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The Java version of Numenta's HTM technology
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/* ---------------------------------------------------------------------
 * Numenta Platform for Intelligent Computing (NuPIC)
 * Copyright (C) 2014, Numenta, Inc.  Unless you have an agreement
 * with Numenta, Inc., for a separate license for this software code, the
 * following terms and conditions apply:
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License version 3 as
 * published by the Free Software Foundation.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
 * See the GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see http://www.gnu.org/licenses.
 *
 * http://numenta.org/licenses/
 * ---------------------------------------------------------------------
 */

package org.numenta.nupic.research;

import java.util.LinkedHashMap;
import java.util.LinkedHashSet;
import java.util.Map;
import java.util.Set;

import org.numenta.nupic.Connections;
import org.numenta.nupic.model.Cell;
import org.numenta.nupic.model.Column;
import org.numenta.nupic.model.DistalDendrite;
import org.numenta.nupic.model.Synapse;

/**
 * Contains a snapshot of the state attained during one computational
 * call to the {@link TemporalMemory}. The {@code TemporalMemory} uses
 * data from previous compute cycles to derive new data for the current cycle
 * through a comparison between states of those different cycles, therefore
 * this state container is necessary.
 * 
 * @author David Ray
 */
public class ComputeCycle {
    Set activeCells = new LinkedHashSet();
    Set winnerCells = new LinkedHashSet();
    Set predictiveCells = new LinkedHashSet();
    Set successfullyPredictedColumns = new LinkedHashSet();
    Set activeSegments = new LinkedHashSet();
    Set learningSegments = new LinkedHashSet();
    Map> activeSynapsesForSegment = new LinkedHashMap>();
    
    
    /**
     * Constructs a new {@code ComputeCycle}
     */
    public ComputeCycle() {}
    
    /**
     * Constructs a new {@code ComputeCycle} initialized with
     * the connections relevant to the current calling {@link Thread} for
     * the specified {@link TemporalMemory}
     * 
     * @param   c       the current connections state of the TemporalMemory
     */
    public ComputeCycle(Connections c) {
        this.activeCells = new LinkedHashSet(c.getActiveCells());
        this.winnerCells = new LinkedHashSet(c.getWinnerCells());
        this.predictiveCells = new LinkedHashSet(c.getPredictiveCells());
        this.successfullyPredictedColumns = new LinkedHashSet(c.getSuccessfullyPredictedColumns());
        this.activeSegments = new LinkedHashSet(c.getActiveSegments());
        this.learningSegments = new LinkedHashSet(c.getLearningSegments());
        this.activeSynapsesForSegment = new LinkedHashMap>(c.getActiveSynapsesForSegment());
    }
    
    /**
     * Returns the current {@link Set} of active cells
     * 
     * @return  the current {@link Set} of active cells
     */
    public Set activeCells() {
        return activeCells;
    }
    
    /**
     * Returns the current {@link Set} of winner cells
     * 
     * @return  the current {@link Set} of winner cells
     */
    public Set winnerCells() {
        return winnerCells;
    }
    
    /**
     * Returns the {@link Set} of predictive cells.
     * @return
     */
    public Set predictiveCells() {
        return predictiveCells;
    }
    
    /**
     * Returns the {@link Set} of columns successfully predicted from t - 1.
     * 
     * @return  the current {@link Set} of predicted columns
     */
    public Set successfullyPredictedColumns() {
        return successfullyPredictedColumns;
    }
    
    /**
     * Returns the Set of learning {@link DistalDendrite}s
     * @return
     */
    public Set learningSegments() {
        return learningSegments;
    }
    
    /**
     * Returns the Set of active {@link DistalDendrite}s
     * @return
     */
    public Set activeSegments() {
        return activeSegments;
    }
    
    /**
     * Returns the mapping of Segments to active synapses in t-1
     * @return
     */
    public Map> activeSynapsesForSegment() {
        return activeSynapsesForSegment;
    }
}