/*
 * Copyright (c) 2012-2013, Peter Abeles. All Rights Reserved.
 *
 * This file is part of DDogleg (http://ddogleg.org).
 *
 * 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.ddogleg.optimization.funcs;

import org.ddogleg.optimization.functions.FunctionNtoM;
import org.ddogleg.optimization.functions.FunctionNtoMxN;

/**
 *
 * 

 * [1] J. More, B. Garbow, K. Hillstrom, "Testing Unconstrained Optimization Software"
 * 1981 ACM Transactions on Mathematical Software, Vol 7, No. 1, Match 1981, pages 17-41
 * 
 *
 * @author Peter Abeles
 */
public class EvalFuncVariablyDimensioned implements EvalFuncLeastSquares {
	
	int N;

	public EvalFuncVariablyDimensioned(int n) {
		N = n;
	}

	@Override
	public FunctionNtoM getFunction() {
		return new Func();
	}

	@Override
	public FunctionNtoMxN getJacobian() {
		return null;
	}

	@Override
	public double[] getInitial() {
		double x[] = new double[N];
		
		for( int i = 0; i < N; i++ ) {
			x[i] = 1-((double)i/(double)N);
		}
		
		return x;
	}

	@Override
	public double[] getOptimal() {
		double x[] = new double[N];
		for( int i = 0; i < N; i++ )
			x[i] = 1;
		return x;
	}

	public class Func implements FunctionNtoM
	{
		@Override
		public int getNumOfInputsN() {
			return N;
		}

		@Override
		public int getNumOfOutputsM() {
			return N+2;
		}

		@Override
		public void process(double[] input, double[] output) {
			for( int i = 0; i < N; i++ ) {
				output[i] = input[i]-1;
			}
			double sum = 0;
			for( int i = 0; i < N; i++ ) {
				sum += (i+1)*(input[i]-1);
			}
			
			output[N] = sum;
			output[N+1] = sum*sum;
		}
	}

}