Subject: [Isis-fish-users] script calibration un seul paramètre
From: Sigrid LEHUTA <[email-masked]>
To: isis-user <[email-masked]>
Date: Thu, 17 Jun 2010 16:38:28 +0200
List-Id: <isis-fish-users.list.isis-fish.org>

Hello
Voici un script de calibration de la capturabilité quand il n y a qu un 
seul paramètre qui semble assez efficace (précision = 1/32 du pas 
initial en 11 simulations).
A adapter aux fonctions objectif de chacun (ici captures mensuelles en 
poids) mais la partie algo (le before simulation) est générique.
(déposé aussi sur le wiki).
A+
Sigrid

-- 
Sigrid LEHUTA
  ~ ><> ~
  
Doctorante
Département Ecologie et Modèles pour l'Halieutique
IFREMER, rue de l'ile d'Yeu BP 21105 
44311 Nantes Cedex 03
Tél : +33 (0)2 40 37 41 23 (interne : 8123)

package analyseplans;
import static org.nuiton.i18n.I18n._;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import scripts.ResultName;
import java.io.*;
import java.util.*;
import org.nuiton.math.matrix.*;
import org.nuiton.topia.*;// pour pouvoir utiliser la methode StringUtil.toDouble()
import org.nuiton.util.*;// pour pouvoir utiliser la methode StringUtil.toDouble()
import fr.ifremer.isisfish.*;
import fr.ifremer.isisfish.types.*;
import fr.ifremer.isisfish.simulator.SimulationContext;
import fr.ifremer.isisfish.types.Date;
import fr.ifremer.isisfish.entities.*;
import fr.ifremer.isisfish.simulator.AnalysePlan;
import fr.ifremer.isisfish.simulator.AnalysePlanContext;
import fr.ifremer.isisfish.simulator.SimulationParameter;
import fr.ifremer.isisfish.datastore.SimulationStorage;
import fr.ifremer.isisfish.datastore.ResultStorage;

/**
 * Calibration_1parameter.java
 * this program computes successive values for the catchability parameter in order to minimise the sum of squarres difference between observed and simulated catches. 
 * not generic ! comments indicate where the code must be adaptated to each fishery 
 *
 * Created: 07/06/10
 *
 * @author   <>
 * @version $Revision: 3.2 $
 *
 * Last update: $Date: 2007/05/24 09:29:18 $
 * by : $Author: bpoussin $
 */
public class Calibration_1param implements AnalysePlan {

    /** to use log facility, just put in your code: log.info("..."); */
    static private Log log = LogFactory.getLog(Calibration_1param.class);
@Doc("path and name of the file where parameter values and performance criteria are saved")
    public String param_nomFileHisto = "Inputs_Anchois/CalibrationSardine/histo.csv";
    File exportHistoric = new File (param_nomFileHisto);
    protected String exportHisto = "";
@Doc("population concerned")
    public Population param_Population = null;
@Doc("values for the 5 initial experiments in increasing order with a constant increment")
    public Double param_M1 = 0.98e-4;// devient un parametre du plan d analyse
    public Double param_M2 = 1.0e-4;// devient un parametre du plan d analyse
    public Double param_M3 = 1.02e-4;// devient un parametre du plan d analyse
    public Double param_M4 = 1.04e-4;// devient un parametre du plan d analyse
    public Double param_M5 = 1.06e-4;// devient un parametre du plan d analyse
		
@Doc("path for the file that contains observed values used for calibration")
    public String param_nomfichier_debarquements = "Inputs_Anchois/CalibrationSardine/DebarquementsSardine.csv";
    protected File  debarquementsObserves;
    protected MatrixND matrixDebarquement;
	protected String[] strNomsNous;
	protected List<Strategy> strNous;
	protected List<Double> q;
	protected List<Double> Fobj = new ArrayList<Double>();

// TO DO : matrix containing simulated values to compare to observed values	
    public String [] necessaryResult = {
            ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP,		
    };

    public String[] getNecessaryResult() {
        return this.necessaryResult;
    }

    /**
     * Permet d'afficher a l'utilisateur une aide sur le plan.
     * @return L'aide ou la description du plan
     */
    public String getDescription() throws Exception {
        return _("Single Factor Optimization from Walters et al., 1991");
   }

    /**
     * Appele au demarrage de la simulation, cette methode permet d'initialiser
     * des valeurs
     * @param simulation La simulation pour lequel on utilise cette regle
     */
    public void init(AnalysePlanContext context) throws Exception {
    	// chargement de la matrice de valeurs observées
		if (param_nomfichier_debarquements==null || "".equals(param_nomfichier_debarquements)){
    		debarquementsObserves = FileUtil.getFile(".*.csv", "fichier csv");
    	} else {
    		debarquementsObserves = new File(param_nomfichier_debarquements);
    	}
		
		// creation of the vector of catchability values
    	 q = new ArrayList<Double>();
    	 q.add(param_M1);
		 q.add(param_M2);
		 q.add(param_M3);
		 q.add(param_M4);
		 q.add(param_M5);
		
		// Creation of the matrix of observed values : TO DO
		// Here the observed values are landings (weight) per strategy per month
		int nbYear = context.getParam().getNumberOfYear();
		List<Strategy> allStrategies = context.getParam().getStrategies();
		// TO DO : names of strategies in apparition order in the file of observed landings 
		// also used to keep only certain strategies if necessary
		strNomsNous = new String[]{"PelProfil1","PelProfil2","BolBasques","BolBretons"};     		
		strNous = new ArrayList<Strategy>();
		for(String strNomCurrent : strNomsNous){
			for (Strategy s : allStrategies){
				if(s.getName().equals(strNomCurrent)){
					strNous.add(s);
				}
			}
		}
		
		// create the vector of dates at which catches are observed 
		int dateFin = nbYear*12;
		List<Date> dates = new ArrayList<Date>();
		for(int i=0; i<dateFin;i++){
			dates.add(new Date(i));
		}
		
    	TopiaContext db = context.getParam().getRegion().getStorage().beginTransaction();
    	Population pop = (Population)db.findByTopiaId(param_Population.getTopiaId());
    	
		// create the matrix of observed values which correspondant dimension
		matrixDebarquement = MatrixFactory.getInstance().create(
				"matDebarq",
				new List[]{dates,strNous},
                new String[]{"Dates","strategies"});
		matrixDebarquement.importCSV(new FileReader(debarquementsObserves),new int []{0,0});

    	db.closeContext();
    }

    /**
     * Call before each simulation
     * @param context plan context
     * @param nextSimulation storage used for next simulation
     * @return true if we must do next simulation, false to stop plan
     * @throws Exception
     */
 
    public boolean beforeSimulation(AnalysePlanContext context, SimulationStorage nextSimulation) throws Exception {
   	boolean doNext = true;

    int number = nextSimulation.getParameter().getAnalysePlanNumber();
	log.info("before simulation" + number);
     
	// TO DO : limit the number of experiments	 
	 if(number <31){ 
	 /** the rest of the code is generic, after the 5 first experiments were run, two new experiments are generated with values of q 
	 at intervals equal to one-half the original interval on either side of the best value found in the initial set. The procedure is repeted, the interval beeing halved each time.
	 **/
		double pasInitial = q.get(1)-q.get(0);
		if (number <5) {
		log.info("number<5");
   		changeDB(q.get(number), nextSimulation);
		}else if(number == 5){
			int min = compareTo(Fobj);
			double newq = q.get(min);
			double pas = pasInitial/2;
			newq = newq - pas;
			q.add(newq);
		}else {
			if(!isPair(number)){
				int min = compareTo(Fobj);
				double newq = q.get(min);
				int puiss = (number-3)/2;
				double pas = pasInitial/Math.pow(2.0,puiss);
				newq = newq - pas;
				q.add(newq);
			}else{
				int min = compareTo(Fobj.subList(0,number-1));
				double newq = q.get(min);
				int puiss = (number - 4)/2;
				double pas = pasInitial/Math.pow(2.0,puiss);
				newq = newq + pas;
				q.add(newq);
			}
		}	
        	changeDB(q.get(number), nextSimulation);
    	}else doNext = false;
    	return doNext;
 }// fin du before simulation

    /**

     * Call after each simulation, compute criteria for last simulation
     * @param context plan context
     * @param nextSimulation storage used for next simulation
     * @return true if we must do next simulation, false to stop plan
     * @throws Exception
    */

    public boolean afterSimulation(AnalysePlanContext context, SimulationStorage lastSimulation) throws Exception {
        int number = lastSimulation.getParameter().getAnalysePlanNumber();
        //int number = context.getNumber();
		System.out.println("after simulation" + number);
        ResultStorage result = lastSimulation.getResultStorage();

		// Pour sommer sur certaines classes les resultats :
        MatrixND L2 = result.getMatrix(param_Population, ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP);   		
	   List<Strategy> str = (List<Strategy>)L2.getSemantic(1);
		System.out.println("import de la matrice des debarquements");

		//pour reccuperer les index des strategies francaises
		int comptSt = 0;
		int comptTab = 0;
		int[] elem = new int[strNous.size()]; 
		for(Strategy st : str){
			if (strNous.contains(st)){
			elem[comptTab] = comptSt;
			comptTab +=1;
			}
		comptSt += 1;	
		}

		MatrixND L = L2.getSubMatrix(1,elem).copy(); 
		
		L = L.sumOverDim(3);// sum sur les groupes
        L = L.sumOverDim(2);// sum sur les metiers
        L = L.sumOverDim(4);// sum sur les zones
		L = L.reduce(); // supprime les dimensions de taille 0

	///////////////////Calcul de la fonction objectif//////////////////
	log.info("calcul de la fobj");       
	System.out.println("dim de L" + " " + Arrays.toString(L.getDim()));
	System.out.println("matrice de debarquements : "+ L);
		double crit = 0;
        for ( MatrixIterator g = L.iterator(); g.hasNext();){
            g.next();
		//boucle sur les dates et les flottilles
            Strategy s = (Strategy)g.getSemanticsCoordinates()[1];
			Date dat = (Date)g.getSemanticsCoordinates()[0];
           // int [] dim = g.getCoordinates();
            double obs = matrixDebarquement.getValue(dat,s);
			double simules = g.getValue();
			double sum_pond = obs-simules;
            crit += Math.pow(sum_pond, 2); // crit = crit + (obs-simules)^2
        }// fin du for
		System.out.println("critere " + number + " = " + crit );
		Fobj.add(crit);

	//ecriture de la table historic
	exportHisto += q.get(number) +";"+ Fobj.get(number) + "\n";
	org.nuiton.util.FileUtil.writeString(exportHistoric, exportHisto);

	return true;
	}// fin du after simulation

    /**
     * Modify nextSimulation database with q1 and q2 in exp.
     * @param exp
     * @param nextSimulation
     * @throws Exception
     */

    protected void changeDB(Double q, SimulationStorage nextSimulation) throws Exception {
	//methode appelee dans before simualtion
		TopiaContext db = nextSimulation.getStorage().beginTransaction();//ouvrir un context pour modifier les donnees
		Population pop = (Population)db.findByTopiaId(param_Population.getTopiaId()); //reccupere la pop ciblee
		MatrixND c = pop.getCapturability(); // reccupere la matrice de 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		for (MatrixIterator i = c.iterator(); i.hasNext();){
			i.next();
			i.setValue(q);		
		}//fin du for
		db.commitTransaction(); // effectue la modification
		db.closeContext(); // ferme le context
	}

	public int compareTo(List<Double> listCrit) {
		int N = listCrit.size(); 
		System.out.println("taille de la liste :"+N);
		int minimum=0;
    		for(int i=0; i<N; i++) {
    			System.out.println("i = "+i);
			if (listCrit.get(i)<listCrit.get(minimum)){minimum = i;}
		} 
    	return minimum;
    }

    public int compare2(Double f1,Double f2){
    int minimum=0;
    if (f2<f1) minimum = 1;
    return minimum;
    }

	public boolean isPair(int nombre){
		return (nombre%2 == 0) ;
	}

}

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