content: /*
   *
   *
   *    Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements.
   *    See the NOTICE file distributed with 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
   *
   *    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.
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  package eu.amidst.latentvariablemodels;
  
  import eu.amidst.core.datastream.DataInstance;
  import eu.amidst.core.datastream.DataOnMemory;
  import eu.amidst.core.datastream.DataStream;
  import eu.amidst.core.utils.DataSetGenerator;
  import eu.amidst.core.variables.Variable;
  import eu.amidst.latentvariablemodels.staticmodels.exceptions.WrongConfigurationException;
  import eu.amidst.latentvariablemodels.staticmodels.GaussianMixture;
  import junit.framework.TestCase;
  
  /**
   * Created by rcabanas on 10/03/16.
   */
  public class GaussianMixtureTest extends TestCase {
  
      protected GaussianMixture gmm;
      DataStream<DataInstance> data;
  
      protected void setUp() throws WrongConfigurationException {
  
  
          DataStream<DataInstance> data = DataSetGenerator.generate(1234,500, 0, 4);
  
  
  
          gmm = new GaussianMixture(data.getAttributes());
          gmm.setDiagonal(false);
          gmm.setNumStatesHiddenVar(3);
  
          gmm.updateModel(data);
          for (DataOnMemory<DataInstance> batch : data.iterableOverBatches(100)) {
              gmm.updateModel(batch);
          }
  
  
      }
  
  
      //////// test methods
  
      public void testHiddenVar() {
          boolean passedTest = true;
  
          Variable classVar = gmm.getHiddenVar();
  
          // class variable is a multinomial
          boolean isMultinomial = classVar.isMultinomial();
  
          //has not parents
          boolean noParents = gmm.getDAG().getParentSet(classVar).getParents().isEmpty();
  
          //all the attributes are their children
          boolean allAttrChildren = gmm.getModel().getVariables().getListOfVariables().stream()
                  .filter(v-> !v.equals(classVar))
                  .allMatch(v -> gmm.getDAG().getParentSet(v).contains(classVar));
  
          assertTrue(isMultinomial && noParents && allAttrChildren);
      }
  
  
  
      public void testAttributes(){
          Variable classVar = gmm.getHiddenVar();
  
          // the attributes have a single parent
          boolean numParents = gmm.getModel().getVariables().getListOfVariables().stream()
                  .filter(v-> !v.equals(classVar))
                  .allMatch(v -> gmm.getDAG().getParentSet(v).getNumberOfParents()==1);
  
          assertTrue(!gmm.isDiagonal() || numParents);
      }
  
  
  
  
  
  }
  