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* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
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* KIND, either express or implied. See the License for the
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package org.apache.uima.ruta.testing.ui.views.util;
import java.util.Collection;
import java.util.HashMap;
import org.apache.uima.cas.CAS;
import org.apache.uima.cas.FSIterator;
import org.apache.uima.cas.Feature;
import org.apache.uima.cas.FeatureStructure;
import org.apache.uima.cas.Type;
import org.apache.uima.cas.TypeSystem;
import org.apache.uima.cas.text.AnnotationFS;
import org.apache.uima.cas.text.AnnotationIndex;
import org.apache.uima.ruta.testing.evaluator.ICasEvaluator;
import org.apache.uima.ruta.testing.ui.views.TestCasData;
import org.apache.uima.ruta.testing.ui.views.evalDataTable.TypeEvalData;
public class EvalDataProcessor {
public static void calculateEvaluatData(TestCasData data, CAS resultCas) {
data.setEvaluationStatus(true);
TypeSystem ts = resultCas.getTypeSystem();
Type falsePositiveType = ts.getType(ICasEvaluator.FALSE_POSITIVE);
Type falseNegativeType = ts.getType(ICasEvaluator.FALSE_NEGATIVE);
Type truePositiveType = ts.getType(ICasEvaluator.TRUE_POSITIVE);
Feature originalFeature = truePositiveType.getFeatureByBaseName("original");
int falsePositiveCount = resultCas.getAnnotationIndex(falsePositiveType).size();
int falseNegativeCount = resultCas.getAnnotationIndex(falseNegativeType).size();
int truePositiveCount = resultCas.getAnnotationIndex(truePositiveType).size();
data.setTruePositiveCount(truePositiveCount);
data.setFalsePositiveCount(falsePositiveCount);
data.setFalseNegativeCount(falseNegativeCount);
HashMap<String, TypeEvalData> map = new HashMap<String, TypeEvalData>();
map.put(" Total", new TypeEvalData("Total", truePositiveCount, falsePositiveCount,
falseNegativeCount));
AnnotationIndex<AnnotationFS> index = resultCas.getAnnotationIndex(truePositiveType);
FSIterator iter = index.iterator();
if (originalFeature != null) {
while (iter.isValid()) {
AnnotationFS a = (AnnotationFS) iter.next();
FeatureStructure fs = a.getFeatureValue(originalFeature);
String typeName = fs.getType().getName();
if (map.containsKey(typeName)) {
TypeEvalData element = map.get(typeName);
int oldCount = element.getTruePositives();
element.setTruePositives(oldCount + 1);
} else {
TypeEvalData newData = new TypeEvalData(typeName, 1, 0, 0);
map.put(typeName, newData);
}
}
index = resultCas.getAnnotationIndex(falsePositiveType);
iter = index.iterator();
while (iter.isValid()) {
AnnotationFS a = (AnnotationFS) iter.next();
FeatureStructure fs = a.getFeatureValue(originalFeature);
String typeName = fs.getType().getName();
if (map.containsKey(typeName)) {
TypeEvalData element = map.get(typeName);
int oldCount = element.getFalsePositives();
element.setFalsePositives(oldCount + 1);
} else {
TypeEvalData newData = new TypeEvalData(typeName, 0, 1, 0);
map.put(typeName, newData);
}
}
index = resultCas.getAnnotationIndex(falseNegativeType);
iter = index.iterator();
while (iter.isValid()) {
AnnotationFS a = (AnnotationFS) iter.next();
FeatureStructure fs = a.getFeatureValue(originalFeature);
String typeName = fs.getType().getName();
if (map.containsKey(typeName)) {
TypeEvalData element = map.get(typeName);
int oldCount = element.getFalseNegatives();
element.setFalseNegatives(oldCount + 1);
} else {
TypeEvalData newData = new TypeEvalData(typeName, 0, 0, 1);
map.put(typeName, newData);
}
}
data.setTypeEvalData(map);
Collection<TypeEvalData> col = map.values();
for (TypeEvalData typeEvalData : col) {
typeEvalData.calcFOne();
}
return;
}
}
}