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replaced more Pair<Double, Double> by ScalableBearing

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This commit is contained in:
Axel Uhl committed 2012-03-01 11:20:12 +01:00
1 parent f24deeb2e3
commit 5acebef1a1
1 file changed
+19 -21
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java/com.sap.sailing.domain.test/src/com/sap/sailing/domain/test/ConfidenceTest.java
+19 -21
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@@ -21,7 +21,6 @@ import com.sap.sailing.domain.common.TimePoint;
import com.sap.sailing.domain.common.impl.DegreeBearingImpl;
import com.sap.sailing.domain.common.impl.DegreePosition;
import com.sap.sailing.domain.common.impl.RadianBearingImpl;
import com.sap.sailing.domain.common.impl.Util.Pair;
import com.sap.sailing.domain.confidence.ConfidenceBasedAverager;
import com.sap.sailing.domain.confidence.ConfidenceFactory;
import com.sap.sailing.domain.confidence.HasConfidence;
@@ -31,7 +30,7 @@ import com.sap.sailing.domain.confidence.Weigher;
import com.sap.sailing.domain.confidence.impl.ScalableDoubleWithConfidence;
public class ConfidenceTest {
private static class ScalableBearing implements ScalableValue<Pair<Double, Double>, Bearing> {
private static class ScalableBearing implements ScalableValue<ScalableBearing, Bearing> {
private final double sin;
private final double cos;
@@ -46,16 +45,15 @@ public class ConfidenceTest {
}
@Override
public ScalableValue<Pair<Double, Double>, Bearing> multiply(double factor) {
Pair<Double, Double> pair = getValue();
return new ScalableBearing(factor*pair.getA(), factor*pair.getB());
public ScalableValue<ScalableBearing, Bearing> multiply(double factor) {
return new ScalableBearing(factor*getValue().sin, factor*getValue().cos);
}
@Override
public ScalableValue<Pair<Double, Double>, Bearing> add(ScalableValue<Pair<Double, Double>, Bearing> t) {
Pair<Double, Double> value = getValue();
Pair<Double, Double> tValue = t.getValue();
return new ScalableBearing(value.getA()+tValue.getA(), value.getB()+tValue.getB());
public ScalableValue<ScalableBearing, Bearing> add(ScalableValue<ScalableBearing, Bearing> t) {
ScalableBearing value = getValue();
ScalableBearing tValue = t.getValue();
return new ScalableBearing(value.sin+tValue.sin, value.cos+tValue.cos);
}
@Override
@@ -71,13 +69,13 @@ public class ConfidenceTest {
}
@Override
public Pair<Double, Double> getValue() {
return new Pair<Double, Double>(sin, cos);
public ScalableBearing getValue() {
return this;
}
}
private static class ScalableBearingWithConfidence<RelativeTo> extends ScalableBearing
implements HasConfidenceAndIsScalable<Pair<Double, Double>, Bearing, RelativeTo> {
implements HasConfidenceAndIsScalable<ScalableBearing, Bearing, RelativeTo> {
private final double confidence;
private final RelativeTo relativeTo;
private final Bearing bearing;
@@ -100,7 +98,7 @@ public class ConfidenceTest {
}
@Override
public ScalableValue<Pair<Double, Double>, Bearing> getScalableValue() {
public ScalableBearingWithConfidence<RelativeTo> getScalableValue() {
return this;
}
@@ -164,9 +162,9 @@ public class ConfidenceTest {
public void testAveragingWithTwoBearings() {
ScalableBearingWithConfidence<TimePoint> d1 = new ScalableBearingWithConfidence<TimePoint>(new DegreeBearingImpl(350.), 1., null);
ScalableBearingWithConfidence<TimePoint> d2 = new ScalableBearingWithConfidence<TimePoint>(new DegreeBearingImpl(10.), 1., null);
ConfidenceBasedAverager<Pair<Double, Double>, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE.createAverager(null);
ConfidenceBasedAverager<ScalableBearing, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE.createAverager(null);
List<ScalableBearingWithConfidence<TimePoint>> list = Arrays.asList(d1, d2);
HasConfidence<Pair<Double, Double>, Bearing, TimePoint> average = averager.getAverage(list, null);
HasConfidence<ScalableBearing, Bearing, TimePoint> average = averager.getAverage(list, null);
assertEquals(0, average.getObject().getDegrees(), 0.00000001);
}
@@ -175,9 +173,9 @@ public class ConfidenceTest {
ScalableBearingWithConfidence<TimePoint> d1 = new ScalableBearingWithConfidence<TimePoint>(new DegreeBearingImpl(350.), 1., null);
ScalableBearingWithConfidence<TimePoint> d2 = new ScalableBearingWithConfidence<TimePoint>(new DegreeBearingImpl(10.), 1., null);
ScalableBearingWithConfidence<TimePoint> d3 = new ScalableBearingWithConfidence<TimePoint>(new DegreeBearingImpl(20.), 2., null);
ConfidenceBasedAverager<Pair<Double, Double>, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE.createAverager(null);
ConfidenceBasedAverager<ScalableBearing, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE.createAverager(null);
List<ScalableBearingWithConfidence<TimePoint>> list = Arrays.asList(d1, d2, d3);
HasConfidence<Pair<Double, Double>, Bearing, TimePoint> average = averager.getAverage(list, null);
HasConfidence<ScalableBearing, Bearing, TimePoint> average = averager.getAverage(list, null);
assertEquals(10, average.getObject().getDegrees(), 0.1);
}
@@ -299,10 +297,10 @@ public class ConfidenceTest {
new DegreeBearingImpl(350.), 1., new MillisecondsTimePoint(1000)); // confidence 2/4 when viewed for time point 2000
ScalableBearingWithConfidence<TimePoint> d2 = new ScalableBearingWithConfidence<TimePoint>(
new DegreeBearingImpl(10.), 1., new MillisecondsTimePoint(2000)); // confidence 4/4 when viewed for time point 2000
ConfidenceBasedAverager<Pair<Double, Double>, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE
ConfidenceBasedAverager<ScalableBearing, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE
.createAverager(ConfidenceFactory.INSTANCE.createExponentialTimeDifferenceWeigher(1000));
List<ScalableBearingWithConfidence<TimePoint>> list = Arrays.asList(d1, d2);
HasConfidence<Pair<Double, Double>, Bearing, TimePoint> average = averager.getAverage(list, new MillisecondsTimePoint(2000));
HasConfidence<ScalableBearing, Bearing, TimePoint> average = averager.getAverage(list, new MillisecondsTimePoint(2000));
assertEquals((2.*10+1.*-10.)/3., average.getObject().getDegrees(), 0.1);
}
@@ -314,10 +312,10 @@ public class ConfidenceTest {
new DegreeBearingImpl(10.), 1., new MillisecondsTimePoint(2000)); // confidence 4/4 when viewed for time point 2000
ScalableBearingWithConfidence<TimePoint> d3 = new ScalableBearingWithConfidence<TimePoint>(
new DegreeBearingImpl(20.), 2., new MillisecondsTimePoint(3000)); // confidence 2/4 when viewed for time point 2000
ConfidenceBasedAverager<Pair<Double, Double>, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE
ConfidenceBasedAverager<ScalableBearing, Bearing, TimePoint> averager = ConfidenceFactory.INSTANCE
.createAverager(ConfidenceFactory.INSTANCE.createExponentialTimeDifferenceWeigher(1000));
List<ScalableBearingWithConfidence<TimePoint>> list = Arrays.asList(d1, d2, d3);
HasConfidence<Pair<Double, Double>, Bearing, TimePoint> average = averager.getAverage(list, new MillisecondsTimePoint(2000));
HasConfidence<ScalableBearing, Bearing, TimePoint> average = averager.getAverage(list, new MillisecondsTimePoint(2000));
assertEquals(10, average.getObject().getDegrees(), 0.1);
}