de.hsheilbronn.mi.domain.NativeSvmModelWrapper.java Source code

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Here is the source code for de.hsheilbronn.mi.domain.NativeSvmModelWrapper.java

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/*-
 * ========================LICENSE_START=================================
 * zlibsvm-core
 * %%
 * Copyright (C) 2014 - 2017 Heilbronn University - Medical Informatics
 * %%
 * 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.
 * =========================LICENSE_END==================================
 */
package de.hsheilbronn.mi.domain;

import de.hsheilbronn.mi.configuration.SvmConfigurationBuilder;
import de.hsheilbronn.mi.process.AbstractSvmTool;
import de.hsheilbronn.mi.util.PrimitiveHelper;
import libsvm.svm_model;
import org.apache.commons.lang3.ArrayUtils;

import java.util.List;
import java.util.Map;

/**
 * @author rz
 */
public class NativeSvmModelWrapper {

    protected svm_model svmModel;

    public NativeSvmModelWrapper(svm_model svmModel) {
        this.svmModel = svmModel;
    }

    public NativeSvmModelWrapper(SvmConfigurationBuilder svmConfigurationBuilder, int probabilityEstimates,
            List<Double> rhoConstants, List<Integer> labelForEachClass, List<Double> probabilityA,
            List<Double> probabilityB, List<Integer> numberOfSVforEachClass, int numberOfClasses,
            int amountOfSupportVectors) {

        this(svmConfigurationBuilder, probabilityEstimates, rhoConstants, labelForEachClass, probabilityA,
                probabilityB, numberOfSVforEachClass, numberOfClasses, amountOfSupportVectors, null, null);
    }

    public NativeSvmModelWrapper(SvmConfigurationBuilder svmConfigurationBuilder, int probabilityEstimates,
            List<Double> rhoConstants, List<Integer> labelForEachClass, List<Double> probabilityA,
            List<Double> probabilityB, List<Integer> numberOfSVforEachClass, int numberOfClasses,
            int amountOfSupportVectors, Map<Integer, List<Double>> svCoefficients,
            Map<Integer, List<SvmFeature>> supportVectors) {

        svm_model nativeSvmModel = new svm_model();

        nativeSvmModel.l = (amountOfSupportVectors);
        nativeSvmModel.nr_class = (numberOfClasses);

        nativeSvmModel.rho = (ArrayUtils.toPrimitive(rhoConstants.toArray(new Double[rhoConstants.size()])));
        nativeSvmModel.probA = (ArrayUtils.toPrimitive(probabilityA.toArray(new Double[probabilityA.size()])));
        nativeSvmModel.probB = (ArrayUtils.toPrimitive(probabilityB.toArray(new Double[probabilityB.size()])));
        nativeSvmModel.label = ((ArrayUtils
                .toPrimitive(labelForEachClass.toArray(new Integer[labelForEachClass.size()]))));
        nativeSvmModel.nSV = (ArrayUtils
                .toPrimitive(numberOfSVforEachClass.toArray(new Integer[numberOfSVforEachClass.size()])));

        if (svCoefficients != null) {
            nativeSvmModel.sv_coef = (PrimitiveHelper.doubleMapTo2dArray(svCoefficients));
        }

        if (supportVectors != null) {
            nativeSvmModel.SV = (PrimitiveHelper.svmFeatureMapTo2dArray(supportVectors));
        }

        nativeSvmModel.param = AbstractSvmTool
                .unwrap((svmConfigurationBuilder.setProbability(probabilityEstimates == 1 ? true : false).build()));

        this.svmModel = nativeSvmModel;
    }

    public svm_model getSvmModel() {
        return svmModel;
    }

}