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 * 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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 * 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
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package org.apache.commons.math3.optimization;

import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;

Simple implementation of the ConvergenceChecker interface using only objective function values. Convergence is considered to have been reached if either the relative difference between the objective function values is smaller than a threshold or if either the absolute difference between the objective function values is smaller than another threshold for all vectors elements. 
 The converged method will also return true if the number of iterations has been set (see this constructor). 
Deprecated:
As of 3.1 (to be removed in 4.0).
Since:
3.0/**
 * Simple implementation of the {@link ConvergenceChecker} interface using
 * only objective function values.
 *
 * Convergence is considered to have been reached if either the relative
 * difference between the objective function values is smaller than a
 * threshold or if either the absolute difference between the objective
 * function values is smaller than another threshold for all vectors elements.
 * <br/>
 * The {@link #converged(int,PointVectorValuePair,PointVectorValuePair) converged}
 * method will also return {@code true} if the number of iterations has been set
 * (see {@link #SimpleVectorValueChecker(double,double,int) this constructor}).
 *
 * @deprecated As of 3.1 (to be removed in 4.0).
 * @since 3.0
 */
@Deprecated
public class SimpleVectorValueChecker
    extends AbstractConvergenceChecker<PointVectorValuePair> {
    
If maxIterationCount is set to this value, the number of iterations will never cause converged(int, PointVectorValuePair, PointVectorValuePair) to return true. /**
     * If {@link #maxIterationCount} is set to this value, the number of
     * iterations will never cause
     * {@link #converged(int,PointVectorValuePair,PointVectorValuePair)}
     * to return {@code true}.
     */
    private static final int ITERATION_CHECK_DISABLED = -1;
    
Number of iterations after which the converged(int, PointVectorValuePair, PointVectorValuePair) method will return true (unless the check is disabled). /**
     * Number of iterations after which the
     * {@link #converged(int,PointVectorValuePair,PointVectorValuePair)} method
     * will return true (unless the check is disabled).
     */
    private final int maxIterationCount;

    
Build an instance with default thresholds.
Deprecated:
See AbstractConvergenceChecker()/**
     * Build an instance with default thresholds.
     * @deprecated See {@link AbstractConvergenceChecker#AbstractConvergenceChecker()}
     */
    @Deprecated
    public SimpleVectorValueChecker() {
        maxIterationCount = ITERATION_CHECK_DISABLED;
    }

    
Build an instance with specified thresholds.
In order to perform only relative checks, the absolute tolerance
must be set to a negative value. In order to perform only absolute
checks, the relative tolerance must be set to a negative value.
Params:
relativeThreshold – relative tolerance threshold
absoluteThreshold – absolute tolerance threshold/**
     * Build an instance with specified thresholds.
     *
     * In order to perform only relative checks, the absolute tolerance
     * must be set to a negative value. In order to perform only absolute
     * checks, the relative tolerance must be set to a negative value.
     *
     * @param relativeThreshold relative tolerance threshold
     * @param absoluteThreshold absolute tolerance threshold
     */
    public SimpleVectorValueChecker(final double relativeThreshold,
                                    final double absoluteThreshold) {
        super(relativeThreshold, absoluteThreshold);
        maxIterationCount = ITERATION_CHECK_DISABLED;
    }

    
Builds an instance with specified tolerance thresholds and
iteration count.
In order to perform only relative checks, the absolute tolerance
must be set to a negative value. In order to perform only absolute
checks, the relative tolerance must be set to a negative value.
Params:
relativeThreshold – Relative tolerance threshold.
absoluteThreshold – Absolute tolerance threshold.
maxIter – Maximum iteration count.
Throws:
NotStrictlyPositiveException – if maxIter <= 0.
Since:
3.1/**
     * Builds an instance with specified tolerance thresholds and
     * iteration count.
     *
     * In order to perform only relative checks, the absolute tolerance
     * must be set to a negative value. In order to perform only absolute
     * checks, the relative tolerance must be set to a negative value.
     *
     * @param relativeThreshold Relative tolerance threshold.
     * @param absoluteThreshold Absolute tolerance threshold.
     * @param maxIter Maximum iteration count.
     * @throws NotStrictlyPositiveException if {@code maxIter <= 0}.
     *
     * @since 3.1
     */
    public SimpleVectorValueChecker(final double relativeThreshold,
                                    final double absoluteThreshold,
                                    final int maxIter) {
        super(relativeThreshold, absoluteThreshold);

        if (maxIter <= 0) {
            throw new NotStrictlyPositiveException(maxIter);
        }
        maxIterationCount = maxIter;
    }

    
Check if the optimization algorithm has converged considering the
last two points.
This method may be called several times from the same algorithm
iteration with different points. This can be detected by checking the
iteration number at each call if needed. Each time this method is
called, the previous and current point correspond to points with the
same role at each iteration, so they can be compared. As an example,
simplex-based algorithms call this method for all points of the simplex,
not only for the best or worst ones.
Params:
iteration – Index of current iteration
previous – Best point in the previous iteration.
current – Best point in the current iteration.
Returns:
true if the arguments satify the convergence criterion./**
     * Check if the optimization algorithm has converged considering the
     * last two points.
     * This method may be called several times from the same algorithm
     * iteration with different points. This can be detected by checking the
     * iteration number at each call if needed. Each time this method is
     * called, the previous and current point correspond to points with the
     * same role at each iteration, so they can be compared. As an example,
     * simplex-based algorithms call this method for all points of the simplex,
     * not only for the best or worst ones.
     *
     * @param iteration Index of current iteration
     * @param previous Best point in the previous iteration.
     * @param current Best point in the current iteration.
     * @return {@code true} if the arguments satify the convergence criterion.
     */
    @Override
    public boolean converged(final int iteration,
                             final PointVectorValuePair previous,
                             final PointVectorValuePair current) {
        if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) {
            return true;
        }

        final double[] p = previous.getValueRef();
        final double[] c = current.getValueRef();
        for (int i = 0; i < p.length; ++i) {
            final double pi         = p[i];
            final double ci         = c[i];
            final double difference = FastMath.abs(pi - ci);
            final double size       = FastMath.max(FastMath.abs(pi), FastMath.abs(ci));
            if (difference > size * getRelativeThreshold() &&
                difference > getAbsoluteThreshold()) {
                return false;
            }
        }
        return true;
    }
}