analytics/math3/src/main/java/org/apache/edgent/analytics/math3/stat/OLS.java

/*
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements.  See the NOTICE file
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

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software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied.  See the License for the
specific language governing permissions and limitations
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*/
package org.apache.edgent.analytics.math3.stat;

import org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression;
import org.apache.edgent.analytics.math3.UnivariateAggregate;
import org.apache.edgent.analytics.math3.UnivariateAggregator;

/**
 * Wrapper over commons math3 {@code OLSMultipleLinearRegression}
 */
class OLS implements UnivariateAggregator {
    
    private final Regression2 type;
    private final OLSMultipleLinearRegression ols = new OLSMultipleLinearRegression();
    private double[] values;
    private int yOffset;
    
    OLS(Regression2 type) {
        this.type = type;
    }

    @Override
    public UnivariateAggregate getAggregate() {
      return type;
    }

    @Override
    public void clear(int n) {
        values = new double[n*2];
        yOffset = 0;
    }

    @Override
    public void increment(double v) {  
        values[yOffset] = v;
        yOffset+=2;
    }
    
    void setSampleData() {
        // Fill  in the x values
        for (int x = 0; x < values.length/2; x++)
            values[(x*2)+1] = x;
        ols.newSampleData(values, values.length/2, 1);
    }
    
    @Override
    public double getResult() {
        // If there are no values or only a single
        // value then we cannot calculate the slope.
        if (values.length <= 2)
            return Double.NaN;
            
        setSampleData();
        double[] regressionParams = ols.estimateRegressionParameters();
        if (regressionParams.length >= 2) {
            // [0] is the constant (zero'th order)
            // [1] is the first order , which we use as the slope.
            final double slope = regressionParams[1];
            return slope;
        }
        return Double.NaN;
    }
}