/*
 * 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
 *
 * 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.apache.commons.math.stat.descriptive;

import org.apache.commons.math.linear.RealMatrix;

/**
 * Reporting interface for basic multivariate statistics.
 *
 * @since 1.2
 * @version $Revision$ $Date$
 */
public interface StatisticalMultivariateSummary {
	/**
	 * Returns the dimension of the data
	 * 
	 * @return The dimension of the data
	 */
	public int getDimension();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the mean of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component means
	 */
	public abstract double[] getMean();

	/**
	 * Returns the covariance of the available values.
	 * 
	 * @return The covariance, null if no multivariate sample have been added or
	 *         a zeroed matrix for a single value set.
	 */
	public abstract RealMatrix getCovariance();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the standard deviation of
	 * the i<sup>th</sup> entries of the arrays that correspond to each
	 * multivariate sample
	 * 
	 * @return the array of component standard deviations
	 */
	public abstract double[] getStandardDeviation();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the maximum of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component maxima
	 */
	public abstract double[] getMax();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the minimum of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component minima
	 */
	public abstract double[] getMin();

	/**
	 * Returns the number of available values
	 * 
	 * @return The number of available values
	 */
	public abstract long getN();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the geometric mean of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component geometric means
	 */
	public double[] getGeometricMean();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the sum of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component sums
	 */
	public abstract double[] getSum();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the sum of squares of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component sums of squares
	 */
	public abstract double[] getSumSq();

	/**
	 * Returns an array whose i<sup>th</sup> entry is the sum of logs of the
	 * i<sup>th</sup> entries of the arrays that correspond to each multivariate
	 * sample
	 * 
	 * @return the array of component log sums
	 */
	public abstract double[] getSumLog();
}