org.spotter.ext.detection.highmessaging.analyze.LogAnalyzer.java Source code

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Here is the source code for org.spotter.ext.detection.highmessaging.analyze.LogAnalyzer.java

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/**
 * Copyright 2014 SAP AG
 *
 * Licensed 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
 *
 * Unless required by applicable law or agreed to in writing, 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 under the License.
 */
package org.spotter.ext.detection.highmessaging.analyze;

import java.util.Collections;
import java.util.List;

import org.apache.commons.math3.stat.regression.SimpleRegression;
import org.spotter.ext.detection.trendlines.LogTrendLine;
import org.spotter.ext.detection.trendlines.TrendLine;
import org.spotter.shared.result.model.SpotterResult;

public class LogAnalyzer extends Analyzer {

    public static final int SMOOTH_WIDE = 1;
    private double maxSlopeFactor;

    /**
     * 
     * @param xValues
     *            x values
     * @param yValues
     *            y values
     * @param maxSlopeFactor
     *            The factor of the slop of the second half of the measurement
     *            data relative to the first part.
     */
    public LogAnalyzer(SpotterResult result, List<Integer> xValues, List<Double> yValues, double maxSlopeFactor) {
        super(result, xValues, yValues);
        this.maxSlopeFactor = maxSlopeFactor;
    }

    @Override
    public AnalyzeResult analyze() {
        result.addMessage("*************************************************");
        result.addMessage("Testing data for stagnating progression..");

        TrendLine logTrend = new LogTrendLine();
        logTrend.setValues(toDoubleArray(normalize(yValues, Collections.min(yValues))), toDoubleArray(xValues));

        List<Double> smoothed = smooth(yValues, SMOOTH_WIDE);

        SimpleRegression first = new SimpleRegression();
        first.addData(
                toDoubleArray(subList(xValues, 0, xValues.size() / 2), subList(smoothed, 0, xValues.size() / 2)));

        SimpleRegression second = new SimpleRegression();
        second.addData(toDoubleArray(subList(xValues, xValues.size() / 2), subList(smoothed, xValues.size() / 2)));

        result.addMessage("> Slope 0%-50%:   " + first.getSlope());
        result.addMessage("> Slope 50%-100%: " + second.getSlope());
        result.addMessage("> Threshold:      " + maxSlopeFactor * first.getSlope());

        if (Math.abs(second.getSlope()) < maxSlopeFactor * first.getSlope()) {
            result.addMessage("> detected");
            return AnalyzeResult.POSITIVE;
        } else {
            result.addMessage("> not detected");
            return AnalyzeResult.NEGATIVE;
        }
    }

}