private void init() {
resultType =
ClusteringType.parse(
props.getObject(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING));
cutoffStrategy = CutoffStrategyFactory.getInstance().getDefault();
if (cutoffStrategy != null) {
InternalEvaluatorFactory<E, Cluster<E>> ief = InternalEvaluatorFactory.getInstance();
cutoffStrategy.setEvaluator(ief.getDefault());
}
noise = null;
}
private void sortArray(double[] values, double min, double max) {
Numeric ary[] = createArray(values);
List<InternalEvaluator> eval = InternalEvaluatorFactory.getInstance().getAll();
for (InternalEvaluator e : eval) {
subject.setEvaluator(e);
Arrays.sort(ary, subject);
if (e.isMaximized()) { // in fact this should be equal to Collections.reverseOrder()
// first value is the best
assertEquals(max, ary[0].getValue(), delta);
// last is the worst
assertEquals(min, ary[ary.length - 1].getValue(), delta);
} else {
assertEquals(min, ary[0].getValue(), delta);
assertEquals(max, ary[ary.length - 1].getValue(), delta);
}
}
}
private void sortNaN(double[] values, double min, double max) {
Numeric ary[] = createArray(values);
List<InternalEvaluator> eval = InternalEvaluatorFactory.getInstance().getAll();
for (InternalEvaluator e : eval) {
subject.setEvaluator(e);
System.out.println("testing " + e.getName() + " maximized: " + e.isMaximized());
Arrays.sort(ary, subject);
System.out.println(Arrays.toString(ary));
if (e.isMaximized()) {
// first value is the best
assertEquals(max, ary[0].getValue(), delta);
assertEquals(Double.NaN, ary[ary.length - 1].getValue(), delta);
} else {
assertEquals(min, ary[0].getValue(), delta);
assertEquals(Double.NaN, ary[ary.length - 1].getValue(), delta);
}
}
}
