Prediction.h

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/*
 * Copyright (C) 2007-2011 RobotCub Consortium, European Commission FP6 Project IST-004370
 * author:  Arjan Gijsberts
 * email:   arjan.gijsberts@iit.it
 * website: www.robotcub.org
 * Permission is granted to copy, distribute, and/or modify this program
 * under the terms of the GNU General Public License, version 2 or any
 * later version published by the Free Software Foundation.
 *
 * A copy of the license can be found at
 * http://www.robotcub.org/icub/license/gpl.txt
 *
 * 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
 */
 
#ifndef LM_PREDICTION__
#define LM_PREDICTION__
 
#include <string>
#include <cassert>
 
#include <yarp/os/ConnectionReader.h>
#include <yarp/os/ConnectionWriter.h>
#include <yarp/os/Portable.h>
#include <yarp/sig/Vector.h>
 
namespace iCub {
namespace learningmachine {
 
class Prediction : public yarp::os::Portable {
protected:
    yarp::sig::Vector prediction;
 
    yarp::sig::Vector variance;
 
    bool varianceSet;
 
public:
    Prediction() {
        this->setPrediction(yarp::sig::Vector(0));
        this->setVariance(yarp::sig::Vector(0));
    }
 
    Prediction(const yarp::sig::Vector& prediction) {
        this->setPrediction(prediction);
        this->setVariance(yarp::sig::Vector(0));
    }
 
    Prediction(const yarp::sig::Vector& prediction, const yarp::sig::Vector& variance) {
        this->setPrediction(prediction);
        this->setVariance(variance);
    }
 
    unsigned int size() {
        return this->prediction.size();
    }
 
    yarp::sig::Vector getPrediction() {
        return this->prediction;
    }
 
    void setPrediction(const yarp::sig::Vector& prediction) {
        this->prediction = prediction;
    }
 
    yarp::sig::Vector getVariance() {
        return this->variance;
    }
 
    void setVariance(const yarp::sig::Vector& variance) {
        assert(prediction.size() == variance.size() || variance.size() == 0);
        this->variance = variance;
        this->varianceSet = (variance.size() > 0);
    }
 
    bool hasVariance() {
        return this->varianceSet;
    }
 
    std::string toString() {
        std::string out = this->prediction.toString().c_str();
        if(this->hasVariance()) {
            out += std::string(" +/- ") + this->variance.toString().c_str();
        }
        return out;
    }
 
    /*
     * Inherited from Portable.
     */
    bool write(yarp::os::ConnectionWriter& connection) const {
        // follows PortablePair implementation
        connection.appendInt32(BOTTLE_TAG_LIST);
        connection.appendInt32(2);
 
        bool ok = this->prediction.write(connection);
        if (ok) {
            ok = this->variance.write(connection);
        }
 
        if (ok) {
            connection.convertTextMode();
        }
 
        return ok;
    }
 
    /*
     * Inherited from Portable.
     */
    bool read(yarp::os::ConnectionReader& connection) {
        // follows PortablePair implementation
        connection.convertTextMode();
 
        int header = connection.expectInt32();
        if(header != BOTTLE_TAG_LIST) {
            return false;
        }
 
        int len = connection.expectInt32();
        if(len != 2) {
            return false;
        }
 
        bool ok = this->prediction.read(connection);
        if (ok) {
            ok = this->variance.read(connection);
        }
        this->varianceSet = (this->variance.size() > 0);
        return ok;
    }
 
    /*
     * Inherited from Portable.
     */
    virtual void onCompletion() {
        this->prediction.onCompletion();
        this->variance.onCompletion();
    }
 
};
 
 
} // learningmachine
} // iCub
 
#endif