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Stochastice Performance Logic is a formalism for capturing performance assumptions. It is, for example, possible to capture assumption that newer version of a function bar is faster than the previous version or that library foobar is faster than library barfoo when rendering antialiased text. The purpose of this framework is to allow evaluation of SPL formulas inside Java applications.

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/*
 * Copyright 2014 Charles University in Prague
 * Copyright 2014 Vojtech Horky
 * 
 * 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 cz.cuni.mff.d3s.spl.interpretation;

import org.apache.commons.math3.distribution.RealDistribution;

/** Data set comparison result that uses probability distributions.
 */
public class DistributionBasedComparisonResult implements ComparisonResult {
	private double statistic;
	private RealDistribution distribution;
	
	/** Create the result from precomputed statistics and corresponding distribution,.
	 * 
	 * @param stat Statistics value.
	 * @param distr Probability distribution.
	 */
	public DistributionBasedComparisonResult(double stat, RealDistribution distr) {
		statistic = stat;
		distribution = distr;
	}

	/** {@inheritDoc} */
	@Override
	public double getStatistic() {
		return statistic;
	}

	/** {@inheritDoc} */
	@Override
	public Relation get(double significanceLevel) {
		boolean lt = statistic > getCriticalValue(significanceLevel);
		boolean gt = statistic < getCriticalValue(1. - significanceLevel);
		
		if ((lt && gt) || (!lt && !gt)) {
			return Relation.EQUAL;
		} else if (lt) {
			return Relation.GREATER_THAN;
		} else {
			return Relation.LESS_THAN;
		}
	}

	/** {@inheritDoc} */
	@Override
	public double getCriticalValue(double significanceLevel) {
		return distribution.inverseCumulativeProbability(significanceLevel);
	}
	
	/** {@inheritDoc} */
	@Override
	public double[] getConfidenceInterval(double confidenceLevel) {
		throw new UnsupportedOperationException("Confidence interval computation not implemented.");
	}
	
}