org.ojalgo.series.primitive.SeriesSet Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of ojalgo Show documentation

oj! Algorithms - ojAlgo - is Open Source Java code that has to do with mathematics, linear algebra and optimisation.

There is a newer version: 55.0.1

/*
 * Copyright 1997-2024 Optimatika
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
package org.ojalgo.series.primitive;

import org.ojalgo.data.DataProcessors;
import org.ojalgo.structure.Factory2D;
import org.ojalgo.structure.Mutate2D;
import org.ojalgo.structure.Structure2D;

public class SeriesSet {

    private final PrimitiveSeries[] mySet;

    SeriesSet(final PrimitiveSeries[] set) {
        super();
        mySet = set;
    }

    public SeriesSet differences() {

        PrimitiveSeries[] retSet = new PrimitiveSeries[mySet.length];

        for (int i = 0; i < retSet.length; i++) {
            retSet[i] = mySet[i].differences();
        }

        return new SeriesSet(retSet);
    }

    public  M getCorrelations(final Factory2D factory) {
        return DataProcessors.correlations(factory, mySet);
    }

    public  M getCovariances(final Factory2D factory) {
        return DataProcessors.covariances(factory, mySet);
    }

    /**
     * Return a {@link Structure2D} with variables in columns and matching samples in rows.
     */
    public  M getData(final Factory2D.Dense factory) {
        return factory.columns(mySet);
    }

    public SeriesSet log() {

        PrimitiveSeries[] retSet = new PrimitiveSeries[mySet.length];

        for (int i = 0; i < retSet.length; i++) {
            retSet[i] = mySet[i].log();
        }

        return new SeriesSet(retSet);
    }

    public SeriesSet quotients() {

        PrimitiveSeries[] retSet = new PrimitiveSeries[mySet.length];

        for (int i = 0; i < retSet.length; i++) {
            retSet[i] = mySet[i].quotients();
        }

        return new SeriesSet(retSet);
    }

}