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.core.conceptdrift.utils;
  
  
  
  import eu.amidst.core.exponentialfamily.EF_UnivariateDistribution;
  import eu.amidst.core.inference.messagepassing.Node;
  import eu.amidst.core.learning.parametric.bayesian.utils.PlateuIIDReplication;
  import eu.amidst.core.variables.Variable;
  
  import java.util.ArrayList;
  import java.util.List;
  import java.util.Map;
  import java.util.concurrent.ConcurrentHashMap;
  import java.util.stream.Collectors;
  
  /**
   * Created by andresmasegosa on 10/03/15.
   */
  public class PlateuHiddenVariableConceptDrift extends PlateuIIDReplication {
  
      List<Variable> localHiddenVars;
      List<Node> localHiddenNodes;
      Map<Variable,Node> hiddenToNode;
      boolean dynamic;
  
      public PlateuHiddenVariableConceptDrift(List<Variable> localHiddenVars_, boolean dynamic_){
          this.localHiddenVars = localHiddenVars_;
          this.dynamic = dynamic_;
      }
  
      public void replicateModel(){
          nonReplictedNodes = new ArrayList();
          replicatedNodes = new ArrayList<>(nReplications);
  
          replicatedVarsToNode = new ArrayList<>();
          nonReplicatedVarsToNode = new ConcurrentHashMap<>();
          nonReplictedNodes = ef_learningmodel.getDistributionList().stream()
                  .filter(dist -> dist.getVariable().isParameterVariable())
                  .map(dist -> {
                      Node node = new Node(dist);
                      nonReplicatedVarsToNode.put(dist.getVariable(), node);
                      return node;
                  })
                  .collect(Collectors.toList());
  
          localHiddenNodes = new ArrayList();
          hiddenToNode = new ConcurrentHashMap();
          for (Variable localVar : this.localHiddenVars) {
              Node node  = new Node(ef_learningmodel.getDistribution(localVar));
              hiddenToNode.put(localVar, node);
              localHiddenNodes.add(node);
          }
  
          for (int i = 0; i < nReplications; i++) {
  
              Map<Variable, Node> map = new ConcurrentHashMap();
              List<Node> tmpNodes = ef_learningmodel.getDistributionList().stream()
                      .filter(dist -> !dist.getVariable().isParameterVariable())
                      .filter(dist -> !hiddenToNode.containsKey(dist.getVariable()))
                      .map(dist -> {
                          Node node = new Node(dist);
                          map.put(dist.getVariable(), node);
                          return node;
                      })
                      .collect(Collectors.toList());
  
              this.replicatedVarsToNode.add(map);
              replicatedNodes.add(tmpNodes);
          }
  
  
          for (int i = 0; i < nReplications; i++) {
              for (Node node : replicatedNodes.get(i)) {
                  final int slice = i;
                  node.setParents(node.getPDist().getConditioningVariables().stream().map(var -> this.getNodeOfVar(var, slice)).collect(Collectors.toList()));
                  node.getPDist().getConditioningVariables().stream().forEach(var -> this.getNodeOfVar(var, slice).getChildren().add(node));
              }
          }
  
          for (Variable localVar : this.localHiddenVars) {
              Node localNode = this.hiddenToNode.get(localVar);
              localNode.setParents(localNode.getPDist().getConditioningVariables().stream().map(var -> this.getNodeOfVar(var, 0)).collect(Collectors.toList()));
              localNode.getPDist().getConditioningVariables().stream().forEach(var -> this.getNodeOfVar(var, 0).getChildren().add(localNode));
              if (dynamic)
                  localNode.getParents().stream().forEach(node -> node.setActive(false));
          }
  
  
  
          List<Node> allNodes = new ArrayList();
  
          allNodes.addAll(this.nonReplictedNodes);
  
          allNodes.addAll(localHiddenNodes);
  
          for (int i = 0; i < nReplications; i++) {
              allNodes.addAll(this.replicatedNodes.get(i));
          }
  
          this.vmp.setNodes(allNodes);
      }
  
      public <E extends EF_UnivariateDistribution> E getEFParameterPosterior(Variable var) {
  
          return (E)this.nonReplicatedVarsToNode.get(var).getQDist();
      }
  
      public Node getNodeOfVar(Variable variable, int slice) {
          if (variable.isParameterVariable())
              return this.nonReplicatedVarsToNode.get(variable);
          else if (this.hiddenToNode.containsKey(variable))
              return this.hiddenToNode.get(variable);
          else
              return this.replicatedVarsToNode.get(slice).get(variable);
      }
  
  }