidenceSum / Util.size(values);
double newConfidence = confidenceSum / count;
BaseType result = numerator.divide(confidenceSum);
return new HasConfidenceImpl<ValueType, BaseType, RelativeTo>(result, newConfidence, at);
}
}
protected Weigher<RelativeTo> getWeigher() {
protected double getWeight(HasConfidenceAndIsScalable<ValueType, BaseType, RelativeTo> next, RelativeTo at) {
return (getWeigher() == null ? 1.0 : getWeigher().getConfidence(next.getRelativeTo(), at)) * next.getConfidence();
}
private Weigher<RelativeTo> getWeigher() {
return weigher;
}
}