org.jpmml.evaluator.functions.AggregateFunction.java Source code

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Here is the source code for org.jpmml.evaluator.functions.AggregateFunction.java

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/*
 * Copyright (c) 2014 Villu Ruusmann
 *
 * This file is part of JPMML-Evaluator
 *
 * JPMML-Evaluator is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Affero General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * JPMML-Evaluator is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU Affero General Public License for more details.
 *
 * You should have received a copy of the GNU Affero General Public License
 * along with JPMML-Evaluator.  If not, see <http://www.gnu.org/licenses/>.
 */
package org.jpmml.evaluator.functions;

import java.util.List;

import com.google.common.base.Predicates;
import com.google.common.collect.Iterables;
import org.apache.commons.math3.stat.descriptive.StorelessUnivariateStatistic;
import org.dmg.pmml.DataType;
import org.jpmml.evaluator.FieldValue;
import org.jpmml.evaluator.FieldValueUtil;
import org.jpmml.evaluator.InvalidResultException;
import org.jpmml.evaluator.TypeUtil;

abstract public class AggregateFunction extends AbstractFunction {

    public AggregateFunction(String name) {
        super(name);
    }

    abstract public StorelessUnivariateStatistic createStatistic();

    public DataType getResultType(DataType dataType) {
        return dataType;
    }

    @Override
    public FieldValue evaluate(List<FieldValue> arguments) {
        StorelessUnivariateStatistic statistic = createStatistic();

        DataType dataType = null;

        // "Missing values in the input to an aggregate function are simply ignored"
        Iterable<FieldValue> values = Iterables.filter(arguments, Predicates.notNull());
        for (FieldValue value : values) {
            statistic.increment((value.asNumber()).doubleValue());

            if (dataType != null) {
                dataType = TypeUtil.getResultDataType(dataType, value.getDataType());
            } else

            {
                dataType = value.getDataType();
            }
        }

        if (statistic.getN() == 0) {
            throw new InvalidResultException(null);
        }

        Object result = cast(getResultType(dataType), statistic.getResult());

        return FieldValueUtil.create(result);
    }
}