uk.ac.diamond.scisoft.analysis.optimize.ApacheMultiDirectional.java Source code

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Here is the source code for uk.ac.diamond.scisoft.analysis.optimize.ApacheMultiDirectional.java

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/*
 * Copyright 2011 Diamond Light Source Ltd.
 * 
 * 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 uk.ac.diamond.scisoft.analysis.optimize;

import org.apache.commons.math.FunctionEvaluationException;
import org.apache.commons.math.analysis.MultivariateRealFunction;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.apache.commons.math.optimization.direct.MultiDirectional;

import uk.ac.diamond.scisoft.analysis.dataset.AbstractDataset;
import uk.ac.diamond.scisoft.analysis.dataset.DatasetUtils;
import uk.ac.diamond.scisoft.analysis.dataset.DoubleDataset;
import uk.ac.diamond.scisoft.analysis.dataset.IDataset;
import uk.ac.diamond.scisoft.analysis.fitting.functions.IFunction;

/**
 * Class which wraps the Apache Commons Multi Directional fitting routine
 * and makes it compatible with the scisoft fitting routines
 */
public class ApacheMultiDirectional implements IOptimizer {

    @Override
    public void optimize(IDataset[] coords, IDataset data, final IFunction function) throws Exception {

        // Pull out the data which is required from the inputs
        final int numCoords = coords.length;
        final DoubleDataset[] newCoords = new DoubleDataset[numCoords];
        for (int i = 0; i < numCoords; i++) {
            newCoords[i] = (DoubleDataset) DatasetUtils.convertToAbstractDataset(coords[i])
                    .cast(AbstractDataset.FLOAT64);
        }

        final DoubleDataset values = (DoubleDataset) DatasetUtils.convertToAbstractDataset(data)
                .cast(AbstractDataset.FLOAT64);

        // create an instance of the fitter
        MultiDirectional md = new MultiDirectional();

        // provide the fitting function which wrappers all the normal fitting functionality
        MultivariateRealFunction f1 = new MultivariateRealFunction() {

            @Override
            public double value(double[] arg0) throws FunctionEvaluationException, IllegalArgumentException {
                function.setParameterValues(arg0);
                return function.residual(true, values, newCoords);
            }
        };

        double[] start = function.getParameterValues();

        // preform the optimisation
        RealPointValuePair result = md.optimize(f1, GoalType.MINIMIZE, start);

        // set the input functions parameters to be the result before finishing.
        function.setParameterValues(result.getPoint());

    }

}