package com.yahoo.labs.samoa.learners.clusterers;

/*
 * #%L
 * SAMOA
 * %%
 * Copyright (C) 2013 Yahoo! Inc.
 * %%
 * 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.
 * #L%
 */
/**
 * License
 */
import com.github.javacliparser.ClassOption;
import com.github.javacliparser.Configurable;
import com.yahoo.labs.samoa.instances.Instance;
import com.yahoo.labs.samoa.instances.Instances;
import com.yahoo.labs.samoa.instances.InstancesHeader;
import com.yahoo.labs.samoa.moa.cluster.Clustering;
import com.yahoo.labs.samoa.moa.clusterers.clustream.Clustream;

/**
 *
 *  Base class for adapting Clustream clusterer.
 *
 */
public class ClustreamClustererAdapter implements LocalClustererAdapter, Configurable {

    /**
     *
     */
    private static final long serialVersionUID = 4372366401338704353L;
    
    public ClassOption learnerOption = new ClassOption("learner", 'l',
            "Clusterer to train.", com.yahoo.labs.samoa.moa.clusterers.Clusterer.class, Clustream.class.getName());
    /**
     * The learner.
     */
    protected com.yahoo.labs.samoa.moa.clusterers.Clusterer learner;
    
    /**
     * The is init.
     */
    protected Boolean isInit;
    
    /**
     * The dataset.
     */
    protected Instances dataset;

    @Override
    public void setDataset(Instances dataset) {
        this.dataset = dataset;
    }

    /**
     * Instantiates a new learner.
     *
     * @param learner the learner
     * @param dataset the dataset
     */
    public ClustreamClustererAdapter(com.yahoo.labs.samoa.moa.clusterers.Clusterer learner, Instances dataset) {
        this.learner = learner.copy();
        this.isInit = false;
        this.dataset = dataset;
    }

    /**
     * Instantiates a new learner.
     *
     * @param learner the learner
     * @param dataset the dataset
     */
    public ClustreamClustererAdapter() {
        this.learner = ((com.yahoo.labs.samoa.moa.clusterers.Clusterer) this.learnerOption.getValue()).copy();
        this.isInit = false;
        //this.dataset = dataset;
    }

    /**
     * Creates a new learner object.
     *
     * @return the learner
     */
    @Override
    public ClustreamClustererAdapter create() {
        ClustreamClustererAdapter l = new ClustreamClustererAdapter(learner, dataset);
        if (dataset == null) {
            System.out.println("dataset null while creating");
        }
        return l;
    }

    /**
     * Trains this classifier incrementally using the given instance.
     *
     * @param inst the instance to be used for training
     */
    @Override
    public void trainOnInstance(Instance inst) {
        if (this.isInit == false) {
            this.isInit = true;
            InstancesHeader instances = new InstancesHeader(dataset);
            this.learner.setModelContext(instances);
            this.learner.prepareForUse();
        }
        if (inst.weight() > 0) {
            inst.setDataset(dataset);
            learner.trainOnInstance(inst);
        }
    }

    /**
     * Predicts the class memberships for a given instance. If an instance is
     * unclassified, the returned array elements must be all zero.
     *
     * @param inst the instance to be classified
     * @return an array containing the estimated membership probabilities of the
     * test instance in each class
     */
    @Override
    public double[] getVotesForInstance(Instance inst) {
        double[] ret;
        inst.setDataset(dataset);
        if (this.isInit == false) {
           ret = new double[dataset.numClasses()];
        } else {
            ret = learner.getVotesForInstance(inst);
        }
        return ret;
    }

    /**
     * Resets this classifier. It must be similar to starting a new classifier
     * from scratch.
     *
     */
    @Override
    public void resetLearning() {
        learner.resetLearning();
    }

    public boolean implementsMicroClusterer() {
        return this.learner.implementsMicroClusterer();
    }

    public Clustering getMicroClusteringResult() {
        return this.learner.getMicroClusteringResult();
    }

    public Instances getDataset() {
        return this.dataset;
    }

}