Example usage for org.apache.commons.math3.util Pair Pair

Introduction

In this page you can find the example usage for org.apache.commons.math3.util Pair Pair.

Prototype

public Pair(K k, V v)

Source Link

Document

Create an entry representing a mapping from the specified key to the specified value.

Usage

From source file:com.insightml.evaluation.functions.Gini.java

private static <T> double gini(final T[] preds, final Object[] expected, final boolean doPerfect) {
    final List<Pair<Object, T>> sortedByPdesc = new LinkedList<>();
    for (int i = 0; i < preds.length; ++i) {
        sortedByPdesc.add(new Pair<>(expected[i], preds[i]));
    }/*from  w ww  .  j av  a 2 s. c  o m*/
    final boolean isBinary = sortedByPdesc.get(0).getSecond() instanceof Boolean;
    Collections.sort(sortedByPdesc, (o1, o2) -> {
        if (doPerfect) {
            if (isBinary) {
                return ((Boolean) o1.getFirst()).booleanValue() ? -1 : 1;
            }
            return (Double) o1.getFirst() >= (Double) o2.getFirst() ? -1 : 1;
        }
        return (Double) o1.getSecond() >= (Double) o2.getSecond() ? -1 : 1;
    });

    double sum = 0;
    double giniSum = 0;
    for (final Pair<Object, T> prediction : sortedByPdesc) {
        if (isBinary) {
            sum += (Boolean) prediction.getFirst() ? 1 : 0;
        } else {
            sum += (Double) prediction.getFirst();
        }
        giniSum += sum;
    }

    giniSum = giniSum / sum - (sortedByPdesc.size() + 1.0) / 2;
    return giniSum / sortedByPdesc.size();
}

From source file:com.cloudera.oryx.common.math.DummyVisitor.java

@Override
public void visit(int index, double value) {
    seenValues.add(new Pair<Integer, Double>(index, value));
}

From source file:com.insightml.evaluation.simulation.SplitSimulation.java

public static <S extends Sample> Pair<Iterable<S>, List<S>> split(final Iterable<S> instances,
        final double trainFraction, final Random random) {
    if (trainFraction == 1.0) {
        return new Pair<>(instances, null);
    }//ww  w.j ava  2s.co m
    final List<S> train = new LinkedList<>();
    final List<S> test = new LinkedList<>();
    for (final S sample : instances) {
        if (random.nextDouble() < trainFraction) {
            train.add(sample);
        } else {
            test.add(sample);
        }
    }
    return new Pair<>(train, test);
}

From source file:com.insightml.models.AbstractBasicDoubleLearner.java

private static Pair<double[], double[][]> filter(final LearnerInput<? extends Sample, ? extends Double> input) {
    final double[][] features = input.getTrain().features();
    final Double[] expected = input.getTrain().expected(input.labelIndex);

    final DoubleArray expFiltered = new DoubleArray(expected.length);
    final List<double[]> featsFiltered = new LinkedList<>();
    for (int i = 0; i < expected.length; ++i) {
        if (expected[i] != null) {
            expFiltered.add(expected[i].doubleValue());
            featsFiltered.add(features[i]);
        }/*  w  w  w  . j  ava2s  .c o  m*/
    }
    final double[][] featsArray = Arrays.of(featsFiltered, double[].class);
    return new Pair<>(expFiltered.toArray(), featsArray);
}

From source file:com.insightml.models.optimization.LinearModelBlenderTest.java

@Override
protected Pair<? extends ILearner<Sample, ? super Double, Double>, Double> getNumeric() {
    return new Pair(new LinearModelBlender(true, new double[1][2], new RMSE(), new OLS()), -0.75341);
}

From source file:com.insightml.models.optimization.LinearModelBlenderTest.java

@Override
protected Pair getBoolean() {
    return new Pair<>(new LinearModelBlender(true, new double[1][2], new LogLoss(false), new OLS()), -0.03123);
}

From source file:io.druid.benchmark.datagen.SequentialDistribution.java

public SequentialDistribution(Integer start, Integer end, List<Object> enumeratedValues) {
    // just pass in some bogus probability mass function, we won't be using it
    super(Arrays.asList(new Pair<Object, Double>(null, 1.0)));
    this.start = start;
    this.end = end;
    this.enumeratedValues = enumeratedValues;
    if (enumeratedValues == null) {
        counter = start;/*from  w  w w. j  a va 2  s  .com*/
    } else {
        counter = 0;
    }
}

From source file:it.unibo.alchemist.SupportedIncarnations.java

/**
 * Fetches an incarnation whose name matches the supplied string.
 * /*  w  w  w  . j  a  v a 2  s  . com*/
 * @param s
 *            the name of the {@link Incarnation}
 * @param <T>
 *            {@link Concentration} type
 * @return an {@link Optional} containing the incarnation, if one with a
 *         matching name exists
 */
@SuppressWarnings("unchecked")
public static <T> Optional<Incarnation<T>> get(final String s) {
    final String cmp = preprocess(s);
    return INCARNATIONS.stream()
            .map(clazz -> new Pair<>(METRIC.distance(preprocess(clazz.getSimpleName()), cmp), clazz))
            .min((p1, p2) -> Double.compare(p1.getFirst(), p2.getFirst())).map(Pair::getSecond)
            .flatMap(clazz -> {
                try {
                    return Optional.of(clazz.newInstance());
                } catch (Exception e) {
                    L.error("Unable to instance incarnation " + clazz + " (closest match to " + s + " among "
                            + INCARNATIONS + ")", e);
                    return Optional.empty();
                }
            });
}

From source file:it.unibo.alchemist.language.protelis.datatype.FieldTroveMapImpl.java

@Override
public void addSample(final DeviceUID n, final Object v) {
    fld.put(n.getId(), new Pair<>(n, v));
}

From source file:it.unibo.alchemist.language.protelis.datatype.AbstractField.java

@Override
public Pair<DeviceUID, Object> reducePairs(final BinaryOperator<Pair<DeviceUID, Object>> accumulator,
        final DeviceUID exclude) {
    return reduce(coupleIterator(), accumulator,
            exclude == null ? null : new Pair<>(exclude, getSample(exclude)), null);
}