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r77 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 17 Mar '09

17 Mar '09

Author: jcouteau Date: 2009-03-17 14:32:13 +0000 (Tue, 17 Mar 2009) New Revision: 77 Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java Log: Working expand grid sensitivity calculator with full analysis. Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-16 16:50:28 UTC (rev 76) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-17 14:32:13 UTC (rev 77) @@ -22,6 +22,8 @@ import java.io.Serializable; import java.util.List; +import org.apache.commons.logging.Log; +import org.apache.commons.logging.LogFactory; import org.codelutin.j2r.REngine; import org.codelutin.j2r.RProxy; import org.codelutin.util.FileUtil; @@ -47,6 +49,10 @@ public class SensitivityCalculatorJavaExpandGrid implements SensitivityCalculator { + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory + .getLog(SensitivityCalculatorJavaExpandGrid.class); + /** * Retourne vrai si le calculateur sait gerer la cardinalité * des facteurs continue. @@ -106,7 +112,7 @@ * result; } - if (factor.getDomain() instanceof ContinuousDomain) { + /*if (factor.getDomain() instanceof ContinuousDomain) { factor .setValueForIdentifier((((ContinuousDomain<Double>) factor .getDomain()).getMaxBound() - ((ContinuousDomain<Double>) factor @@ -114,14 +120,15 @@ / rest + ((ContinuousDomain<Double>) factor .getDomain()).getMinBound()); - } + }*/ factor.setValueForIdentifier(rest); experimentScenario.addFactor(factor); } thisExperimentScenarios.add(experimentScenario); - thisExperiment.setScenarios(thisExperimentScenarios); + } + thisExperiment.setScenarios(thisExperimentScenarios); /* * Call R to save the data for result analysis @@ -147,6 +154,7 @@ } vector = vector + ")"; engine.voidEval(vector); + log.info("Message sent to R : " + vector); } @@ -155,22 +163,29 @@ for (int j = 0; j < factorNumber; j++) { if (j < factorNumber - 1) { dataframe = dataframe + "factor" + j + "=factor(factor" + j - + "))"; + + "),"; } else { dataframe = dataframe + "factor" + j + "=factor(factor" + j - + "),"; + + "))"; } } engine.voidEval(dataframe); + log.info("Message sent to R : " + dataframe); // Set output directory engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + "\")"); + log.info("Message sent to R : " + "setwd(\"" + + outputdirectory.getAbsolutePath() + "\")"); // Export the data.frame object for the second run in a .expandgrid file - engine.voidEval("dput(data,file=\".expandgrid\")"); + engine.voidEval("write.csv(data,file=\".expandgrid.csv\")"); + log + .info("Message sent to R : write.csv(data,file=\".expandgrid\")"); + engine.terminate(); + } catch (Exception e) { e.printStackTrace(); // Error while processing @@ -194,17 +209,29 @@ for (int k = 0; k < sensitivityNumber; k++) { + // Set output directory + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + log.info("Message sent to R : setwd(\"" + + outputdirectory.getAbsolutePath() + "\")"); + //Get back the scenarios - engine.voidEval("factors<-dget(\".expandgrid\")"); + //engine.voidEval("factors<-read.csv(\".expandgrid.csv\",row.names=1,col.names=1)"); + engine.voidEval("factors<-read.csv(\".expandgrid.csv\")"); + log + .info("Message sent to R : factors<-read.csv(\".expandgrid.csv\")"); //Get back the factors number - int factorNumber = (Integer) engine.eval("length(factors)"); + int factorNumber = ((Double)engine.eval("length(factors)-1")).intValue(); + //factorNumber=factorNumber-1; //Create the results vectors String result = "result<-c("; for (int l = 0; l < simulationStorages.size(); l++) { File importFile = new File( - simulationStorages.get(l).getDirectory().toString(), + simulationStorages.get(l).getDirectory().toString() + + File.separator + + SimulationStorage.RESULT_EXPORT_DIRECTORY, ExportStorage .getExport( simulationStorages @@ -232,10 +259,12 @@ } result = result + ")"; engine.voidEval(result); + log.info("Message sent to R : " + result); //Create the dataforaov data.frame String dataframe = "dataforaov<-data.frame(factors,result=result)"; engine.voidEval(dataframe); + log.info("Message sent to R : " + dataframe); //Call aov() String aovCall = "aovresult<-aov(result~"; @@ -247,6 +276,7 @@ } } engine.voidEval(aovCall); + log.info("Message sent to R : " + aovCall); /*Export the results *Export format is csv, data separated by ',' @@ -257,36 +287,62 @@ //Compute Sum of Squares and Sensitivity indices engine.voidEval("SoS<-summary(aovresult)[[1]][1:" + factorNumber + ",2]"); + log.info("Message sent to R : SoS<-summary(aovresult)[[1]][1:" + + factorNumber + ",2]"); engine - .voidEval("names(SoS)<-dimnames(summary(aovresult)[[1]])[[1]]"); + .voidEval("names(SoS)<-dimnames(summary(aovresult)[[1]])[[1]][1:" + + factorNumber + "]"); + log + .info("Message sent to R : names(SoS)<-dimnames(summary(aovresult)[[1]])[[1]][1:" + + factorNumber + "]"); engine.voidEval("IndSensibilite<-SoS/sum(SoS)"); + log.info("Message sent to R : IndSensibilite<-SoS/sum(SoS)"); //Create a data.frame to export sensitivity important results in one file. engine.voidEval("exportsensitivity=data.frame(SoS[1:" + factorNumber + "],IndSensibilite[1:" + factorNumber + "])"); + log + .info("Message sent to R : exportsensitivity=data.frame(SoS[1:" + + factorNumber + + "],IndSensibilite[1:" + + factorNumber + "])"); engine .voidEval("names(exportsensitivity)<-c(\"Sum Of Squares\",\"Sensitivity indices\")"); + log + .info("Message sent to R : names(exportsensitivity)<-c(\"Sum Of Squares\",\"Sensitivity indices\")"); /*Set the export directory *Export directory is the first simulation export directory. */ engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + "\")"); + log.info("Message sent to R : setwd(\"" + + outputdirectory.getAbsolutePath() + "\")"); //Save the results with the scenarios. engine.voidEval("write.csv(dataforaov,\"" + simulationStorages.get(0).getParameter() .getSensitivityExportNames().get(k) - + "_Results.csv"); + + "_Results.csv\")"); + log.info("Message sent to R : write.csv(dataforaov,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + "_Results.csv\")"); //Save the sensitivity indices engine.voidEval("write.csv(exportsensitivity,\"" + simulationStorages.get(0).getParameter() .getSensitivityExportNames().get(k) + "_SensitivityIndices.csv\")"); + log.info("Message sent to R : write.csv(exportsensitivity,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + "_SensitivityIndices.csv\")"); //FIXME export through java to enable export when using Rserve (when distant Rserve). + engine.terminate(); } + log.info("end"); } catch (Exception e) { e.printStackTrace();

1 0

r76 - trunk/sensitivity
by chatellier＠users.labs.libre-entreprise.org 16 Mar '09

16 Mar '09

Author: chatellier Date: 2009-03-16 16:50:28 +0000 (Mon, 16 Mar 2009) New Revision: 76 Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Ajout d'une methode sur les calculateurs permettant de savoir s'il savent gerer la cardinalit?\195?\169 ou pas. Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-16 10:27:55 UTC (rev 75) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-16 16:50:28 UTC (rev 76) @@ -47,6 +47,16 @@ public class SensitivityCalculatorJavaExpandGrid implements SensitivityCalculator { + /** + * Retourne vrai si le calculateur sait gerer la cardinalité + * des facteurs continue. + * + * @return <tt>true</tt> s'il sait la gerer + */ + public boolean canManageCardinality() { + return false; + } + public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) throws SensitivityException { Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-16 10:27:55 UTC (rev 75) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-16 16:50:28 UTC (rev 76) @@ -58,6 +58,16 @@ private static Log log = LogFactory .getLog(SensitivityCalculatorRMorris.class); + /** + * Retourne vrai si le calculateur sait gerer la cardinalité + * des facteurs continue. + * + * @return <tt>true</tt> s'il sait la gerer + */ + public boolean canManageCardinality() { + return false; + } + public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) { double[] dataframe = new double[0];

1 0

r75 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 16 Mar '09

16 Mar '09

Author: jcouteau Date: 2009-03-16 10:27:55 +0000 (Mon, 16 Mar 2009) New Revision: 75 Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Adapt analysis to Interface changes. Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-13 09:30:36 UTC (rev 74) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-16 10:27:55 UTC (rev 75) @@ -47,7 +47,7 @@ public class SensitivityCalculatorJavaExpandGrid implements SensitivityCalculator { - public SensitivityScenarios compute(DesignPlan plan) + public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) throws SensitivityException { int k = 1; //number of sensitivity scenarios (initialization) @@ -112,45 +112,83 @@ thisExperimentScenarios.add(experimentScenario); thisExperiment.setScenarios(thisExperimentScenarios); } + + /* + * Call R to save the data for result analysis + */ + int scenariosNumber = thisExperimentScenarios.size(); + + REngine engine = new RProxy(); + try { + //Create the factors vectors + for (int j = 0; j < factorNumber; j++) { + String vector = "factor" + j + "<-c("; + for (int i = 0; i < scenariosNumber; i++) { + if (i < (scenariosNumber - 1)) { + vector = vector + + thisExperimentScenarios.get(i).getFactors() + .get(j).getValue() + ","; + } else { + vector = vector + + thisExperimentScenarios.get(i).getFactors() + .get(j).getValue(); + } + + } + vector = vector + ")"; + engine.voidEval(vector); + + } + + //Create the data data.frame from the factors + String dataframe = "data<-data.frame("; + for (int j = 0; j < factorNumber; j++) { + if (j < factorNumber - 1) { + dataframe = dataframe + "factor" + j + "=factor(factor" + j + + "))"; + } else { + dataframe = dataframe + "factor" + j + "=factor(factor" + j + + "),"; + } + + } + engine.voidEval(dataframe); + + // Set output directory + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + + // Export the data.frame object for the second run in a .expandgrid file + engine.voidEval("dput(data,file=\".expandgrid\")"); + + } catch (Exception e) { + e.printStackTrace(); + // Error while processing + } + return thisExperiment; } - public void analyzeResult(SensitivityScenarios sensitivityScenarios, - List<SimulationStorage> simulationStorages) - throws SensitivityException { + public void analyzeResult(List<SimulationStorage> simulationStorages, + File outputdirectory) throws SensitivityException { - int scenariosNumber = sensitivityScenarios.getScenarios().size(); - int factorNumber = sensitivityScenarios.getScenarios().get(0) - .getFactors().size(); - REngine engine = new RProxy(); try { + /*int scenariosNumber = sensitivityScenarios.getScenarios().size(); + int factorNumber = sensitivityScenarios.getScenarios().get(0) + .getFactors().size();*/ + int sensitivityNumber = simulationStorages.get(0).getParameter() .getSensitivityExportNames().size(); for (int k = 0; k < sensitivityNumber; k++) { - //Create the params vectors - for (int j = 0; j < factorNumber; j++) { - String vector = "factor" + j + "<-c("; - for (int i = 0; i < scenariosNumber; i++) { - if (i < (scenariosNumber - 1)) { - vector = vector - + sensitivityScenarios.getScenarios() - .get(i).getFactors().get(j) - .getValue() + ","; - } else { - vector = vector - + sensitivityScenarios.getScenarios() - .get(i).getFactors().get(j) - .getValue(); - } + //Get back the scenarios + engine.voidEval("factors<-dget(\".expandgrid\")"); - } - vector = vector + ")"; - engine.voidEval(vector); - } + //Get back the factors number + int factorNumber = (Integer) engine.eval("length(factors)"); //Create the results vectors String result = "result<-c("; @@ -186,13 +224,7 @@ engine.voidEval(result); //Create the dataforaov data.frame - String dataframe = "dataforaov<-data.frame("; - for (int j = 0; j < factorNumber; j++) { - dataframe = dataframe + "factor" + j + "=factor(factor" + j - + "),"; - - } - dataframe = dataframe + "result=result)"; + String dataframe = "dataforaov<-data.frame(factors,result=result)"; engine.voidEval(dataframe); //Call aov() @@ -206,27 +238,44 @@ } engine.voidEval(aovCall); - //Export the results - /* - * SoS<-anova(aovresult)[1:3,2] - * IndSensibilite<-SoS/sum(SoS) - * write.csv(IndSensibilite) + /*Export the results + *Export format is csv, data separated by ',' + *Results Export name is sensitivityExportName_Results.csv + *Sensitivity Indices export name is sensitivityExportName_SensitivityIndices.csv */ - engine.voidEval("SoS<-anova(aovresult)[1:" + factorNumber - + ",2]"); - engine.voidEval("names(SoS)<-dimnames(anova(aovtest))[[1]][1:" - + factorNumber + "]"); + //Compute Sum of Squares and Sensitivity indices + engine.voidEval("SoS<-summary(aovresult)[[1]][1:" + + factorNumber + ",2]"); + engine + .voidEval("names(SoS)<-dimnames(summary(aovresult)[[1]])[[1]]"); engine.voidEval("IndSensibilite<-SoS/sum(SoS)"); - engine.voidEval("setwd(\"" - + simulationStorages.get(0).getDirectory().toString() + + //Create a data.frame to export sensitivity important results in one file. + engine.voidEval("exportsensitivity=data.frame(SoS[1:" + + factorNumber + "],IndSensibilite[1:" + factorNumber + + "])"); + engine + .voidEval("names(exportsensitivity)<-c(\"Sum Of Squares\",\"Sensitivity indices\")"); + + /*Set the export directory + *Export directory is the first simulation export directory. + */ + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + "\")"); - engine - .voidEval("write.csv(IndSensibilite,\"" - + simulationStorages.get(0).getParameter() - .getSensitivityExportNames().get(k) - + ".csv\")"); - //FIXME export through java to enable export when using Rserve + + //Save the results with the scenarios. + engine.voidEval("write.csv(dataforaov,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + "_Results.csv"); + + //Save the sensitivity indices + engine.voidEval("write.csv(exportsensitivity,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + "_SensitivityIndices.csv\")"); + //FIXME export through java to enable export when using Rserve (when distant Rserve). } } catch (Exception e) { Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-13 09:30:36 UTC (rev 74) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-16 10:27:55 UTC (rev 75) @@ -31,8 +31,6 @@ import org.codelutin.math.matrix.MatrixND; import org.codelutin.util.FileUtil; -import scripts.GravityModel; - import fr.ifremer.isisfish.datastore.ExportStorage; import fr.ifremer.isisfish.datastore.SimulationStorage; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; @@ -51,16 +49,17 @@ * @author jcouteau * @version $Revision$ * - * Last update : $Date$ - * By : $Author$ + * Last update : $Date$ By : + * $Author$ */ public class SensitivityCalculatorRMorris implements SensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ - private static Log log = LogFactory.getLog(SensitivityCalculatorRMorris.class); - - public SensitivityScenarios compute(DesignPlan plan) { + private static Log log = LogFactory + .getLog(SensitivityCalculatorRMorris.class); + public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) { + double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); @@ -175,15 +174,24 @@ // Load sensitivity package into R (if package already loaded, // nothing happens. engine.voidEval("library(sensitivity)"); + // Run sensitivity analysis engine.voidEval(rInstruction); + + // Set output directory + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + + // Export the morris object for the second run in a .morris file + engine.voidEval("dput(a,file=\".morris\")"); + // Get back experiment plan dataframe = (double[]) engine.eval("a$X"); if (log.isDebugEnabled()) { log.debug("rInstruction = " + rInstruction); } - + nbExperiments = dataframe.length / factorNumber; } catch (RException e) { @@ -231,21 +239,30 @@ } - public void analyzeResult(SensitivityScenarios sensitivityScenarios, - List<SimulationStorage> simulationStorages) { + public void analyzeResult(List<SimulationStorage> simulationStorages, + File outputdirectory) { - int scenariosNumber = sensitivityScenarios.getScenarios().size(); - REngine engine = new RProxy(); try { + //Set the working directory (for import and exports) + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + + // Export the morris object for the second run in a .morris file + engine.voidEval("a<-dget(\".morris\")"); + + /*int scenariosNumber = sensitivityScenarios.getScenarios().size();*/ + int scenariosNumber = (Integer) engine + .eval("length(y$X)/y$factors"); + int sensitivityNumber = simulationStorages.get(0).getParameter() .getSensitivityExportNames().size(); for (int k = 0; k < sensitivityNumber; k++) { - // Creates the R expression. - String rInstruction = "tell(x,y=c("; + // Creates the R expression to import results in R + String rInstruction = "results<-c("; for (int l = 0; l < scenariosNumber; l++) { File importFile = new File( simulationStorages.get(l).getDirectory().toString(), @@ -280,22 +297,30 @@ // Load sensitivity package into R (if package already loaded, // nothing happens. engine.voidEval("library(sensitivity)"); + // Send the simulation results engine.voidEval(rInstruction); + + //Compute results + engine.voidEval("tell(x,y=results"); + // Get back the sensitivity results, mu, mu star and sigma. engine.voidEval("mu<-apply(x$ee, 2, mean)"); engine .voidEval("mu.star <- apply(x$ee, 2, function(x) mean(abs(x)))"); engine.voidEval("sigma <- apply(x$ee, 2, sd)"); + + //Create the data.frame of sensitivity indices for export purpose engine.voidEval("df=data.frame(mu,mu.star,sigma)"); + + // engine.voidEval("setwd(\"" + simulationStorages.get(0).getDirectory().toString() + "\")"); - engine - .voidEval("write.csv(df,\"" - + simulationStorages.get(0).getParameter() - .getSensitivityExportNames().get(k) - + ".csv\")"); + engine.voidEval("write.csv(df,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + "_SensitivityIndices.csv\")"); //FIXME export through java to enable export when using Rserve }

1 0

r74 - trunk/exports
by chatellier＠users.labs.libre-entreprise.org 13 Mar '09

13 Mar '09

Author: chatellier Date: 2009-03-13 09:30:36 +0000 (Fri, 13 Mar 2009) New Revision: 74 Modified: trunk/exports/SensitivityCapturesPoidsPopage.java Log: Erreur de copi?\195?\169/coll?\195?\169 Modified: trunk/exports/SensitivityCapturesPoidsPopage.java =================================================================== --- trunk/exports/SensitivityCapturesPoidsPopage.java 2009-03-12 20:02:47 UTC (rev 73) +++ trunk/exports/SensitivityCapturesPoidsPopage.java 2009-03-13 09:30:36 UTC (rev 74) @@ -18,7 +18,7 @@ public class SensitivityCapturesPoidsPopage implements SensitivityExport { /** to use log facility, just put in your code: log.info("..."); */ - static private Log log = LogFactory.getLog(CapturesPoids.class); + static private Log log = LogFactory.getLog(SensitivityCapturesPoidsPopage.class); protected String[] necessaryResult = { ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP };

1 0

r73 - trunk/sensitivity
by chatellier＠users.labs.libre-entreprise.org 12 Mar '09

12 Mar '09

Author: chatellier Date: 2009-03-12 20:02:47 +0000 (Thu, 12 Mar 2009) New Revision: 73 Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Add logging Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-11 18:28:16 UTC (rev 72) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-12 20:02:47 UTC (rev 73) @@ -22,6 +22,8 @@ import java.io.Serializable; import java.util.List; +import org.apache.commons.logging.Log; +import org.apache.commons.logging.LogFactory; import org.codelutin.j2r.REngine; import org.codelutin.j2r.RException; import org.codelutin.j2r.RProxy; @@ -29,6 +31,8 @@ import org.codelutin.math.matrix.MatrixND; import org.codelutin.util.FileUtil; +import scripts.GravityModel; + import fr.ifremer.isisfish.datastore.ExportStorage; import fr.ifremer.isisfish.datastore.SimulationStorage; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; @@ -42,15 +46,19 @@ import fr.ifremer.isisfish.simulator.sensitivity.domain.MatrixContinuousDomain; /** - * Implementation of Morris method using R + * Implementation of Morris method using R. * * @author jcouteau - * @version $Revision: 1.0 $ + * @version $Revision$ * - * Last update : $Date: 26 févr. 2009 $ By : $Author: chatellier $ + * Last update : $Date$ + * By : $Author$ */ public class SensitivityCalculatorRMorris implements SensitivityCalculator { + /** to use log facility, just put in your code: log.info("..."); */ + private static Log log = LogFactory.getLog(SensitivityCalculatorRMorris.class); + public SensitivityScenarios compute(DesignPlan plan) { double[] dataframe = new double[0]; @@ -172,6 +180,10 @@ // Get back experiment plan dataframe = (double[]) engine.eval("a$X"); + if (log.isDebugEnabled()) { + log.debug("rInstruction = " + rInstruction); + } + nbExperiments = dataframe.length / factorNumber; } catch (RException e) { Property changes on: trunk/sensitivity/SensitivityCalculatorRMorris.java ___________________________________________________________________ Name: svn:keywords + Revision Date Author

1 0

r72 - in trunk: exports sensitivity
by jcouteau＠users.labs.libre-entreprise.org 11 Mar '09

11 Mar '09

Author: jcouteau Date: 2009-03-11 18:28:16 +0000 (Wed, 11 Mar 2009) New Revision: 72 Added: trunk/exports/SensitivityBiomassPopage.java trunk/exports/SensitivityCapturesPoidsPopage.java Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Adding export for sensitivity Modifs on calculators (beginning of continuous matrix implementation, taking cardinality into account on continuous domains) Copied: trunk/exports/SensitivityBiomassPopage.java (from rev 71, trunk/exports/SensitivityBiomass.java) =================================================================== --- trunk/exports/SensitivityBiomassPopage.java (rev 0) +++ trunk/exports/SensitivityBiomassPopage.java 2009-03-11 18:28:16 UTC (rev 72) @@ -0,0 +1,69 @@ +package exports; + +import static org.codelutin.i18n.I18n._; + +import java.io.Writer; + +import org.apache.commons.logging.Log; +import org.apache.commons.logging.LogFactory; +import org.codelutin.math.matrix.MatrixIterator; +import org.codelutin.math.matrix.MatrixND; + +import scripts.ResultName; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; + +public class SensitivityBiomassPopage implements SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory.getLog(SensitivityBiomassPopage.class); + + protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + Date lastDate = simulation.getResultStorage().getLastDate(); + double biomass = 0.0; + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals("popage")) { + MatrixND mat = simulation.getResultStorage().getMatrix(pop, + ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = mat.iterator(); i.hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + Date date = (Date) sems[0]; + + if (date.afterOrEquals(lastDate)) { + biomass = biomass + i.getValue(); + } + } + } + } + out.write(Double.toString(biomass)); + + } + + @Override + public String getDescription() { + return _("Biomass for the last time step. Biomass is the sum on the groups and zones"); + } + + @Override + public String getExportFilename() { + return "SensitivityBiomassPopage"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} Property changes on: trunk/exports/SensitivityBiomassPopage.java ___________________________________________________________________ Name: svn:mergeinfo + Added: trunk/exports/SensitivityCapturesPoidsPopage.java =================================================================== --- trunk/exports/SensitivityCapturesPoidsPopage.java (rev 0) +++ trunk/exports/SensitivityCapturesPoidsPopage.java 2009-03-11 18:28:16 UTC (rev 72) @@ -0,0 +1,73 @@ +package exports; + +import static org.codelutin.i18n.I18n._; + +import java.io.Writer; + +import org.apache.commons.logging.Log; +import org.apache.commons.logging.LogFactory; +import org.codelutin.math.matrix.MatrixIterator; +import org.codelutin.math.matrix.MatrixND; + +import scripts.ResultName; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; + +public class SensitivityCapturesPoidsPopage implements SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory.getLog(CapturesPoids.class); + + protected String[] necessaryResult = { ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP }; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + Date lastDate = simulation.getResultStorage().getLastDate(); + Double capturesWeight = 0.0; + + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals("popage")) { + for (Date date = new Date(0); !date.after(lastDate); date = date + .next()) { + MatrixND mat = simulation + .getResultStorage() + .getMatrix( + date, + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + if (mat != null) { // can be null if simulation is stopped before last year simulation + mat = mat.sumOverDim(0); //sum on strategy + for (MatrixIterator i = mat.iterator(); i.hasNext();) { + i.next(); + capturesWeight=capturesWeight+i.getValue(); + } + } + } + } + } + } + + @Override + public String getDescription() { + return _("Captures in weight for the last year for the popage population. Captures is the sum of zones, groups, metiers and strategies"); + } + + @Override + public String getExportFilename() { + return "SensitivityCapturesPoidsPopage"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-10 17:53:18 UTC (rev 71) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-11 18:28:16 UTC (rev 72) @@ -96,6 +96,16 @@ * result; } + if (factor.getDomain() instanceof ContinuousDomain) { + factor + .setValueForIdentifier((((ContinuousDomain<Double>) factor + .getDomain()).getMaxBound() - ((ContinuousDomain<Double>) factor + .getDomain()).getMinBound()) + / rest + + ((ContinuousDomain<Double>) factor + .getDomain()).getMinBound()); + } + factor.setValueForIdentifier(rest); experimentScenario.addFactor(factor); } @@ -216,7 +226,7 @@ + simulationStorages.get(0).getParameter() .getSensitivityExportNames().get(k) + ".csv\")"); - //FIXME export through java to enable export when using Rserve + //FIXME export through java to enable export when using Rserve } } catch (Exception e) { Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-10 17:53:18 UTC (rev 71) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-11 18:28:16 UTC (rev 72) @@ -29,7 +29,6 @@ import org.codelutin.math.matrix.MatrixND; import org.codelutin.util.FileUtil; -import scripts.ResultName; import fr.ifremer.isisfish.datastore.ExportStorage; import fr.ifremer.isisfish.datastore.SimulationStorage; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; @@ -40,6 +39,7 @@ import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; +import fr.ifremer.isisfish.simulator.sensitivity.domain.MatrixContinuousDomain; /** * Implementation of Morris method using R @@ -51,8 +51,6 @@ */ public class SensitivityCalculatorRMorris implements SensitivityCalculator { - protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; - public SensitivityScenarios compute(DesignPlan plan) { double[] dataframe = new double[0]; @@ -94,7 +92,9 @@ + ((DiscreteDomain<? extends Serializable>) domain) .getValues().size() + ","; } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction + "4" + ","; + rInstruction = rInstruction + + ((ContinuousDomain<? extends Serializable>) domain) + .getCardinality() + ","; } } else { if (domain instanceof DiscreteDomain) { @@ -102,7 +102,9 @@ + ((DiscreteDomain<? extends Serializable>) domain) .getValues().size(); } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction + "4"; + rInstruction = rInstruction + + ((ContinuousDomain<? extends Serializable>) domain) + .getCardinality(); } } } @@ -188,8 +190,26 @@ Scenario experimentScenario = new Scenario(); for (int i = 0; i < factorNumber; i++) { Factor<? extends Serializable> factor = factors.get(i); - factor.setValueForIdentifier(morris - .getValue(new int[] { i, j })); + if (factor.getDomain() instanceof MatrixContinuousDomain) { + if (((MatrixContinuousDomain<?>) factor.getDomain()) + .getOperator().equals("*")) { + factor + .setValueForIdentifier(((MatrixContinuousDomain<?>) factor + .getDomain()).getMatrix().mults( + morris.getValue(new int[] { i, j }))); + } + if (((MatrixContinuousDomain<?>) factor.getDomain()) + .getOperator().equals("/")) { + factor + .setValueForIdentifier(((MatrixContinuousDomain<?>) factor + .getDomain()).getMatrix().divs( + morris.getValue(new int[] { i, j }))); + } + + } else { + factor.setValueForIdentifier(morris.getValue(new int[] { i, + j })); + } experimentScenario.addFactor(factor); } thisExperimentScenarios.add(experimentScenario); @@ -277,8 +297,4 @@ return "Implementation of Morris method using R"; } - public String[] getNecessaryResult() { - return this.necessaryResult; - } - }

1 0

r71 - trunk/exports
by jcouteau＠users.labs.libre-entreprise.org 10 Mar '09

10 Mar '09

Author: jcouteau Date: 2009-03-10 17:53:18 +0000 (Tue, 10 Mar 2009) New Revision: 71 Added: trunk/exports/SensitivityBiomass.java Log: Export biomass for sensitivity analysis Added: trunk/exports/SensitivityBiomass.java =================================================================== --- trunk/exports/SensitivityBiomass.java (rev 0) +++ trunk/exports/SensitivityBiomass.java 2009-03-10 17:53:18 UTC (rev 71) @@ -0,0 +1,84 @@ +package exports; + +import static org.codelutin.i18n.I18n._; + +import java.io.Writer; + +import org.apache.commons.logging.Log; +import org.apache.commons.logging.LogFactory; +import org.codelutin.math.matrix.MatrixIterator; +import org.codelutin.math.matrix.MatrixND; + +import scripts.ResultName; + +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.entities.PopulationGroup; +import fr.ifremer.isisfish.entities.Zone; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; + +public class SensitivityBiomass implements SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory.getLog(SensitivityBiomass.class); + + protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + double biomass = 0.0; + int lastDate = 0; + for (Population pop : simulation.getParameter().getPopulations()) { + MatrixND mat = simulation.getResultStorage().getMatrix(pop, + ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = mat.iterator(); i.hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + Date date = (Date) sems[0]; + if (date.getDate()>lastDate){ + lastDate=date.getDate(); + } + + } + } + for (Population pop : simulation.getParameter().getPopulations()) { + MatrixND mat = simulation.getResultStorage().getMatrix(pop, ResultName.MATRIX_BIOMASS); + for (MatrixIterator i=mat.iterator(); i.hasNext();) { + i.next(); + Object [] sems = i.getSemanticsCoordinates(); + Date date = (Date)sems[0]; + PopulationGroup group = (PopulationGroup)sems[1]; + Zone zone = (Zone)sems[2]; + + if(date.getDate()==lastDate){ + biomass=biomass+i.getValue(); + } + } + } + out.write(Double.toString(biomass)); + + } + + @Override + public String getDescription() { + return _("Biomass for the last time step. Biomass is the sum on the groups and zones"); + } + + @Override + public String getExportFilename() { + return "SensitivityBiomass"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +}

1 0

r70 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 10 Mar '09

10 Mar '09

Author: jcouteau Date: 2009-03-10 16:03:05 +0000 (Tue, 10 Mar 2009) New Revision: 70 Added: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Sensitivity calculators : -Adding Expand Grid using Java for the scenario, R for the analysis on different exports, does not work with Rserve. -Update Morris method, analysis on different exports, does not work with Rserve. Added: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java (rev 0) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-03-10 16:03:05 UTC (rev 70) @@ -0,0 +1,233 @@ +/* *##% + * Copyright (C) 2006 - 2009 Code Lutin + * + * This program is free software; you can redistribute it and/or + * modify it under the terms of the GNU General Public License + * as published by the Free Software Foundation; either version 2 + * of the License, or (at your option) any later version. + * + * 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, write to the Free Software + * Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. + *##%*/ + +package sensitivity; + +import java.io.File; +import java.io.Serializable; +import java.util.List; + +import org.codelutin.j2r.REngine; +import org.codelutin.j2r.RProxy; +import org.codelutin.util.FileUtil; + +import fr.ifremer.isisfish.datastore.ExportStorage; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; +import fr.ifremer.isisfish.simulator.sensitivity.Factor; +import fr.ifremer.isisfish.simulator.sensitivity.Scenario; +import fr.ifremer.isisfish.simulator.sensitivity.SensitivityCalculator; +import fr.ifremer.isisfish.simulator.sensitivity.SensitivityException; +import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; +import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; +import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; + +/** + * Implementation of ExpandGrid method using Java + * + * @author jcouteau + * @version $Revision: 1.0 $ + * + */ +public class SensitivityCalculatorJavaExpandGrid implements + SensitivityCalculator { + + public SensitivityScenarios compute(DesignPlan plan) + throws SensitivityException { + + int k = 1; //number of sensitivity scenarios (initialization) + int factorNumber = plan.getFactors().size(); //number of factors + List<Factor<? extends Serializable>> factors = plan.getFactors(); //list of factors + + for (int i = 0; i < factorNumber; i++) { + if (factors.get(i).getDomain() instanceof ContinuousDomain) { + k = k + * ((ContinuousDomain<? extends Serializable>) factors + .get(i).getDomain()).getCardinality(); + } else if (factors.get(i).getDomain() instanceof DiscreteDomain) { + k = k + * ((DiscreteDomain<? extends Serializable>) factors + .get(i).getDomain()).getValues().size(); + } + } + + SensitivityScenarios thisExperiment = new SensitivityScenarios(); + List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); + + for (int i = 0; i < k; i++) { + int result = 0; //used for the euclidian division + int rest = k; //used for the euclidian division + Scenario experimentScenario = new Scenario(); + for (int j = (factorNumber - 1); j >= 0; j--) { + Factor<? extends Serializable> factor = factors.get(j); + if (factors.get(j).getDomain() instanceof ContinuousDomain) { + result = (int) Math + .floor(rest + / ((ContinuousDomain<? extends Serializable>) factors + .get(j).getDomain()) + .getCardinality()); + rest = rest + - ((ContinuousDomain<? extends Serializable>) factors + .get(j).getDomain()).getCardinality() + * result; + } + if (factors.get(j).getDomain() instanceof DiscreteDomain) { + result = (int) Math.floor(rest + / ((DiscreteDomain<? extends Serializable>) factors + .get(j).getDomain()).getValues().size()); + rest = rest + - ((DiscreteDomain<? extends Serializable>) factors + .get(j).getDomain()).getValues().size() + * result; + } + + factor.setValueForIdentifier(rest); + experimentScenario.addFactor(factor); + } + thisExperimentScenarios.add(experimentScenario); + thisExperiment.setScenarios(thisExperimentScenarios); + } + return thisExperiment; + } + + public void analyzeResult(SensitivityScenarios sensitivityScenarios, + List<SimulationStorage> simulationStorages) + throws SensitivityException { + + int scenariosNumber = sensitivityScenarios.getScenarios().size(); + int factorNumber = sensitivityScenarios.getScenarios().get(0) + .getFactors().size(); + + REngine engine = new RProxy(); + try { + + int sensitivityNumber = simulationStorages.get(0).getParameter() + .getSensitivityExportNames().size(); + + for (int k = 0; k < sensitivityNumber; k++) { + + //Create the params vectors + for (int j = 0; j < factorNumber; j++) { + String vector = "factor" + j + "<-c("; + for (int i = 0; i < scenariosNumber; i++) { + if (i < (scenariosNumber - 1)) { + vector = vector + + sensitivityScenarios.getScenarios() + .get(i).getFactors().get(j) + .getValue() + ","; + } else { + vector = vector + + sensitivityScenarios.getScenarios() + .get(i).getFactors().get(j) + .getValue(); + } + + } + vector = vector + ")"; + engine.voidEval(vector); + } + + //Create the results vectors + String result = "result<-c("; + for (int l = 0; l < simulationStorages.size(); l++) { + File importFile = new File( + simulationStorages.get(l).getDirectory().toString(), + ExportStorage + .getExport( + simulationStorages + .get(l) + .getParameter() + .getSensitivityExportNames() + .get(k)) + .getNewExportInstance().getExportFilename() + + ExportStorage + .getExport( + simulationStorages + .get(l) + .getParameter() + .getSensitivityExportNames() + .get(k)) + .getNewExportInstance() + .getExtensionFilename()); + String simulResult = FileUtil.readAsString(importFile); + double simulationResult = Double.valueOf(simulResult); + if (l < simulationStorages.size() - 1) { + result = result + simulationResult + ","; + } else { + result = result + simulationResult; + } + } + result = result + ")"; + engine.voidEval(result); + + //Create the dataforaov data.frame + String dataframe = "dataforaov<-data.frame("; + for (int j = 0; j < factorNumber; j++) { + dataframe = dataframe + "factor" + j + "=factor(factor" + j + + "),"; + + } + dataframe = dataframe + "result=result)"; + engine.voidEval(dataframe); + + //Call aov() + String aovCall = "aovresult<-aov(result~"; + for (int j = 0; j < factorNumber; j++) { + if (j < (factorNumber - 1)) { + aovCall = aovCall + "factor" + j + "+"; + } else { + aovCall = aovCall + "factor" + j + ",data=dataforaov)"; + } + } + engine.voidEval(aovCall); + + //Export the results + /* + * SoS<-anova(aovresult)[1:3,2] + * IndSensibilite<-SoS/sum(SoS) + * write.csv(IndSensibilite) + */ + + engine.voidEval("SoS<-anova(aovresult)[1:" + factorNumber + + ",2]"); + engine.voidEval("names(SoS)<-dimnames(anova(aovtest))[[1]][1:" + + factorNumber + "]"); + engine.voidEval("IndSensibilite<-SoS/sum(SoS)"); + engine.voidEval("setwd(\"" + + simulationStorages.get(0).getDirectory().toString() + + "\")"); + engine + .voidEval("write.csv(IndSensibilite,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + ".csv\")"); + //FIXME export through java to enable export when using Rserve + } + + } catch (Exception e) { + e.printStackTrace(); + // Error while processing + } + + } + + public String getDescription() { + return "Implementation of Expand Grid method using Java"; + } + +} Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-09 16:52:38 UTC (rev 69) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-10 16:03:05 UTC (rev 70) @@ -18,11 +18,7 @@ package sensitivity; -import java.io.BufferedWriter; import java.io.File; -import java.io.FileReader; -import java.io.FileWriter; -import java.io.IOException; import java.io.Serializable; import java.util.List; @@ -31,8 +27,10 @@ import org.codelutin.j2r.RProxy; import org.codelutin.math.matrix.MatrixFactory; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.util.FileUtil; import scripts.ResultName; +import fr.ifremer.isisfish.datastore.ExportStorage; import fr.ifremer.isisfish.datastore.SimulationStorage; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; import fr.ifremer.isisfish.simulator.sensitivity.Domain; @@ -56,11 +54,19 @@ protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; public SensitivityScenarios compute(DesignPlan plan) { + double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); List<Factor<? extends Serializable>> factors = plan.getFactors(); + //Test all factors, if one is discrete, return null + for (int i = 0; i < factorNumber; i++) { + if (factors.get(i).getDomain() instanceof DiscreteDomain) { + return null; + } + } + String rInstruction = "a<-morris(model=NULL,factors=c("; // Creating the factors vector. @@ -196,96 +202,75 @@ public void analyzeResult(SensitivityScenarios sensitivityScenarios, List<SimulationStorage> simulationStorages) { - // This is is an analysis example with biomass analysis. + int scenariosNumber = sensitivityScenarios.getScenarios().size(); - // Creates the R expression. - String rInstruction = "tell(x,y=c("; + REngine engine = new RProxy(); + try { - for (int i = 0; i < sensitivityScenarios.getScenarios().size(); i++) { - try { - File biomass; - MatrixND matrixBiomass; - biomass = new File(simulationStorages.get(i) - .getSimulationDirectory().toString(), "Biomasses.csv"); - /* - * biomass = FileUtil.getFile(".*.csv", "fichier csv séparateur - * ';'"); - */ - matrixBiomass = MatrixFactory.getInstance().create( - new int[] { 0 }); + int sensitivityNumber = simulationStorages.get(0).getParameter() + .getSensitivityExportNames().size(); - matrixBiomass.importCSV(new FileReader(biomass), - new int[] { 0 }); + for (int k = 0; k < sensitivityNumber; k++) { - // uses the very last value of the matrix to check sensitivity - - int[] dimensions = matrixBiomass.getDim(); - if (i == sensitivityScenarios.getScenarios().size() - 1) { - rInstruction = rInstruction - + (double) matrixBiomass.getValue(dimensions) - + "))"; - } else { - rInstruction = rInstruction - + (double) matrixBiomass.getValue(dimensions) + ","; + // Creates the R expression. + String rInstruction = "tell(x,y=c("; + for (int l = 0; l < scenariosNumber; l++) { + File importFile = new File( + simulationStorages.get(l).getDirectory().toString(), + ExportStorage + .getExport( + simulationStorages + .get(l) + .getParameter() + .getSensitivityExportNames() + .get(k)) + .getNewExportInstance().getExportFilename() + + ExportStorage + .getExport( + simulationStorages + .get(l) + .getParameter() + .getSensitivityExportNames() + .get(k)) + .getNewExportInstance() + .getExtensionFilename()); + String simulResult = FileUtil.readAsString(importFile); + double simulationResult = Double.valueOf(simulResult); + if (l < simulationStorages.size() - 1) { + rInstruction = rInstruction + simulationResult + ","; + } else { + rInstruction = rInstruction + simulationResult; + } } + rInstruction = rInstruction + "))"; - } catch (Exception e) { - e.printStackTrace(); - } - } + // Call R + // Load sensitivity package into R (if package already loaded, + // nothing happens. + engine.voidEval("library(sensitivity)"); + // Send the simulation results + engine.voidEval(rInstruction); + // Get back the sensitivity results, mu, mu star and sigma. + engine.voidEval("mu<-apply(x$ee, 2, mean)"); + engine + .voidEval("mu.star <- apply(x$ee, 2, function(x) mean(abs(x)))"); + engine.voidEval("sigma <- apply(x$ee, 2, sd)"); + engine.voidEval("df=data.frame(mu,mu.star,sigma)"); + engine.voidEval("setwd(\"" + + simulationStorages.get(0).getDirectory().toString() + + "\")"); + engine + .voidEval("write.csv(df,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExportNames().get(k) + + ".csv\")"); + //FIXME export through java to enable export when using Rserve - double[] mu = { 0 }; - double[] mustar = { 0 }; - double[] sigma = { 0 }; - - // Call R - REngine engine = new RProxy(); - try { - // Load sensitivity package into R (if package already loaded, - // nothing happens. - engine.voidEval("library(sensitivity)"); - // Send the simulation results - engine.voidEval(rInstruction); - // Get back the sensitivity results, mu, mu star and sigma. - engine.voidEval("mu<-apply(x$ee, 2, mean)"); - mu = (double[]) engine.eval("mu"); - engine - .voidEval("mu.star <- apply(x$ee, 2, function(x) mean(abs(x)))"); - mustar = (double[]) engine.eval("mu.star"); - engine.voidEval("sigma <- apply(x$ee, 2, sd)"); - sigma = (double[]) engine.eval("sigma"); - - } catch (RException e) { + } + } catch (Exception e) { e.printStackTrace(); - // Error while retrieving the results } - // Treat the sensitivity results as wished. - // Create the content for export - String exportContent = ""; - for (int i = 0; i < sigma.length; i++) { - exportContent = exportContent - + "Factor : " - + sensitivityScenarios.getScenarios().get(0).getFactors() - .get(i).getName() + "\n mu = " + mu[i] - + "\n mu.star = " + mustar[i] + "\n sigma = " + sigma[i] - + "\n\n\n"; - } - - // export in the first simulation storage - try { - File export; - export = new File(simulationStorages.get(0) - .getSimulationDirectory().toString(), "sensitivity.txt"); - - FileWriter fstream = new FileWriter(export); - BufferedWriter out = new BufferedWriter(fstream); - out.write(exportContent); - out.close(); - } catch (IOException e) { - e.printStackTrace(); - } - } public String getDescription() {

1 0

r69 - trunk/sensitivity
by chatellier＠users.labs.libre-entreprise.org 09 Mar '09

09 Mar '09

Author: chatellier Date: 2009-03-09 16:52:38 +0000 (Mon, 09 Mar 2009) New Revision: 69 Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Add new domain implementation. Move domain to "domain" package. Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-03 16:10:13 UTC (rev 68) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-09 16:52:38 UTC (rev 69) @@ -34,14 +34,14 @@ import scripts.ResultName; import fr.ifremer.isisfish.datastore.SimulationStorage; -import fr.ifremer.isisfish.simulator.sensitivity.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; -import fr.ifremer.isisfish.simulator.sensitivity.DiscreteDomain; import fr.ifremer.isisfish.simulator.sensitivity.Domain; import fr.ifremer.isisfish.simulator.sensitivity.Factor; import fr.ifremer.isisfish.simulator.sensitivity.Scenario; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; +import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; +import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; /** * Implementation of Morris method using R

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r68 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 03 Mar '09

03 Mar '09

Author: jcouteau Date: 2009-03-03 16:10:13 +0000 (Tue, 03 Mar 2009) New Revision: 68 Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Simplify the scenario creation. Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-03 10:53:32 UTC (rev 67) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-03-03 16:10:13 UTC (rev 68) @@ -24,7 +24,6 @@ import java.io.FileWriter; import java.io.IOException; import java.io.Serializable; -import java.util.ArrayList; import java.util.List; import org.codelutin.j2r.REngine; @@ -54,250 +53,247 @@ */ public class SensitivityCalculatorRMorris implements SensitivityCalculator { - protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; + protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; - public SensitivityScenarios compute(DesignPlan plan) { - double[] dataframe = new double[0]; - int nbExperiments = 0; - int factorNumber = plan.getFactors().size(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + public SensitivityScenarios compute(DesignPlan plan) { + double[] dataframe = new double[0]; + int nbExperiments = 0; + int factorNumber = plan.getFactors().size(); + List<Factor<? extends Serializable>> factors = plan.getFactors(); - String rInstruction = "a<-morris(model=NULL,factors=c("; + String rInstruction = "a<-morris(model=NULL,factors=c("; - // Creating the factors vector. - for (int i = 0; i < factorNumber; i++) { - if (i != (factorNumber - 1)) { - rInstruction = rInstruction + "\"" + factors.get(i).getName() - + "\","; - } else { - rInstruction = rInstruction + "\"" + factors.get(i).getName() - + "\""; - } - } + // Creating the factors vector. + for (int i = 0; i < factorNumber; i++) { + if (i != (factorNumber - 1)) { + rInstruction = rInstruction + "\"" + factors.get(i).getName() + + "\","; + } else { + rInstruction = rInstruction + "\"" + factors.get(i).getName() + + "\""; + } + } - // Adding the number of repetition parameter (r), the morris type - // (type="oat") and the level vector - rInstruction = rInstruction - + "),r=4,design=list(type=\"oat\",levels=c("; + // Adding the number of repetition parameter (r), the morris type + // (type="oat") and the level vector + rInstruction = rInstruction + + "),r=4,design=list(type=\"oat\",levels=c("; - // Creating the levels vector. - for (int i = 0; i < factorNumber; i++) { - Domain<? extends Serializable> domain = factors.get(i).getDomain(); - if (i != (factorNumber - 1)) { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction - + ((DiscreteDomain<? extends Serializable>) domain) - .getValues().size() + ","; - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction + "4" + ","; - } - } else { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction - + ((DiscreteDomain<? extends Serializable>) domain) - .getValues().size(); - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction + "4"; - } - } - } + // Creating the levels vector. + for (int i = 0; i < factorNumber; i++) { + Domain<? extends Serializable> domain = factors.get(i).getDomain(); + if (i != (factorNumber - 1)) { + if (domain instanceof DiscreteDomain) { + rInstruction = rInstruction + + ((DiscreteDomain<? extends Serializable>) domain) + .getValues().size() + ","; + } else if (domain instanceof ContinuousDomain) { + rInstruction = rInstruction + "4" + ","; + } + } else { + if (domain instanceof DiscreteDomain) { + rInstruction = rInstruction + + ((DiscreteDomain<? extends Serializable>) domain) + .getValues().size(); + } else if (domain instanceof ContinuousDomain) { + rInstruction = rInstruction + "4"; + } + } + } - // Adding the grid.jump parameter - rInstruction = rInstruction + "),grid.jump=1),binf=c("; + // Adding the grid.jump parameter + rInstruction = rInstruction + "),grid.jump=1),binf=c("; - // Adding the binf parameter - for (int i = 0; i < factorNumber; i++) { - Domain<? extends Serializable> domain = factors.get(i).getDomain(); - if (i != (factorNumber - 1)) { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction + "0,"; - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + ((ContinuousDomain<? extends Serializable>) domain) - .getMinBound() + ","; - } - } else { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction + "0"; - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + ((ContinuousDomain<? extends Serializable>) domain) - .getMinBound(); - } - } - } + // Adding the binf parameter + for (int i = 0; i < factorNumber; i++) { + Domain<? extends Serializable> domain = factors.get(i).getDomain(); + if (i != (factorNumber - 1)) { + if (domain instanceof DiscreteDomain) { + rInstruction = rInstruction + "0,"; + } else if (domain instanceof ContinuousDomain) { + rInstruction = rInstruction + + ((ContinuousDomain<? extends Serializable>) domain) + .getMinBound() + ","; + } + } else { + if (domain instanceof DiscreteDomain) { + rInstruction = rInstruction + "0"; + } else if (domain instanceof ContinuousDomain) { + rInstruction = rInstruction + + ((ContinuousDomain<? extends Serializable>) domain) + .getMinBound(); + } + } + } - // Adding the bsup parameter - rInstruction = rInstruction + "),bsup=c("; - for (int i = 0; i < factorNumber; i++) { - Domain<? extends Serializable> domain = factors.get(i).getDomain(); - if (i != (factorNumber - 1)) { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction - + ((((DiscreteDomain<? extends Serializable>) domain) - .getValues().size()) - 1) + ","; - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + ((ContinuousDomain<? extends Serializable>) domain) - .getMaxBound() + ","; - } - } else { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction - + ((((DiscreteDomain<? extends Serializable>) domain) - .getValues().size()) - 1); - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + ((ContinuousDomain<? extends Serializable>) domain) - .getMaxBound(); - } - } - } - rInstruction = rInstruction + "))"; + // Adding the bsup parameter + rInstruction = rInstruction + "),bsup=c("; + for (int i = 0; i < factorNumber; i++) { + Domain<? extends Serializable> domain = factors.get(i).getDomain(); + if (i != (factorNumber - 1)) { + if (domain instanceof DiscreteDomain) { + rInstruction = rInstruction + + ((((DiscreteDomain<? extends Serializable>) domain) + .getValues().size()) - 1) + ","; + } else if (domain instanceof ContinuousDomain) { + rInstruction = rInstruction + + ((ContinuousDomain<? extends Serializable>) domain) + .getMaxBound() + ","; + } + } else { + if (domain instanceof DiscreteDomain) { + rInstruction = rInstruction + + ((((DiscreteDomain<? extends Serializable>) domain) + .getValues().size()) - 1); + } else if (domain instanceof ContinuousDomain) { + rInstruction = rInstruction + + ((ContinuousDomain<? extends Serializable>) domain) + .getMaxBound(); + } + } + } + rInstruction = rInstruction + "))"; - REngine engine = new RProxy(); - try { - // Load sensitivity package into R (if package already loaded, - // nothing happens. - engine.voidEval("library(sensitivity)"); - // Run sensitivity analysis - engine.voidEval(rInstruction); - // Get back experiment plan - dataframe = (double[]) engine.eval("a$X"); + REngine engine = new RProxy(); + try { + // Load sensitivity package into R (if package already loaded, + // nothing happens. + engine.voidEval("library(sensitivity)"); + // Run sensitivity analysis + engine.voidEval(rInstruction); + // Get back experiment plan + dataframe = (double[]) engine.eval("a$X"); - nbExperiments = dataframe.length / factorNumber; + nbExperiments = dataframe.length / factorNumber; - } catch (RException e) { - e.printStackTrace(); - // Error while retrieving scenario - } + } catch (RException e) { + e.printStackTrace(); + // Error while retrieving scenario + } - // Transform the result from R in a matrix - MatrixND morris = MatrixFactory.getInstance().create(dataframe, - new int[] { factorNumber, nbExperiments }); + // Transform the result from R in a matrix + MatrixND morris = MatrixFactory.getInstance().create(dataframe, + new int[] { factorNumber, nbExperiments }); - // Setting up the scenarios. - SensitivityScenarios thisExperiment = new SensitivityScenarios(); - List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); - for (int j = 0; j < nbExperiments; j++) { - Scenario experimentScenario = new Scenario(); - List<Factor<? extends Serializable>> factorslist = new ArrayList(); - for (int i = 0; i < factorNumber; i++) { - Factor<? extends Serializable> factor = (Factor<? extends Serializable>) factors - .get(i).clone(); - factor.setValueForIdentifier(morris - .getValue(new int[] { i, j })); - factorslist.add(factor); - } - experimentScenario.setFactors(factorslist); - thisExperimentScenarios.add(experimentScenario); - thisExperiment.setScenarios(thisExperimentScenarios); - } - return thisExperiment; + // Setting up the scenarios. + SensitivityScenarios thisExperiment = new SensitivityScenarios(); + List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); + for (int j = 0; j < nbExperiments; j++) { + Scenario experimentScenario = new Scenario(); + for (int i = 0; i < factorNumber; i++) { + Factor<? extends Serializable> factor = factors.get(i); + factor.setValueForIdentifier(morris + .getValue(new int[] { i, j })); + experimentScenario.addFactor(factor); + } + thisExperimentScenarios.add(experimentScenario); + thisExperiment.setScenarios(thisExperimentScenarios); + } + return thisExperiment; - } + } - public void analyzeResult(SensitivityScenarios sensitivityScenarios, - List<SimulationStorage> simulationStorages) { + public void analyzeResult(SensitivityScenarios sensitivityScenarios, + List<SimulationStorage> simulationStorages) { - // This is is an analysis example with biomass analysis. + // This is is an analysis example with biomass analysis. - // Creates the R expression. - String rInstruction = "tell(x,y=c("; + // Creates the R expression. + String rInstruction = "tell(x,y=c("; - for (int i = 0; i < sensitivityScenarios.getScenarios().size(); i++) { - try { - File biomass; - MatrixND matrixBiomass; - biomass = new File(simulationStorages.get(i) - .getSimulationDirectory().toString(), "Biomasses.csv"); - /* - * biomass = FileUtil.getFile(".*.csv", "fichier csv séparateur - * ';'"); - */ - matrixBiomass = MatrixFactory.getInstance().create( - new int[] { 0 }); + for (int i = 0; i < sensitivityScenarios.getScenarios().size(); i++) { + try { + File biomass; + MatrixND matrixBiomass; + biomass = new File(simulationStorages.get(i) + .getSimulationDirectory().toString(), "Biomasses.csv"); + /* + * biomass = FileUtil.getFile(".*.csv", "fichier csv séparateur + * ';'"); + */ + matrixBiomass = MatrixFactory.getInstance().create( + new int[] { 0 }); - matrixBiomass.importCSV(new FileReader(biomass), - new int[] { 0 }); + matrixBiomass.importCSV(new FileReader(biomass), + new int[] { 0 }); - // uses the very last value of the matrix to check sensitivity + // uses the very last value of the matrix to check sensitivity - int[] dimensions = matrixBiomass.getDim(); - if (i == sensitivityScenarios.getScenarios().size() - 1) { - rInstruction = rInstruction - + (double) matrixBiomass.getValue(dimensions) - + "))"; - } else { - rInstruction = rInstruction - + (double) matrixBiomass.getValue(dimensions) + ","; - } + int[] dimensions = matrixBiomass.getDim(); + if (i == sensitivityScenarios.getScenarios().size() - 1) { + rInstruction = rInstruction + + (double) matrixBiomass.getValue(dimensions) + + "))"; + } else { + rInstruction = rInstruction + + (double) matrixBiomass.getValue(dimensions) + ","; + } - } catch (Exception e) { - e.printStackTrace(); - } - } + } catch (Exception e) { + e.printStackTrace(); + } + } - double[] mu = { 0 }; - double[] mustar = { 0 }; - double[] sigma = { 0 }; + double[] mu = { 0 }; + double[] mustar = { 0 }; + double[] sigma = { 0 }; - // Call R - REngine engine = new RProxy(); - try { - // Load sensitivity package into R (if package already loaded, - // nothing happens. - engine.voidEval("library(sensitivity)"); - // Send the simulation results - engine.voidEval(rInstruction); - // Get back the sensitivity results, mu, mu star and sigma. - engine.voidEval("mu<-apply(x$ee, 2, mean)"); - mu = (double[]) engine.eval("mu"); - engine - .voidEval("mu.star <- apply(x$ee, 2, function(x) mean(abs(x)))"); - mustar = (double[]) engine.eval("mu.star"); - engine.voidEval("sigma <- apply(x$ee, 2, sd)"); - sigma = (double[]) engine.eval("sigma"); + // Call R + REngine engine = new RProxy(); + try { + // Load sensitivity package into R (if package already loaded, + // nothing happens. + engine.voidEval("library(sensitivity)"); + // Send the simulation results + engine.voidEval(rInstruction); + // Get back the sensitivity results, mu, mu star and sigma. + engine.voidEval("mu<-apply(x$ee, 2, mean)"); + mu = (double[]) engine.eval("mu"); + engine + .voidEval("mu.star <- apply(x$ee, 2, function(x) mean(abs(x)))"); + mustar = (double[]) engine.eval("mu.star"); + engine.voidEval("sigma <- apply(x$ee, 2, sd)"); + sigma = (double[]) engine.eval("sigma"); - } catch (RException e) { - e.printStackTrace(); - // Error while retrieving the results - } + } catch (RException e) { + e.printStackTrace(); + // Error while retrieving the results + } - // Treat the sensitivity results as wished. - // Create the content for export - String exportContent = ""; - for (int i = 0; i < sigma.length; i++) { - exportContent = exportContent - + "Factor : " - + sensitivityScenarios.getScenarios().get(0).getFactors() - .get(i).getName() + "\n mu = " + mu[i] - + "\n mu.star = " + mustar[i] + "\n sigma = " + sigma[i] - + "\n\n\n"; - } + // Treat the sensitivity results as wished. + // Create the content for export + String exportContent = ""; + for (int i = 0; i < sigma.length; i++) { + exportContent = exportContent + + "Factor : " + + sensitivityScenarios.getScenarios().get(0).getFactors() + .get(i).getName() + "\n mu = " + mu[i] + + "\n mu.star = " + mustar[i] + "\n sigma = " + sigma[i] + + "\n\n\n"; + } - // export in the first simulation storage - try { - File export; - export = new File(simulationStorages.get(0) - .getSimulationDirectory().toString(), "sensitivity.txt"); + // export in the first simulation storage + try { + File export; + export = new File(simulationStorages.get(0) + .getSimulationDirectory().toString(), "sensitivity.txt"); - FileWriter fstream = new FileWriter(export); - BufferedWriter out = new BufferedWriter(fstream); - out.write(exportContent); - out.close(); - } catch (IOException e) { - e.printStackTrace(); - } + FileWriter fstream = new FileWriter(export); + BufferedWriter out = new BufferedWriter(fstream); + out.write(exportContent); + out.close(); + } catch (IOException e) { + e.printStackTrace(); + } - } + } - public String getDescription() { - return "Implementation of Morris method using R"; - } + public String getDescription() { + return "Implementation of Morris method using R"; + } - public String[] getNecessaryResult() { - return this.necessaryResult; - } + public String[] getNecessaryResult() { + return this.necessaryResult; + } }

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