- Isis-fish-data-commits - mailman.cloud.codelutin.com

r117 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 21 Apr '09

21 Apr '09

Author: jcouteau Date: 2009-04-21 12:27:21 +0000 (Tue, 21 Apr 2009) New Revision: 117 Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Fixed attributes bug in R Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-20 16:25:44 UTC (rev 116) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-21 12:27:21 UTC (rev 117) @@ -209,9 +209,29 @@ nbExperiments = dataframe.length / factorNumber; + String isisFactorDistribution = "isis.factor.distribution<-data.frame(NomFacteur=c(%s),NomDistribution=c(%s),ParametreDistribution=c(%s))"; + + String distribution = ""; + String parameters = ""; + + for (int i = 0; i < factorNumber; i++) { + Domain domain = factors.get(i).getDomain(); + if (i != 0) { + distribution += ","; + parameters += ","; + } + + distribution += "\"qunif\""; + parameters += "\"[" + ((ContinuousDomain) domain).getMinBound() + + ";" + ((ContinuousDomain) domain).getMaxBound() + + "]\""; + } + log.info("Message sent to R : " - + "isis.factor.distribution<-c(0.0)"); - engine.voidEval("isis.factor.distribution<-c(0.0)"); + + String.format(isisFactorDistribution, factorNames, + distribution, parameters)); + engine.voidEval(String.format(isisFactorDistribution, factorNames, + distribution, parameters)); log.info("Message sent to R : " + "call<-a$call"); engine.voidEval("call<-a$call"); @@ -224,18 +244,18 @@ log .info("Message sent to R : " - + "attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + + "attr(isis.MethodExp,\"nomModel\")<-\"isis-fish-externe-R\""); engine - .voidEval("attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + .voidEval("attr(isis.MethodExp,\"nomModel\")<-\"isis-fish-externe-R\""); log.info("Message sent to R : " + "isis.simule<-data.frame(a$X)"); engine.voidEval("isis.simule<-data.frame(a$X)"); log .info("Message sent to R : " - + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + "attr(isis.simule,\"nomModel\")<-\"isis-fish-externe-R\""); engine - .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + .voidEval("attr(isis.simule,\"nomModel\")<-\"isis-fish-externe-R\""); log.info("Message sent to R : " + "names(isis.simule)<-isis.factors[[1]]"); @@ -318,7 +338,7 @@ engine.voidEval("factornames<-dget(\".factornames\")"); log.info("Message sent to R : " + "factornames<-dget(\".factornames\")"); - + int scenariosNumber = ((Double) engine .eval("length(a$X)/length(a$factors)")).intValue(); log.info("Message sent to R : " + "length(a$X)/length(a$factors)"); @@ -368,9 +388,15 @@ //adding attribute to isis.Simule log .info("Message sent to R : " - + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + "attr(isis.simule,\"nomModel\")<-\"isis-fish-externe-R\""); engine - .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + .voidEval("attr(isis.simule,\"nomModel\")<-\"isis-fish-externe-R\""); + + log + .info("Message sent to R : " + + "attr(isis.simule,\"call\")<-isis.MethodExp$call"); + engine + .voidEval("attr(isis.simule,\"call\")<-isis.MethodExp$call"); for (int k = 0; k < sensitivityNumber; k++) { @@ -386,11 +412,17 @@ log .info("Message sent to R : " + "isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" - + name + ")" + "\",a)"); + + name + ")" + "\",\"analysis_result\"=a)"); engine .voidEval("isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" - + name + ")" + "\",a)"); + + name + ")" + "\",\"analysis_result\"=a)"); + //setting isis.methodAnalyse attributes + log + .info("attr(isis.methodAnalyse,\"nomModel\")<-\"isis-fish-externe-R\")"); + engine + .voidEval("attr(isis.methodAnalyse,\"nomModel\")<-\"isis-fish-externe-R\")"); + // Get back the sensitivity results, mu, mu star and sigma. engine.voidEval("mu<-apply(a$ee, 2, mean)"); log.info("Message sent to R : " + "mu<-apply(a$ee, 2, mean)");

1 0

r116 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 20 Apr '09

20 Apr '09

Author: jcouteau Date: 2009-04-20 16:25:44 +0000 (Mon, 20 Apr 2009) New Revision: 116 Added: trunk/sensitivity/SensitivityCalculatorRegularFractions.java trunk/sensitivity/regularfractions.R Log: Regular Fractions method working, conform to the new CDC. Added: trunk/sensitivity/SensitivityCalculatorRegularFractions.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRegularFractions.java (rev 0) +++ trunk/sensitivity/SensitivityCalculatorRegularFractions.java 2009-04-20 16:25:44 UTC (rev 116) @@ -0,0 +1,614 @@ +package sensitivity; + +import java.io.File; +import java.util.List; + +import javax.swing.Box; +import javax.swing.JLabel; +import javax.swing.JOptionPane; +import javax.swing.JScrollPane; +import javax.swing.JTextPane; + +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; +import org.codelutin.math.matrix.MatrixFactory; +import org.codelutin.math.matrix.MatrixND; +import org.codelutin.util.FileUtil; + +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.simulator.sensitivity.AbstractSensitivityCalculator; +import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; +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.SensitivityException; +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.EquationContinuousDomain; +import fr.ifremer.isisfish.simulator.sensitivity.domain.MatrixContinuousDomain; +import fr.ifremer.isisfish.util.Doc; + +public class SensitivityCalculatorRegularFractions extends + AbstractSensitivityCalculator { + + /** to use log facility, just put in your code: log.info("..."); */ + private static Log log = LogFactory + .getLog(SensitivityCalculatorRFrF2.class); + + @Doc("the path of the directory where the R function is stored") + public String param_pathToFunction = ""; + + @Doc("unique prime number of levels of all input and unit factors") + public int param_p = 2; + + @Doc("number of unit factors (so that there are N=p^r units)") + public int param_r = 2; + + @Doc("resolution of the fraction") + public int param_resolution = 2; + + @Doc("True to be able to modify the code sent to R") + public boolean param_modifR = false; + + /** + * 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 true; + } + + public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) { + + setIsisFactorsR(plan, outputdirectory); + + double[] dataframeplan = new double[0]; + int nbExperiments = 0; + int factorNumber = plan.getFactors().size(); + List<Factor> factors = plan.getFactors(); + SensitivityScenarios thisExperiment = new SensitivityScenarios(); + List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); + + String factorNames = ""; + + //Test all factors, if one is discrete, return null + //Create a string with all factors names + for (int i = 0; i < factorNumber; i++) { + Domain domain = factors.get(i).getDomain(); + if (i != 0) { + factorNames += ","; + } + + factorNames += "\"" + factors.get(i).getName() + "\""; + + if (domain instanceof DiscreteDomain) { + JOptionPane + .showMessageDialog( + null, + "Error", + factors.get(i).getName() + + " has a discrete domain, this is not acceptable for this method.", + JOptionPane.ERROR_MESSAGE); + return null; + } + } + + REngine engine = new RProxy(); + + try { + + //Set working directory to get Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + //Get Isis R session + log.info("load(\".RData\")"); + engine.voidEval("load(\".RData\")"); + + //Set the working directory (to import the R function) + engine.voidEval("setwd(\"" + param_pathToFunction + "\")"); + log.info("Message sent to R : " + "setwd(\"" + param_pathToFunction + + "\")"); + + //Import the function + log.info("source(\"regularfractions.R\")"); + engine.voidEval("source(\"regularfractions.R\")"); + + //Create the instruction + String rInstruction = "x<-regular.fraction(%s,%s,%s,%s)"; + String rCall = String.format(rInstruction, factors.size(), param_p, + param_r, param_resolution); + + if (param_modifR) { + JLabel label = new JLabel( + "Modifier le code R envoyé si vous le souhaitez"); + JTextPane text = new JTextPane(); + text.setText(rCall); + text.setSize(400, 400); + text.setPreferredSize(text.getSize()); + + Box box = Box.createVerticalBox(); + box.add(label); + box.add(new JScrollPane(text)); + + JOptionPane.showMessageDialog(null, box, "R modif", + JOptionPane.QUESTION_MESSAGE); + rCall = text.getText(); + } + + // Run function + engine.voidEval(rCall); + log.info("Message sent to R : " + rCall); + + // Run function + engine.voidEval("call<-\"" + rCall + "\""); + log.info("Message sent to R : " + "call<-\"" + rCall + "\""); + + // Creating the factors vector. + rInstruction = "factornames<-c(%s)"; + rCall = String.format(rInstruction, factorNames); + + engine.voidEval(rCall); + log.info("Message sent to R : " + rCall); + + // Set output directory + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + log.info("Message sent to R : " + "setwd(\"" + + outputdirectory.getAbsolutePath() + "\")"); + + // Export the morris object for the second run in a .morris file + engine.voidEval("dput(x,file=\".regularfractions\")"); + log.info("Message sent to R : " + + "dput(x,file=\".regularfractions\")"); + + // Export the factornames object for the second run in a .factornames file + engine.voidEval("dput(factornames,file=\".factornames\")"); + log.info("Message sent to R : " + + "dput(factornames,file=\".factornames\")"); + + // Get back experiment plan + dataframeplan = (double[]) engine.eval("x$plan"); + log.info("Message sent to R : " + "x$plan"); + + //Get back the simulation number + log.info("length(x[,1])"); + int simulationNumber = (Integer) engine.eval("length(x$plan[,1])"); + + // Transform the result from R in a matrix + MatrixND morris = MatrixFactory.getInstance().create(dataframeplan, + new int[] { factors.size(), simulationNumber }); + + // Setting up the scenarios. + for (int j = 0; j < simulationNumber; j++) { + Scenario experimentScenario = new Scenario(); + for (int i = 0; i < factors.size(); i++) { + Factor factor = plan.getFactors().get(i); + if ((factor.getDomain() instanceof MatrixContinuousDomain) + || (factor.getDomain() instanceof EquationContinuousDomain)) { + factor.setValueForIdentifier(morris.getValue(new int[] { + i, j })); + } else { + Double value = (Double) ((ContinuousDomain) factor + .getDomain()).getMinBound() + + ((Double) ((ContinuousDomain) factor + .getDomain()).getMaxBound() - (Double) ((ContinuousDomain) factor + .getDomain()).getMinBound()) + * (morris.getValue(new int[] { i, j }) / (param_p - 1)); + factor.setValueForIdentifier(value); + } + experimentScenario.addFactor(factor); + } + thisExperimentScenarios.add(experimentScenario); + thisExperiment.setScenarios(thisExperimentScenarios); + } + + String dataframe = "data<-data.frame("; + + //Create the factors vectors and the dataframe instruction + for (int j = 0; j < factorNumber; j++) { + Factor factor = thisExperimentScenarios.get(0).getFactors() + .get(j); + if (factor.getDomain() instanceof EquationContinuousDomain) { + + String vector = factor.getName().replaceAll(" ", "") + + "<-c("; + for (int i = 0; i < simulationNumber; i++) { + if (i < (simulationNumber - 1)) { + vector = vector + + ((EquationContinuousDomain) thisExperimentScenarios + .get(i).getFactors().get(j) + .getDomain()).getValue() + ","; + } else { + vector = vector + + ((EquationContinuousDomain) thisExperimentScenarios + .get(i).getFactors().get(j) + .getDomain()).getValue(); + } + + } + vector = vector + ")"; + engine.voidEval(vector); + log.info("Message sent to R : " + vector); + } else if (factor.getDomain() instanceof MatrixContinuousDomain) { + String vector = factor.getName().replaceAll(" ", "") + + "<-c("; + for (int i = 0; i < simulationNumber; i++) { + if (i < (simulationNumber - 1)) { + vector = vector + + ((MatrixContinuousDomain) thisExperimentScenarios + .get(i).getFactors().get(j) + .getDomain()).getValue() + ","; + } else { + vector = vector + + ((MatrixContinuousDomain) thisExperimentScenarios + .get(i).getFactors().get(j) + .getDomain()).getValue(); + } + + } + vector = vector + ")"; + engine.voidEval(vector); + log.info("Message sent to R : " + vector); + } else { + String vector = factor.getName().replaceAll(" ", "") + + "<-c("; + for (int i = 0; i < simulationNumber; i++) { + if (i < (simulationNumber - 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); + log.info("Message sent to R : " + vector); + } + + if (j < factorNumber - 1) { + dataframe = dataframe + + factor.getName().replaceAll(" ", "") + "=factor(" + + factor.getName().replaceAll(" ", "") + "),"; + } else { + dataframe += factor.getName().replaceAll(" ", "") + + "=factor(" + factor.getName().replaceAll(" ", "") + + "))"; + } + + } + engine.voidEval(dataframe); + log.info("Message sent to R : " + dataframe); + + log.info("Message sent to R : " + + "isis.factor.distribution<-c(0.0)"); + engine.voidEval("isis.factor.distribution<-c(0.0)"); + + log + .info("Message sent to R : " + + "isis.MethodExp<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"call\"=call)"); + engine + .voidEval("isis.MethodExp<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"call\"=call)"); + + log + .info("Message sent to R : " + + "attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + + //Create isis.Simule + log.info("Message sent to R : " + "isis.simule<-data.frame(data)"); + engine.voidEval("isis.simule<-data.frame(data)"); + + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + log.info("Message sent to R : " + + "names(isis.simule)<-isis.factors[[1]]"); + engine.voidEval("names(isis.simule)<-isis.factors[[1]]"); + + // Export the data.frame object for the second run in a .expandgrid file + engine.voidEval("write.csv(data,file=\".data.csv\")"); + log + .info("Message sent to R : write.csv(data,file=\".data.csv\")"); + + + //Set working directory to save Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + // Save Isis R session + log.info("save.image()"); + engine.voidEval("save.image()"); + + engine.terminate(); + + } catch (RException eee) { + eee.printStackTrace(); + throw new RuntimeException("R evaluation failed", eee); + } + + return thisExperiment; + + } + + public void analyzeResult(List<SimulationStorage> simulationStorages, + File outputdirectory) throws SensitivityException { + + REngine engine = new RProxy(); + try { + + //Set working directory to get Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + //Get Isis R session + log.info("load(\".RData\")"); + engine.voidEval("load(\".RData\")"); + + // Set output directory + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + log.info("Message sent to R : setwd(\"" + + outputdirectory.getAbsolutePath() + "\")"); + + // Get the regularfractions object from the .regularfractions file + engine.voidEval("x<-dget(\".regularfractions\")"); + log.info("Message sent to R : " + "x<-dget(\".regularfractions\")"); + + // Get the factornames object from the .factornames file + engine.voidEval("factornames<-dget(\".factornames\")"); + log.info("Message sent to R : " + + "factornames<-dget(\".factornames\")"); + + //Get back the scenarios + engine.voidEval("factors<-read.csv(\".data.csv\")"); + log + .info("Message sent to R : factors<-read.csv(\".data.csv\")"); + + //Get back the factors number + int factorNumber = ((Double) engine.eval("length(factors)-1")) + .intValue(); + + int sensitivityNumber = simulationStorages.get(0).getParameter() + .getSensitivityExport().size(); + + for (int k = 0; k < sensitivityNumber; k++) { + + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); + + //Create the results vectors + String result = name + "<-c("; + for (int l = 0; l < simulationStorages.size(); l++) { + File importFile = new File(simulationStorages.get(l) + .getDirectory().toString() + + File.separator + + SimulationStorage.RESULT_EXPORT_DIRECTORY, + simulationStorages.get(l).getParameter() + .getSensitivityExport().get(k) + .getExportFilename() + + simulationStorages.get(l).getParameter() + .getSensitivityExport().get(k) + .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); + log.info("Message sent to R : " + result); + + //Put results in isis.simule + engine.voidEval("isis.simule<-data.frame(isis.simule," + name + + ")"); + log.info("Message sent to R : " + + "isis.simule<-data.frame(isis.simule," + name + ")"); + } + + //adding attribute to isis.Simule + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + for (int k = 0; k < sensitivityNumber; k++) { + + // Creates the R expression to import results in R + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); + + //Create the dataforaov data.frame + String dataframe = "dataforaov<-data.frame(factors," + name + + "=" + name + ")"; + engine.voidEval(dataframe); + log.info("Message sent to R : " + dataframe); + + //Call aov() + String aovCall = "aovresult<-aov(" + name + "~"; + for (int j = 0; j < factorNumber; j++) { + log.info("Message sent to R : " + "names(factors)[" + + (j + 2) + "]"); + + if (j < (factorNumber - 1)) { + aovCall = aovCall + + engine + .eval("names(factors)[" + (j + 2) + "]") + + "+"; + } else { + aovCall = aovCall + + engine + .eval("names(factors)[" + (j + 2) + "]") + + ",data=dataforaov)"; + } + } + engine.voidEval(aovCall); + log.info("Message sent to R : " + aovCall); + + /*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 + */ + + //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]][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\")"); + engine.voidEval("row.names(exportsensitivity)<-factornames"); + log.info("Message sent to R : " + + "row.names(exportsensitivity)<-factornames"); + + //Set dataforaov names + engine + .voidEval("resultsnames<-c(\"Simulation\",factornames,\"Result\")"); + log + .info("Message sent to R : " + + "resultsnames<-c(\"Simulation\",factornames,\"Result\")"); + engine.voidEval("names(dataforaov)<-resultsnames"); + log.info("Message sent to R : " + + "names(dataforaov)<-resultsnames"); + + /*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() + .getSensitivityExport().get(k) + .getExportFilename() + "_Results.csv\")"); + log.info("Message sent to R : write.csv(dataforaov,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k) + .getExportFilename() + "_Results.csv\")"); + + //Save the sensitivity indices + engine.voidEval("write.csv(exportsensitivity,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k) + .getExportFilename() + + "_SensitivityIndices.csv\")"); + log.info("Message sent to R : write.csv(exportsensitivity,\"" + + simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k) + .getExportFilename() + + "_SensitivityIndices.csv\")"); + //FIXME export through java to enable export when using Rserve (when distant Rserve). + + //creating isis.methodAnalyse + log + .info("Message sent to R : " + + "isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"" + + aovCall + "\"" + ",aovresult)"); + engine + .voidEval("isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"" + + aovCall + "\"" + ",aovresult)"); + + String renameIsisMethodAnalyse = "%s.isis.methodAnalyse<-isis.methodAnalyse"; + String simulationName = simulationStorages.get(0).getName() + .replaceAll("-", ""); + log.info("Message sent to R : " + + String.format(renameIsisMethodAnalyse, simulationName + + "." + name)); + engine.voidEval(String.format(renameIsisMethodAnalyse, + simulationName + "." + name)); + + } + + //Rename R objects for saving purpose + + String renameIsisSimule = "%s.isis.simule<-isis.simule"; + String renameIsisFactorDistribution = "%s.isis.factor.distribution<-isis.factor.distribution"; + String renameIsisFactor = "%s.isis.factor<-isis.factors"; + String renameIsisMethodExp = "%s.isis.methodExp<-isis.MethodExp"; + + String simulationName = simulationStorages.get(0).getName() + .replaceAll("-", ""); + + log.info("Message sent to R : " + + String.format(renameIsisSimule, simulationName)); + engine.voidEval(String.format(renameIsisSimule, simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisFactorDistribution, + simulationName)); + engine.voidEval(String.format(renameIsisFactorDistribution, + simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisFactor, simulationName)); + engine.voidEval(String.format(renameIsisFactor, simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisMethodExp, simulationName)); + engine.voidEval(String.format(renameIsisMethodExp, simulationName)); + + //Set working directory to save Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + // Save Isis R session + log.info("save.image()"); + engine.voidEval("save.image()"); + + engine.terminate(); + + } catch (Exception eee) { + eee.printStackTrace(); + throw new RuntimeException("R evaluation failed", eee); + } + + } + + public String getDescription() { + return "Implementation of Regular fractions method using R"; + } + +} Added: trunk/sensitivity/regularfractions.R =================================================================== --- trunk/sensitivity/regularfractions.R (rev 0) +++ trunk/sensitivity/regularfractions.R 2009-04-20 16:25:44 UTC (rev 116) @@ -0,0 +1,211 @@ +#================================================================================ +# FONCTIONS DE CALCUL D'UNE FRACTION REGULIERE DE RESOLUTION DONNEE +# Auteur: H. Monod, INRA Jouy en Josas +# Copyright INRA 2009 +# Ce programme est une version preliminaire et simplifiee d'une librairie R +# en preparation par A. Kobilinsky, H. Monod, A. Bouvier +#================================================================================ +regular.fraction <- function(s,p,r,resolution){ + # DESCRIPTION + # generates a regular fractional factorial design of given resolution, + # for s factors at p levels in p^r units + # ARGUMENTS + # s : number of input factors + # p : unique prime number of levels of all input and unit factors + # r : number of unit factors (so that there are N=p^r units) + # resolution : resolution of the fraction + # max.sol : maximum number of solutions + # DETAILS + # This is a simplified version of a more general library in preparation. + # In this version, all factors must have the same prime number of levels + # and only fractions with a given resolution can be constructed. The first + # q factors are used as basic factors. The first solution is kept although + # it may not be the most interesting one (no control of aberration). This + # function is programmed entirely in R and so it is not efficient with respect + # to computer time. There is no explicit check on the arguments and so it + # is up to the user to restrict p to a prime number such as 2, 3, 5 or 7. + # OUTPUT: + # a list with two components: plan (the design in base p) and matrice.cle + # (the design key). The design has N=p^r rows (units) and s columns (factors). + # All its elements are integers modulo p that represent the factor levels. + + # ensemble ineligible + cat("Determination des termes ineligibles: ") + ineligible <- diag(s) + for(reso in 2:(resolution-1)){ + combis <- combn(s,reso) + ncombi <- ncol(combis) + select <- cbind( c(combis), rep(seq(ncombi),rep(reso,ncombi)) ) + ineli <- matrix(0,s,ncombi) + ineli[select] <- 1 + ineligible <- cbind(ineligible,ineli) + } + cat(ncol(ineligible)," termes ineligibles.\n") + if( (p!=2) ){ + ineligible <- representative.basep(ineligible,p) + } + # Identification of the last non-zero coefficients in each ineligible trt character + ineligible.lnz <- apply(ineligible, 2, function(x){max(seq(along=x)[x!=0])}) + # initialisation of PhiStar by using the first q factors as basic factors + PhiStar <- diag(r) + # + f <- ncol(PhiStar) + if(s == f){ + check <- !any(apply(((PhiStar %*% ineligible)%%p)==0, 2, all)) + if(check) return(list(PhiStar)) + } + # Calculation of the set of initially admissible elements of U* + admissible <- t(convertinto.basep(seq((p^r)-1),p)) + nb.admissible <- ncol(admissible) + # Backtrack search - preliminaries + eeU <- list(length=s-f) + leeU <- rep(NA,s-f) + neeU <- rep(0,s-f) + # Backtrack search + cat("Recherche d'une solution (algorithme backtrack).\n") + jprev <- 0 ; j <- 1 + solved <- FALSE + while((j > 0)&(!solved)){ + PhiStar <- PhiStar[,seq(f+j-1), drop=FALSE] + if(jprev < j){ + ineligible.j <- ineligible[ seq(f+j-1), ineligible.lnz==(f+j), drop=FALSE ] + admissible.keep <- planor.kernelcheck.basep(PhiStar, admissible, ineligible.j, p) + eeU[[j]] <- seq(nb.admissible)[admissible.keep] + leeU[j] <- length(eeU[[j]]) + neeU[j] <- 0 + } + if(neeU[j] < leeU[j]){ + neeU[j] <- neeU[j]+1 + newcolj <- (eeU[[j]])[neeU[j]] + PhiStar <- cbind(PhiStar,admissible[,newcolj]) + if(j == (s-f)){ + cat("Solution obtenue. ") + solved <- TRUE + jprev <- j ; j <- j + } + else{ + jprev <- j ; j <- j+1 + } + } + else{ + jprev <- j ; j <- j-1 + } + } + if(solved){ + # Construction du plan + plan <- crossing(rep(p,r),start=0) %*% PhiStar %%p + # Sortie + out <- list(plan=plan, matrice.cle=PhiStar, p=p) + } + else{ + cat("Pas de solution. ") + out <- NULL + } + cat("Recherche terminee.\n") + return(out) +} +#--------------------------------------------------------------------------- +planor.kernelcheck.basep <- function(PhiStar, admissible, IneligibleSet, p){ + ImagesIS <- (- PhiStar %*% IneligibleSet)%%p + avoid <- convertfrom.basep( t(ImagesIS), p) + candidate <- convertfrom.basep( t(admissible), p) + test <- !(candidate %in% avoid) + return(test) +} +#--------------------------------------------------------------------------- +convertinto.basep <- function (x, p) { + # Conversion of an integer or integer vector x into base p + # The coefficients are ordered by increasing powers of p + if (!is.numeric(x)) + stop("cannot decompose non-numeric arguments") + if (length(x) > 1) { + l <- matrix(0, length(x), length(Recall(max(x),p))) + for(i in seq(along = x)){ + dec.i <- Recall(x[i],p) + l[i, seq(along=dec.i) ] <- dec.i + } + return(l) + } + if (x != round(x) || x < 0) + return(x) + val <- x%%p + while ( (x <- x%/%p) > 0 ) { + newval <- x%%p + val <- c(val,newval) + } + return(val) +} +#--------------------------------------------------------------------------- +convertfrom.basep <- function (x, p) { + # Conversion of integers x coded as vectors of coefficients in base p + # to classical integers in base 10 + + if (!is.numeric(x)) + stop("cannot recompose non-numeric arguments") + if( (max(x)>p) || (min(x)<0) ) + stop("x must be reduced modulo p") + if (is.matrix(x)) { + l <- rep(NA, nrow(x)) + for(i in seq(along = l)){ + l[i] <- Recall(x[i,],p) + } + return(l) + } + val <- sum( x * p^(seq(along=x)-1) ) + return(val) +} +#--------------------------------------------------------------------------- +inverses.basep <- function(p){ + # Raw calculation of the inverses modulo p + + if(p==2) return(1) + else if(p==3) return(c(1,2)) + products <- outer(seq(2,p-2), seq(2,p-2), "*")%%p + inverses <- 1 + apply(products, 1, function(x){ seq(along=x)[x==1] }) + return( c(1,inverses,p-1) ) +} +#--------------------------------------------------------------------------- +representative.basep <- function(mat,p){ + # generates the minimal set of representatives in base p + # of the columns x of matrix mat + + mat <- as.matrix(mat) + # + if(p==2) return(mat %%2) + # + representative <- NULL + for(j in seq(ncol(mat))){ + x <- mat[,j] + select <- seq(x)[x != 0] + nbtocross <- length(select)-1 + if( nbtocross <= 0 ) mat.j <- x + else{ + select <- select[seq(nbtocross)] + N <- (p-1)^nbtocross + mat.j <- matrix(x, nrow(mat), N) + mat.j[select,] <- t( crossing(rep(p-1,nbtocross),start=1) ) + } + representative <- cbind(representative, mat.j) + } + return(representative %%p) +} +#--------------------------------------------------------------------------- +crossing <- function(n,start=1){ + # Generates all n1 x n2 x ... x ns combinations of size s with n1,...,ns integers + + N <- prod(n) + s <- length(n) + n <- c(n,1) + crosses <- matrix(NA, N, s) + for(i in seq(s)) + { + motif <- start + seq(n[s+1-i])-1 + repet1 <- rep( prod(n[s+1-i+seq(i)]), n[s+1-i] ) + if(i==s){ repet2 <- 1 } + else{ repet2 <- prod(n[seq(s-i)]) } + crosses[,s-i+1] <- rep( rep( motif, repet1 ), repet2 ) + } + return(crosses) +} +#--------------------------------------------------------------------------- +

1 0

r115 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 20 Apr '09

20 Apr '09

Author: jcouteau Date: 2009-04-20 13:40:15 +0000 (Mon, 20 Apr 2009) New Revision: 115 Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Expand Grid conform to CDC, fixed bug on Morris (in R). Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-04-20 08:28:32 UTC (rev 114) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-04-20 13:40:15 UTC (rev 115) @@ -28,10 +28,10 @@ import org.codelutin.util.FileUtil; import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.simulator.sensitivity.AbstractSensitivityCalculator; 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityException; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; @@ -68,24 +68,26 @@ public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) throws SensitivityException { + setIsisFactorsR(plan, outputdirectory); + int k = 1; //number of sensitivity scenarios (initialization) int factorNumber = plan.getFactors().size(); //number of factors List<Factor> factors = plan.getFactors(); //list of factors for (int i = 0; i < factorNumber; i++) { if (factors.get(i).getDomain() instanceof ContinuousDomain) { - if (((ContinuousDomain) factors.get(i) - .getDomain()).getCardinality() != 0) { + if (((ContinuousDomain) factors.get(i).getDomain()) + .getCardinality() != 0) { k = k - * ((ContinuousDomain) factors - .get(i).getDomain()).getCardinality(); + * ((ContinuousDomain) factors.get(i).getDomain()) + .getCardinality(); } } else if (factors.get(i).getDomain() instanceof DiscreteDomain) { - if (((DiscreteDomain) factors.get(i) - .getDomain()).getValues().size() != 0) { + if (((DiscreteDomain) factors.get(i).getDomain()).getValues() + .size() != 0) { k = k - * ((DiscreteDomain) factors - .get(i).getDomain()).getValues().size(); + * ((DiscreteDomain) factors.get(i).getDomain()) + .getValues().size(); } } } @@ -104,8 +106,8 @@ .getMaxBound(); Double min = ((ContinuousDomain) factor.getDomain()) .getMinBound(); - int card = ((ContinuousDomain) factor - .getDomain()).getCardinality(); + int card = ((ContinuousDomain) factor.getDomain()) + .getCardinality(); result = (int) Math.floor(rest / card); rest = rest - (card * result); @@ -118,8 +120,8 @@ } } if (factor.getDomain() instanceof DiscreteDomain) { - int card = ((DiscreteDomain) factor - .getDomain()).getValues().size(); + int card = ((DiscreteDomain) factor.getDomain()) + .getValues().size(); result = (int) Math.floor(rest / card); rest = rest - (card * result); factor.setValueForIdentifier(rest); @@ -141,13 +143,26 @@ REngine engine = new RProxy(); try { - //Create the factors vectors + + //Set working directory to get Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + //Get Isis R session + log.info("load(\".RData\")"); + engine.voidEval("load(\".RData\")"); + + String dataframe = "data<-data.frame("; + + //Create the factors vectors and the dataframe instruction for (int j = 0; j < factorNumber; j++) { - Factor factor = thisExperimentScenarios - .get(0).getFactors().get(j); + Factor factor = thisExperimentScenarios.get(0).getFactors() + .get(j); if (factor.getDomain() instanceof EquationContinuousDomain) { - String vector = "factor" + j + "<-c("; + //String vector = "factor" + j + "<-c("; + String vector = factor.getName().replaceAll(" ", "") + + "<-c("; for (int i = 0; i < scenariosNumber; i++) { if (i < (scenariosNumber - 1)) { vector = vector @@ -166,7 +181,9 @@ engine.voidEval(vector); log.info("Message sent to R : " + vector); } else if (factor.getDomain() instanceof MatrixContinuousDomain) { - String vector = "factor" + j + "<-c("; + //String vector = "factor" + j + "<-c("; + String vector = factor.getName().replaceAll(" ", "") + + "<-c("; for (int i = 0; i < scenariosNumber; i++) { if (i < (scenariosNumber - 1)) { vector = vector @@ -185,7 +202,9 @@ engine.voidEval(vector); log.info("Message sent to R : " + vector); } else { - String vector = "factor" + j + "<-c("; + //String vector = "factor" + j + "<-c("; + String vector = factor.getName().replaceAll(" ", "") + + "<-c("; for (int i = 0; i < scenariosNumber; i++) { if (i < (scenariosNumber - 1)) { vector = vector @@ -204,16 +223,13 @@ log.info("Message sent to R : " + 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 - + "),"; + dataframe = dataframe + + factor.getName().replaceAll(" ", "") + "=factor(" + + factor.getName().replaceAll(" ", "") + "),"; } else { - dataframe = dataframe + "factor" + j + "=factor(factor" + j + dataframe += factor.getName().replaceAll(" ", "") + + "=factor(" + factor.getName().replaceAll(" ", "") + "))"; } @@ -254,6 +270,46 @@ log.info("Message sent to R : " + "dput(factornames,file=\".factornames\")"); + //Create the isis.factor.distribution + log.info("Message sent to R : " + + "isis.factor.distribution<-c(0.0)"); + engine.voidEval("isis.factor.distribution<-c(0.0)"); + + //Create isis.MethodExp + log + .info("Message sent to R : " + + "isis.MethodExp<-list(isis.factor,isis.factor.distribution,call_méthode=\"isis-fish-externeR\")"); + engine + .voidEval("isis.MethodExp<-list(isis.factor,isis.factor.distribution,call_méthode=\"isis-fish-externeR\")"); + + log + .info("Message sent to R : " + + "attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + + //Create isis.Simule + log.info("Message sent to R : " + "isis.simule<-data.frame(data)"); + engine.voidEval("isis.simule<-data.frame(data)"); + + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + log.info("Message sent to R : " + + "names(isis.simule)<-isis.factors[[1]]"); + engine.voidEval("names(isis.simule)<-isis.factors[[1]]"); + + //Set working directory to save Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + // Save Isis R session + log.info("save.image()"); + engine.voidEval("save.image()"); + engine.terminate(); } catch (Exception e) { @@ -270,39 +326,44 @@ REngine engine = new RProxy(); try { - /*int scenariosNumber = sensitivityScenarios.getScenarios().size(); - int factorNumber = sensitivityScenarios.getScenarios().get(0) - .getFactors().size();*/ + //Set working directory to get Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + //Get Isis R session + log.info("load(\".RData\")"); + engine.voidEval("load(\".RData\")"); + + // Set output directory + engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + + "\")"); + log.info("Message sent to R : setwd(\"" + + outputdirectory.getAbsolutePath() + "\")"); + + //Get back the scenarios + engine.voidEval("factors<-read.csv(\".expandgrid.csv\")"); + log + .info("Message sent to R : factors<-read.csv(\".expandgrid.csv\")"); + + // Get the factornames object in the .factornames file + engine.voidEval("factornames<-dget(\".factornames\")"); + log.info("Message sent to R : " + + "factornames<-dget(\".factornames\")"); + + //Get back the factors number + int factorNumber = ((Double) engine.eval("length(factors)-1")) + .intValue(); + int sensitivityNumber = simulationStorages.get(0).getParameter() .getSensitivityExport().size(); for (int k = 0; k < sensitivityNumber; k++) { - // Set output directory - engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() - + "\")"); - log.info("Message sent to R : setwd(\"" - + outputdirectory.getAbsolutePath() + "\")"); + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); - //Get back the scenarios - //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 the factornames object in the .factornames file - engine.voidEval("factornames<-dget(\".factornames\")"); - log.info("Message sent to R : " - + "factornames<-dget(\".factornames\")"); - - //Get back the factors number - int factorNumber = ((Double) engine.eval("length(factors)-1")) - .intValue(); - //factorNumber=factorNumber-1; - //Create the results vectors - String result = "result<-c("; + String result = name + "<-c("; for (int l = 0; l < simulationStorages.size(); l++) { File importFile = new File(simulationStorages.get(l) .getDirectory().toString() @@ -326,18 +387,48 @@ engine.voidEval(result); log.info("Message sent to R : " + result); + //Put results in isis.simule + engine.voidEval("isis.simule<-data.frame(isis.simule," + name + + ")"); + log.info("Message sent to R : " + + "isis.simule<-data.frame(isis.simule," + name + ")"); + } + + //adding attribute to isis.Simule + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + for (int k = 0; k < sensitivityNumber; k++) { + + // Creates the R expression to import results in R + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); + //Create the dataforaov data.frame - String dataframe = "dataforaov<-data.frame(factors,result=result)"; + String dataframe = "dataforaov<-data.frame(factors," + name + + "=" + name + ")"; engine.voidEval(dataframe); log.info("Message sent to R : " + dataframe); //Call aov() - String aovCall = "aovresult<-aov(result~"; + String aovCall = "aovresult<-aov(" + name + "~"; for (int j = 0; j < factorNumber; j++) { + log.info("Message sent to R : " + "names(factors)[" + + (j + 2) + "]"); + if (j < (factorNumber - 1)) { - aovCall = aovCall + "factor" + j + "+"; + aovCall = aovCall + + engine + .eval("names(factors)[" + (j + 2) + "]") + + "+"; } else { - aovCall = aovCall + "factor" + j + ",data=dataforaov)"; + aovCall = aovCall + + engine + .eval("names(factors)[" + (j + 2) + "]") + + ",data=dataforaov)"; } } engine.voidEval(aovCall); @@ -420,10 +511,65 @@ .getExportFilename() + "_SensitivityIndices.csv\")"); //FIXME export through java to enable export when using Rserve (when distant Rserve). - engine.terminate(); + + //creating isis.methodAnalyse + log + .info("Message sent to R : " + + "isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"" + + aovCall + "\"" + ",aovresult)"); + engine + .voidEval("isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"" + + aovCall + "\"" + ",aovresult)"); + + String renameIsisMethodAnalyse = "%s.isis.methodAnalyse<-isis.methodAnalyse"; + String simulationName = simulationStorages.get(0).getName() + .replaceAll("-", ""); + log.info("Message sent to R : " + + String.format(renameIsisMethodAnalyse, simulationName + + "." + name)); + engine.voidEval(String.format(renameIsisMethodAnalyse, + simulationName + "." + name)); + } - log.info("end"); + //Rename R objects for saving purpose + + String renameIsisSimule = "%s.isis.simule<-isis.simule"; + String renameIsisFactorDistribution = "%s.isis.factor.distribution<-isis.factor.distribution"; + String renameIsisFactor = "%s.isis.factor<-isis.factors"; + String renameIsisMethodExp = "%s.isis.methodExp<-isis.MethodExp"; + + String simulationName = simulationStorages.get(0).getName() + .replaceAll("-", ""); + + log.info("Message sent to R : " + + String.format(renameIsisSimule, simulationName)); + engine.voidEval(String.format(renameIsisSimule, simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisFactorDistribution, + simulationName)); + engine.voidEval(String.format(renameIsisFactorDistribution, + simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisFactor, simulationName)); + engine.voidEval(String.format(renameIsisFactor, simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisMethodExp, simulationName)); + engine.voidEval(String.format(renameIsisMethodExp, simulationName)); + + //Set working directory to save Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + // Save Isis R session + log.info("save.image()"); + engine.voidEval("save.image()"); + + engine.terminate(); + } catch (Exception e) { e.printStackTrace(); // Error while processing Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-20 08:28:32 UTC (rev 114) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-20 13:40:15 UTC (rev 115) @@ -318,8 +318,7 @@ engine.voidEval("factornames<-dget(\".factornames\")"); log.info("Message sent to R : " + "factornames<-dget(\".factornames\")"); - - /*int scenariosNumber = sensitivityScenarios.getScenarios().size();*/ + int scenariosNumber = ((Double) engine .eval("length(a$X)/length(a$factors)")).intValue(); log.info("Message sent to R : " + "length(a$X)/length(a$factors)"); @@ -359,10 +358,39 @@ // Send the simulation results engine.voidEval(rInstruction); + //Put results in isis.simule + engine.voidEval("isis.simule<-data.frame(isis.simule," + name + + ")"); + log.info("Message sent to R : " + + "isis.simule<-data.frame(isis.simule," + name + ")"); + } + + //adding attribute to isis.Simule + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + for (int k = 0; k < sensitivityNumber; k++) { + + // Creates the R expression to import results in R + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); + //Compute results engine.voidEval("tell(a,y=" + name + ")"); log.info("Message sent to R : " + "tell(a,y=" + name + ")"); + //creating isis.methodAnalyse + log + .info("Message sent to R : " + + "isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" + + name + ")" + "\",a)"); + engine + .voidEval("isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" + + name + ")" + "\",a)"); + // Get back the sensitivity results, mu, mu star and sigma. engine.voidEval("mu<-apply(a$ee, 2, mean)"); log.info("Message sent to R : " + "mu<-apply(a$ee, 2, mean)"); @@ -429,35 +457,6 @@ .getExportFilename() + "_Results.csv\")"); //FIXME export through java to enable export when using Rserve - //Put results in isis.simule - engine.voidEval("isis.simule<-data.frame(isis.simule," + name - + ")"); - log.info("Message sent to R : " - + "isis.simule<-data.frame(isis.simule," + name + ")"); - } - - //adding attribute to isis.Simule - log - .info("Message sent to R : " - + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); - engine - .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); - - for (int k = 0; k < sensitivityNumber; k++) { - - // Creates the R expression to import results in R - String name = simulationStorages.get(0).getParameter() - .getSensitivityExport().get(k).getExportFilename(); - - //creating isis.methodAnalyse - log - .info("Message sent to R : " - + "isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" - + name + ")" + "\",a)"); - engine - .voidEval("isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" - + name + ")" + "\",a)"); - String renameIsisMethodAnalyse = "%s.isis.methodAnalyse<-isis.methodAnalyse"; String simulationName = simulationStorages.get(0).getName() .replaceAll("-", "");

1 0

r114 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 20 Apr '09

20 Apr '09

Author: jcouteau Date: 2009-04-20 08:28:32 +0000 (Mon, 20 Apr 2009) New Revision: 114 Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Morris method managing more than one export (in R) Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-18 13:12:30 UTC (rev 113) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-20 08:28:32 UTC (rev 114) @@ -58,6 +58,7 @@ * Last update : $Date$ By : * $Author$ */ + @Doc("Morris method") public class SensitivityCalculatorRMorris extends AbstractSensitivityCalculator { @@ -217,9 +218,9 @@ log .info("Message sent to R : " - + "isis.MethodExp<-list(isis.factors,isis.factor.distribution,call)"); + + "isis.MethodExp<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"call\"=call)"); engine - .voidEval("isis.MethodExp<-list(isis.factors,isis.factor.distribution,call)"); + .voidEval("isis.MethodExp<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"call\"=call)"); log .info("Message sent to R : " @@ -359,8 +360,8 @@ engine.voidEval(rInstruction); //Compute results - engine.voidEval("tell(a,y=name)"); - log.info("Message sent to R : " + "tell(a,y=name)"); + engine.voidEval("tell(a,y=" + name + ")"); + log.info("Message sent to R : " + "tell(a,y=" + name + ")"); // Get back the sensitivity results, mu, mu star and sigma. engine.voidEval("mu<-apply(a$ee, 2, mean)"); @@ -433,7 +434,6 @@ + ")"); log.info("Message sent to R : " + "isis.simule<-data.frame(isis.simule," + name + ")"); - } //adding attribute to isis.Simule @@ -443,20 +443,38 @@ engine .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); - //creating isis.methodAnalyse - log - .info("Message sent to R : " - + "isis.methodAnalyse<-list(isis.factor,isis.factor.distribution,isis.simule,call_method=\"tell(a,results)\",a)"); - engine - .voidEval("isis.methodAnalyse<-list(isis.factor,isis.factor.distribution,isis.simule,call_method=\"tell(a,results)\",a)"); + for (int k = 0; k < sensitivityNumber; k++) { + // Creates the R expression to import results in R + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); + + //creating isis.methodAnalyse + log + .info("Message sent to R : " + + "isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" + + name + ")" + "\",a)"); + engine + .voidEval("isis.methodAnalyse<-list(\"isis.factors\"=isis.factors,\"isis.factor.distribution\"=isis.factor.distribution,\"isis.simule\"=isis.simule,call_method=\"tell(a,y=" + + name + ")" + "\",a)"); + + String renameIsisMethodAnalyse = "%s.isis.methodAnalyse<-isis.methodAnalyse"; + String simulationName = simulationStorages.get(0).getName() + .replaceAll("-", ""); + log.info("Message sent to R : " + + String.format(renameIsisMethodAnalyse, simulationName + + "." + name)); + engine.voidEval(String.format(renameIsisMethodAnalyse, + simulationName + "." + name)); + + } + //Rename R objects for saving purpose String renameIsisSimule = "%s.isis.simule<-isis.simule"; - String renameIsisMethodAnalyse = "%s.isis.methodAnalyse<-isis.methodAnalyse"; String renameIsisFactorDistribution = "%s.isis.factor.distribution<-isis.factor.distribution"; - String renameIsisFactor = "%s.isis.factor<-isis.factor"; - String renameIsisMethodExp = "%s.isis.methodExp<-isis.methodExp"; + String renameIsisFactor = "%s.isis.factor<-isis.factors"; + String renameIsisMethodExp = "%s.isis.methodExp<-isis.MethodExp"; String simulationName = simulationStorages.get(0).getName() .replaceAll("-", ""); @@ -466,11 +484,6 @@ engine.voidEval(String.format(renameIsisSimule, simulationName)); log.info("Message sent to R : " - + String.format(renameIsisMethodAnalyse, simulationName)); - engine.voidEval(String.format(renameIsisMethodAnalyse, - simulationName)); - - log.info("Message sent to R : " + String.format(renameIsisFactorDistribution, simulationName)); engine.voidEval(String.format(renameIsisFactorDistribution,

1 0

r113 - trunk/exports
by jcouteau＠users.labs.libre-entreprise.org 18 Apr '09

18 Apr '09

Author: jcouteau Date: 2009-04-18 13:12:30 +0000 (Sat, 18 Apr 2009) New Revision: 113 Modified: trunk/exports/SensitivityBiomassReferenceY9.java trunk/exports/SensitivityBiomassRelativeReferenceY12.java trunk/exports/SensitivityCapturesWeightReferenceY7.java trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java trunk/exports/SensitivityGenitorBiomassReferenceY8.java trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java Log: Fixed resultStorage bug on exports Modified: trunk/exports/SensitivityBiomassReferenceY9.java =================================================================== --- trunk/exports/SensitivityBiomassReferenceY9.java 2009-04-17 13:51:32 UTC (rev 112) +++ trunk/exports/SensitivityBiomassReferenceY9.java 2009-04-18 13:12:30 UTC (rev 113) @@ -7,6 +7,7 @@ import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.topia.TopiaContext; import scripts.ResultName; import fr.ifremer.isisfish.datastore.ResultStorage; @@ -43,6 +44,8 @@ Double biomass = 0.0; Double referenceBiomass = 0.0; + System.out.println("reference simul : " + param_referenceSimulation); + for (Population pop : simulation.getParameter().getPopulations()) { if (pop.getName().equals(param_pop.getName())) { @@ -50,14 +53,26 @@ MatrixND matlastdate = resultStorage.getMatrix(lastDate, pop, ResultName.MATRIX_BIOMASS); biomass = matlastdate.sumAll(); + System.out.println("matlastdate:" + (Object) matlastdate); - //Get the reference biomass of the last time step + TopiaContext tx = referenceSimulation.getStorage() + .beginTransaction(); + MatrixND matreferencelastdate = referenceResultStorage - .getMatrix(lastDate, pop, ResultName.MATRIX_BIOMASS); + .getMatrix(lastDate, ResultName.MATRIX_BIOMASS + " " + + pop, tx); referenceBiomass = matreferencelastdate.sumAll(); + tx.commitTransaction(); + tx.closeContext(); } } + System.out.println("simulationStorage:" + simulation); + System.out.println("referenece simulation:" + referenceSimulation); + System.out.println("resultStorage:" + resultStorage); + System.out.println("referenceStroagr:" + referenceResultStorage); + System.out.println("biomass:" + biomass); + System.out.println("referenceBiomass:" + referenceBiomass); out.write(Double.toString(biomass / referenceBiomass)); Modified: trunk/exports/SensitivityBiomassRelativeReferenceY12.java =================================================================== --- trunk/exports/SensitivityBiomassRelativeReferenceY12.java 2009-04-17 13:51:32 UTC (rev 112) +++ trunk/exports/SensitivityBiomassRelativeReferenceY12.java 2009-04-18 13:12:30 UTC (rev 113) @@ -7,6 +7,7 @@ import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.topia.TopiaContext; import scripts.ResultName; import fr.ifremer.isisfish.datastore.ResultStorage; @@ -30,7 +31,7 @@ public Population param_pop; @Doc("Name of the reference simulation") - public String param_referenceSimulation=""; + public String param_referenceSimulation = ""; @Override public void export(SimulationStorage simulation, Writer out) @@ -61,14 +62,23 @@ biomass = matlastdate.sumAll(); //Get the biomass on december of the first year + TopiaContext tx = referenceSimulation.getStorage() + .beginTransaction(); MatrixND matfirstdatereference = referenceResultStorage - .getMatrix(firstDate, pop, ResultName.MATRIX_BIOMASS); + .getMatrix(firstDate, ResultName.MATRIX_BIOMASS + " " + + pop, tx); firstbiomassReference = matfirstdatereference.sumAll(); + tx.commitTransaction(); + tx.closeContext(); //Get the biomass of the last time step + tx = referenceSimulation.getStorage().beginTransaction(); MatrixND matlastdatereference = referenceResultStorage - .getMatrix(lastDate, pop, ResultName.MATRIX_BIOMASS); + .getMatrix(lastDate, ResultName.MATRIX_BIOMASS + " " + + pop, tx); biomassReference = matlastdatereference.sumAll(); + tx.commitTransaction(); + tx.closeContext(); } } Modified: trunk/exports/SensitivityCapturesWeightReferenceY7.java =================================================================== --- trunk/exports/SensitivityCapturesWeightReferenceY7.java 2009-04-17 13:51:32 UTC (rev 112) +++ trunk/exports/SensitivityCapturesWeightReferenceY7.java 2009-04-18 13:12:30 UTC (rev 113) @@ -7,6 +7,7 @@ import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.topia.TopiaContext; import scripts.ResultName; import fr.ifremer.isisfish.datastore.ResultStorage; @@ -29,7 +30,7 @@ public Population param_pop; @Doc("Name of the reference simulation") - public String param_referenceSimulation=""; + public String param_referenceSimulation = ""; @Override public void export(SimulationStorage simulation, Writer out) @@ -56,12 +57,16 @@ capturesWeight += matlastdate.sumAll(); //Get the reference captures Weight of each month of the last year + TopiaContext tx = referenceSimulation.getStorage() + .beginTransaction(); MatrixND matlastdatereference = referenceResultStorage .getMatrix( new Date(lastDate.getDate() - i), - pop, - ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP + + " " + pop, tx); capturesWeightReference += matlastdatereference.sumAll(); + tx.commitTransaction(); + tx.closeContext(); } Modified: trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java =================================================================== --- trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java 2009-04-17 13:51:32 UTC (rev 112) +++ trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java 2009-04-18 13:12:30 UTC (rev 113) @@ -7,6 +7,7 @@ import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.topia.TopiaContext; import scripts.ResultName; import fr.ifremer.isisfish.datastore.ResultStorage; @@ -67,21 +68,27 @@ capturesWeightfirst += matfirstdate.sumAll(); //Get the reference captures Weight of each month of the last year + + TopiaContext tx = referenceSimulation.getStorage() + .beginTransaction(); + MatrixND matlastdatereference = referenceResultStorage .getMatrix( new Date(lastDate.getDate() - i), - pop, - ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP + + " " + pop, tx); capturesWeightreference += matlastdatereference.sumAll(); //Get the reference captures Weight of each month of the first year MatrixND matfirstdatereference = referenceResultStorage .getMatrix( new Date(i), - pop, - ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP + + " " + pop, tx); capturesWeightfirstreference += matfirstdatereference .sumAll(); + tx.commitTransaction(); + tx.closeContext(); } } } Modified: trunk/exports/SensitivityGenitorBiomassReferenceY8.java =================================================================== --- trunk/exports/SensitivityGenitorBiomassReferenceY8.java 2009-04-17 13:51:32 UTC (rev 112) +++ trunk/exports/SensitivityGenitorBiomassReferenceY8.java 2009-04-18 13:12:30 UTC (rev 113) @@ -8,6 +8,7 @@ import org.apache.commons.logging.LogFactory; import org.codelutin.math.matrix.MatrixIterator; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.topia.TopiaContext; import scripts.ResultName; import fr.ifremer.isisfish.datastore.ResultStorage; @@ -62,8 +63,10 @@ } //Get the reference biomass of the last time step + TopiaContext tx = referenceSimulation.getStorage() + .beginTransaction(); MatrixND matlastdatereference = referenceResultStorage - .getMatrix(pop, ResultName.MATRIX_BIOMASS); + .getMatrix(ResultName.MATRIX_BIOMASS + " " + pop, tx); for (MatrixIterator i = matlastdatereference.iterator(); i .hasNext();) { i.next(); @@ -75,6 +78,8 @@ * group.getReproductionRate(); } } + tx.commitTransaction(); + tx.closeContext(); } } out.write(Double.toString(biomass / referenceBiomass)); Modified: trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java =================================================================== --- trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java 2009-04-17 13:51:32 UTC (rev 112) +++ trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java 2009-04-18 13:12:30 UTC (rev 113) @@ -8,6 +8,7 @@ import org.apache.commons.logging.LogFactory; import org.codelutin.math.matrix.MatrixIterator; import org.codelutin.math.matrix.MatrixND; +import org.codelutin.topia.TopiaContext; import scripts.ResultName; import fr.ifremer.isisfish.datastore.ResultStorage; @@ -81,8 +82,10 @@ } //Get the reference biomass of the first time step + TopiaContext tx = referenceSimulation.getStorage() + .beginTransaction(); MatrixND matfirstdatereference = referenceResultStorage - .getMatrix(pop, ResultName.MATRIX_BIOMASS); + .getMatrix(ResultName.MATRIX_BIOMASS + " " + pop, tx); for (MatrixIterator i = matfirstdatereference.iterator(); i .hasNext();) { i.next(); @@ -97,7 +100,7 @@ //Get the reference biomass of the last time step MatrixND matlastdatereference = referenceResultStorage - .getMatrix(pop, ResultName.MATRIX_BIOMASS); + .getMatrix(ResultName.MATRIX_BIOMASS + " " + pop, tx); for (MatrixIterator i = matlastdatereference.iterator(); i .hasNext();) { i.next(); @@ -109,6 +112,8 @@ * group.getReproductionRate(); } } + tx.commitTransaction(); + tx.closeContext(); } } out.write(Double.toString((biomass / firstbiomass)

1 0

r112 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 17 Apr '09

17 Apr '09

Author: jcouteau Date: 2009-04-17 13:51:32 +0000 (Fri, 17 Apr 2009) New Revision: 112 Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java Log: Adapt Morris method to the new R CDC Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-17 12:27:11 UTC (rev 111) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-17 13:51:32 UTC (rev 112) @@ -19,7 +19,6 @@ package sensitivity; import java.io.File; -import java.io.Serializable; import java.util.List; import javax.swing.Box; @@ -38,13 +37,11 @@ import org.codelutin.util.FileUtil; import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.simulator.sensitivity.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; - 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; @@ -62,7 +59,7 @@ * $Author$ */ @Doc("Morris method") -public class SensitivityCalculatorRMorris extends AbstractSensitivityCalculator { +public class SensitivityCalculatorRMorris extends AbstractSensitivityCalculator { @Doc("Integer giving the number of repetitions of the design, i.e. the number of elementary effect computed per factor. (Default value : 4)") public int param_r = 4; @@ -85,9 +82,9 @@ } public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) { - - setIsisFactorsR(plan,outputdirectory); + setIsisFactorsR(plan, outputdirectory); + double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); @@ -129,17 +126,13 @@ factorNames += "\"" + factors.get(i).getName() + "\""; - levels += ((ContinuousDomain) domain) - .getCardinality(); + levels += ((ContinuousDomain) domain).getCardinality(); - gridJump += (Integer) (((ContinuousDomain) domain) - .getCardinality() / 2); + gridJump += (Integer) (((ContinuousDomain) domain).getCardinality() / 2); - binf += ((ContinuousDomain) domain) - .getMinBound(); + binf += ((ContinuousDomain) domain).getMinBound(); - bsup += ((ContinuousDomain) domain) - .getMaxBound(); + bsup += ((ContinuousDomain) domain).getMaxBound(); } String rInstruction = "a<-morris(model=NULL,factors=c(%s),r=%s,design=list(type=\"oat\",levels=c(%s),grid.jump=c(%s)),binf=c(%s),bsup=c(%s))"; @@ -166,13 +159,21 @@ REngine engine = new RProxy(); try { + //Set working directory to get Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + //Get Isis R session + log.info("load(\".RData\")"); + engine.voidEval("load(\".RData\")"); + // Load sensitivity package into R (if package already loaded, // nothing happens. engine.voidEval("library(sensitivity)"); log.info("Message sent to R : " + "library(sensitivity)"); // Run sensitivity analysis - engine.voidEval(rInstruction); + engine.voidEval(rCall); log.info("Message sent to R : " + rCall); // Creating the factors vector. @@ -180,26 +181,26 @@ rCall = String.format(rInstruction, factorNames); engine.voidEval(rCall); - log.info("Message sent to R" + rCall); + log.info("Message sent to R : " + rCall); // Set output directory engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() + "\")"); - log.info("Message sent to R" + "setwd(\"" + log.info("Message sent to R : " + "setwd(\"" + outputdirectory.getAbsolutePath() + "\")"); // Export the morris object for the second run in a .morris file engine.voidEval("dput(a,file=\".morris\")"); - log.info("Message sent to R" + "dput(a,file=\".morris\")"); + log.info("Message sent to R : " + "dput(a,file=\".morris\")"); // Export the factornames object for the second run in a .factornames file engine.voidEval("dput(factornames,file=\".factornames\")"); - log.info("Message sent to R" + log.info("Message sent to R : " + "dput(factornames,file=\".factornames\")"); // Get back experiment plan dataframe = (double[]) engine.eval("a$X"); - log.info("Message sent to R" + "a$X"); + log.info("Message sent to R : " + "a$X"); if (log.isDebugEnabled()) { log.debug("rInstruction = " + rInstruction); @@ -207,6 +208,46 @@ nbExperiments = dataframe.length / factorNumber; + log.info("Message sent to R : " + + "isis.factor.distribution<-c(0.0)"); + engine.voidEval("isis.factor.distribution<-c(0.0)"); + + log.info("Message sent to R : " + "call<-a$call"); + engine.voidEval("call<-a$call"); + + log + .info("Message sent to R : " + + "isis.MethodExp<-list(isis.factors,isis.factor.distribution,call)"); + engine + .voidEval("isis.MethodExp<-list(isis.factors,isis.factor.distribution,call)"); + + log + .info("Message sent to R : " + + "attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.MethodExp)<-list(nomModel=\"isis-fish-externe-R\")"); + + log.info("Message sent to R : " + "isis.simule<-data.frame(a$X)"); + engine.voidEval("isis.simule<-data.frame(a$X)"); + + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + log.info("Message sent to R : " + + "names(isis.simule)<-isis.factors[[1]]"); + engine.voidEval("names(isis.simule)<-isis.factors[[1]]"); + + //Set working directory to save Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + // Save Isis R session + log.info("save.image()"); + engine.voidEval("save.image()"); + } catch (RException eee) { eee.printStackTrace(); throw new RuntimeException("R evaluation failed", eee); @@ -226,7 +267,9 @@ Factor factor = factors.get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { - factor.setValueForIdentifier((Double)morris.getValue(i, j)); + factor + .setValueForIdentifier((Double) morris.getValue(i, + j)); } else { factor.setValueForIdentifier(morris.getValue(new int[] { i, j })); @@ -246,6 +289,14 @@ REngine engine = new RProxy(); try { + //Set working directory to get Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + //Get Isis R session + log.info("load(\".RData\")"); + engine.voidEval("load(\".RData\")"); + // Call R // Load sensitivity package into R (if package already loaded, // nothing happens. @@ -278,7 +329,9 @@ for (int k = 0; k < sensitivityNumber; k++) { // Creates the R expression to import results in R - String rInstruction = "results<-c("; + String name = simulationStorages.get(0).getParameter() + .getSensitivityExport().get(k).getExportFilename(); + String rInstruction = name + "<-c("; for (int l = 0; l < scenariosNumber; l++) { File importFile = new File(simulationStorages.get(l) .getDirectory().toString() @@ -306,8 +359,8 @@ engine.voidEval(rInstruction); //Compute results - engine.voidEval("tell(a,y=results)"); - log.info("Message sent to R : " + "tell(a,y=results)"); + engine.voidEval("tell(a,y=name)"); + log.info("Message sent to R : " + "tell(a,y=name)"); // Get back the sensitivity results, mu, mu star and sigma. engine.voidEval("mu<-apply(a$ee, 2, mean)"); @@ -330,9 +383,9 @@ log.info("Message sent to R : " + "row.names(df)<-factornames"); //Create the data.frame of scenarios and results for export purpose - engine.voidEval("dfresults=data.frame(a$X,results)"); + engine.voidEval("dfresults=data.frame(a$X,name)"); log.info("Message sent to R : " - + "dfresults=data.frame(a$X,results)"); + + "dfresults=data.frame(a$X,name)"); //Set dfresults names engine @@ -375,7 +428,70 @@ .getExportFilename() + "_Results.csv\")"); //FIXME export through java to enable export when using Rserve + //Put results in isis.simule + engine.voidEval("isis.simule<-data.frame(isis.simule," + name + + ")"); + log.info("Message sent to R : " + + "isis.simule<-data.frame(isis.simule," + name + ")"); + } + + //adding attribute to isis.Simule + log + .info("Message sent to R : " + + "attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + engine + .voidEval("attributes(isis.simule)<-list(nomModel=\"isis-fish-externe-R\")"); + + //creating isis.methodAnalyse + log + .info("Message sent to R : " + + "isis.methodAnalyse<-list(isis.factor,isis.factor.distribution,isis.simule,call_method=\"tell(a,results)\",a)"); + engine + .voidEval("isis.methodAnalyse<-list(isis.factor,isis.factor.distribution,isis.simule,call_method=\"tell(a,results)\",a)"); + + //Rename R objects for saving purpose + + String renameIsisSimule = "%s.isis.simule<-isis.simule"; + String renameIsisMethodAnalyse = "%s.isis.methodAnalyse<-isis.methodAnalyse"; + String renameIsisFactorDistribution = "%s.isis.factor.distribution<-isis.factor.distribution"; + String renameIsisFactor = "%s.isis.factor<-isis.factor"; + String renameIsisMethodExp = "%s.isis.methodExp<-isis.methodExp"; + + String simulationName = simulationStorages.get(0).getName() + .replaceAll("-", ""); + + log.info("Message sent to R : " + + String.format(renameIsisSimule, simulationName)); + engine.voidEval(String.format(renameIsisSimule, simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisMethodAnalyse, simulationName)); + engine.voidEval(String.format(renameIsisMethodAnalyse, + simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisFactorDistribution, + simulationName)); + engine.voidEval(String.format(renameIsisFactorDistribution, + simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisFactor, simulationName)); + engine.voidEval(String.format(renameIsisFactor, simulationName)); + + log.info("Message sent to R : " + + String.format(renameIsisMethodExp, simulationName)); + engine.voidEval(String.format(renameIsisMethodExp, simulationName)); + + //Set working directory to save Isis R session + log.info("setwd(\"" + outputdirectory.getParent() + "\")"); + engine.voidEval("setwd(\"" + outputdirectory.getParent() + "\")"); + + // Save Isis R session + log.info("save.image()"); + engine.voidEval("save.image()"); + } catch (Exception e) { e.printStackTrace(); }

1 0

r111 - trunk
by chatellier＠users.labs.libre-entreprise.org 17 Apr '09

17 Apr '09

Author: chatellier Date: 2009-04-17 12:27:11 +0000 (Fri, 17 Apr 2009) New Revision: 111 Modified: trunk/pom.xml Log: Update dependency Modified: trunk/pom.xml =================================================================== --- trunk/pom.xml 2009-04-17 10:03:06 UTC (rev 110) +++ trunk/pom.xml 2009-04-17 12:27:11 UTC (rev 111) @@ -54,7 +54,7 @@ <dependency> <groupId>ifremer</groupId> <artifactId>isis-fish</artifactId> - <version>3.2.0.4-rc3-SNAPSHOT</version> + <version>3.2.0.4-rc4-SNAPSHOT</version> <scope>compile</scope> </dependency> </dependencies>

1 0

r110 - trunk
by jcouteau＠users.labs.libre-entreprise.org 17 Apr '09

17 Apr '09

Author: jcouteau Date: 2009-04-17 10:03:06 +0000 (Fri, 17 Apr 2009) New Revision: 110 Modified: trunk/pom.xml Log: Modified: trunk/pom.xml =================================================================== --- trunk/pom.xml 2009-04-17 09:51:03 UTC (rev 109) +++ trunk/pom.xml 2009-04-17 10:03:06 UTC (rev 110) @@ -54,7 +54,7 @@ <dependency> <groupId>ifremer</groupId> <artifactId>isis-fish</artifactId> - <version>3.2.0.4-rc2-SNAPSHOT</version> + <version>3.2.0.4-rc3-SNAPSHOT</version> <scope>compile</scope> </dependency> </dependencies>

1 0

r109 - trunk/sensitivity
by jcouteau＠users.labs.libre-entreprise.org 17 Apr '09

17 Apr '09

Author: jcouteau Date: 2009-04-17 09:51:03 +0000 (Fri, 17 Apr 2009) New Revision: 109 Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java trunk/sensitivity/SensitivityCalculatorRFast.java trunk/sensitivity/SensitivityCalculatorRFrF2.java trunk/sensitivity/SensitivityCalculatorRMorris.java trunk/sensitivity/SensitivityCalculatorROptimumLHS.java trunk/sensitivity/SensitivityCalculatorRRandomLHS.java trunk/sensitivity/SensitivityCalculatorRSobol.java Log: Adapt to isis-fish sensitivity refactoring Modified: trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorJavaExpandGrid.java 2009-04-17 09:51:03 UTC (rev 109) @@ -19,7 +19,6 @@ package sensitivity; import java.io.File; -import java.io.Serializable; import java.util.List; import org.apache.commons.logging.Log; @@ -32,7 +31,7 @@ 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityException; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; @@ -49,8 +48,8 @@ * */ @Doc("ExpandGrid") -public class SensitivityCalculatorJavaExpandGrid implements - SensitivityCalculator { +public class SensitivityCalculatorJavaExpandGrid extends + AbstractSensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ static private Log log = LogFactory @@ -71,21 +70,21 @@ 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 + List<Factor> factors = plan.getFactors(); //list of factors for (int i = 0; i < factorNumber; i++) { if (factors.get(i).getDomain() instanceof ContinuousDomain) { - if (((ContinuousDomain<? extends Serializable>) factors.get(i) + if (((ContinuousDomain) factors.get(i) .getDomain()).getCardinality() != 0) { k = k - * ((ContinuousDomain<? extends Serializable>) factors + * ((ContinuousDomain) factors .get(i).getDomain()).getCardinality(); } } else if (factors.get(i).getDomain() instanceof DiscreteDomain) { - if (((DiscreteDomain<? extends Serializable>) factors.get(i) + if (((DiscreteDomain) factors.get(i) .getDomain()).getValues().size() != 0) { k = k - * ((DiscreteDomain<? extends Serializable>) factors + * ((DiscreteDomain) factors .get(i).getDomain()).getValues().size(); } } @@ -99,13 +98,13 @@ int rest = i; //used for the euclidian division Scenario experimentScenario = new Scenario(); for (int j = 0; j < factorNumber; j++) { - Factor<? extends Serializable> factor = factors.get(j); + Factor factor = factors.get(j); if (factor.getDomain() instanceof ContinuousDomain) { - Double max = ((ContinuousDomain<Double>) factor.getDomain()) + Double max = ((ContinuousDomain) factor.getDomain()) .getMaxBound(); - Double min = ((ContinuousDomain<Double>) factor.getDomain()) + Double min = ((ContinuousDomain) factor.getDomain()) .getMinBound(); - int card = ((ContinuousDomain<? extends Serializable>) factor + int card = ((ContinuousDomain) factor .getDomain()).getCardinality(); result = (int) Math.floor(rest / card); rest = rest - (card * result); @@ -119,7 +118,7 @@ } } if (factor.getDomain() instanceof DiscreteDomain) { - int card = ((DiscreteDomain<? extends Serializable>) factor + int card = ((DiscreteDomain) factor .getDomain()).getValues().size(); result = (int) Math.floor(rest / card); rest = rest - (card * result); @@ -144,7 +143,7 @@ try { //Create the factors vectors for (int j = 0; j < factorNumber; j++) { - Factor<? extends Serializable> factor = thisExperimentScenarios + Factor factor = thisExperimentScenarios .get(0).getFactors().get(j); if (factor.getDomain() instanceof EquationContinuousDomain) { @@ -152,12 +151,12 @@ for (int i = 0; i < scenariosNumber; i++) { if (i < (scenariosNumber - 1)) { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } @@ -171,12 +170,12 @@ for (int i = 0; i < scenariosNumber; i++) { if (i < (scenariosNumber - 1)) { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } Modified: trunk/sensitivity/SensitivityCalculatorRFast.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRFast.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorRFast.java 2009-04-17 09:51:03 UTC (rev 109) @@ -38,6 +38,8 @@ 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; @@ -55,7 +57,7 @@ * $Author: jcouteau $ */ -public class SensitivityCalculatorRFast implements SensitivityCalculator { +public class SensitivityCalculatorRFast extends AbstractSensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ private static Log log = LogFactory @@ -92,7 +94,7 @@ double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + List<Factor> factors = plan.getFactors(); SensitivityScenarios thisExperiment = new SensitivityScenarios(); List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); @@ -186,17 +188,17 @@ for (int j = 0; j < nbExperiments; j++) { Scenario experimentScenario = new Scenario(); for (int i = 0; i < factorNumber; i++) { - Factor<? extends Serializable> factor = plan.getFactors() + Factor factor = plan.getFactors() .get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { factor.setValueForIdentifier(Double.valueOf( fast.getValue(new int[] { i, j })).toString()); } else { - Double value = (Double) ((ContinuousDomain<?>) factor + Double value = (Double) ((ContinuousDomain) factor .getDomain()).getMinBound() - + ((Double) ((ContinuousDomain<?>) factor - .getDomain()).getMaxBound() - (Double) ((ContinuousDomain<?>) factor + + ((Double) ((ContinuousDomain) factor + .getDomain()).getMaxBound() - (Double) ((ContinuousDomain) factor .getDomain()).getMinBound()) * fast.getValue(new int[] { i, j }); factor.setValueForIdentifier(value); Modified: trunk/sensitivity/SensitivityCalculatorRFrF2.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRFrF2.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorRFrF2.java 2009-04-17 09:51:03 UTC (rev 109) @@ -38,6 +38,8 @@ 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; @@ -55,7 +57,7 @@ * $Author: chatellier $ */ @Doc("FrF2 method, at least 4 factors need to be declared") -public class SensitivityCalculatorRFrF2 implements SensitivityCalculator { +public class SensitivityCalculatorRFrF2 extends AbstractSensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ private static Log log = LogFactory @@ -79,7 +81,7 @@ double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + List<Factor> factors = plan.getFactors(); SensitivityScenarios thisExperiment = new SensitivityScenarios(); List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); @@ -161,7 +163,7 @@ for (int j = 0; j < nbExperiments; j++) { Scenario experimentScenario = new Scenario(); for (int i = 0; i < factorNumber; i++) { - Factor<? extends Serializable> factor = plan.getFactors() + Factor factor = plan.getFactors() .get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { @@ -177,13 +179,13 @@ } else { if (frf2.getValue(new int[] { i, j }) == -1) { factor - .setValueForIdentifier(((ContinuousDomain<?>) factor + .setValueForIdentifier(((ContinuousDomain) factor .getDomain()).getMinBound()); } if (frf2.getValue(new int[] { i, j }) == 1) { factor - .setValueForIdentifier(((ContinuousDomain<?>) factor + .setValueForIdentifier(((ContinuousDomain) factor .getDomain()).getMaxBound()); } } @@ -195,7 +197,7 @@ try { //Create the factors vectors for (int j = 0; j < factorNumber; j++) { - Factor<? extends Serializable> factor = thisExperimentScenarios + Factor factor = thisExperimentScenarios .get(0).getFactors().get(j); if (factor.getDomain() instanceof EquationContinuousDomain) { @@ -203,12 +205,12 @@ for (int i = 0; i < nbExperiments; i++) { if (i < (nbExperiments - 1)) { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } @@ -222,12 +224,12 @@ for (int i = 0; i < nbExperiments; i++) { if (i < (nbExperiments - 1)) { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } Modified: trunk/sensitivity/SensitivityCalculatorRMorris.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorRMorris.java 2009-04-17 09:51:03 UTC (rev 109) @@ -22,6 +22,12 @@ import java.io.Serializable; import java.util.List; +import javax.swing.Box; +import javax.swing.JLabel; +import javax.swing.JOptionPane; +import javax.swing.JScrollPane; +import javax.swing.JTextPane; + import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.codelutin.j2r.REngine; @@ -33,10 +39,12 @@ import fr.ifremer.isisfish.datastore.SimulationStorage; import fr.ifremer.isisfish.simulator.sensitivity.DesignPlan; + 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; @@ -54,11 +62,14 @@ * $Author$ */ @Doc("Morris method") -public class SensitivityCalculatorRMorris implements SensitivityCalculator { +public class SensitivityCalculatorRMorris extends AbstractSensitivityCalculator { @Doc("Integer giving the number of repetitions of the design, i.e. the number of elementary effect computed per factor. (Default value : 4)") - public int param_r; + public int param_r = 4; + @Doc("True to be able to modify the code sent to R") + public boolean param_modifR = false; + /** to use log facility, just put in your code: log.info("..."); */ private static Log log = LogFactory .getLog(SensitivityCalculatorRMorris.class); @@ -74,174 +85,102 @@ } public SensitivityScenarios compute(DesignPlan plan, File outputdirectory) { + + setIsisFactorsR(plan,outputdirectory); double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + List<Factor> factors = plan.getFactors(); - if (((Integer) param_r == null) || ((Integer) param_r == 0)) { + if (param_r == 0) { param_r = 4; } //Test all factors, if one is discrete, return null for (int i = 0; i < factorNumber; i++) { if (factors.get(i).getDomain() instanceof DiscreteDomain) { + JOptionPane + .showMessageDialog( + null, + "Error", + factors.get(i).getName() + + " has a discrete domain, this is not acceptable for this method.", + JOptionPane.ERROR_MESSAGE); return null; } } - String rInstruction = "a<-morris(model=NULL,factors=c("; - - // Creating the factors vector. + // Creating the vectors. + String factorNames = ""; + String levels = ""; + String gridJump = ""; + String binf = ""; + String bsup = ""; for (int i = 0; i < factorNumber; i++) { - if (i != (factorNumber - 1)) { - rInstruction = rInstruction + "\"" + factors.get(i).getName() - + "\","; - } else { - rInstruction = rInstruction + "\"" + factors.get(i).getName() - + "\""; + Domain domain = factors.get(i).getDomain(); + if (i != 0) { + factorNames += ","; + levels += ","; + gridJump += ","; + binf += ","; + bsup += ","; } - } - // Adding the number of repetition parameter (r), the morris type - // (type="oat") and the level vector - rInstruction = rInstruction + "),r=" + param_r - + ",design=list(type=\"oat\",levels=c("; + factorNames += "\"" + factors.get(i).getName() + "\""; - // 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 - + ((ContinuousDomain<? extends Serializable>) domain) - .getCardinality() + ","; - } - } else { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction - + ((DiscreteDomain<? extends Serializable>) domain) - .getValues().size(); - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + ((ContinuousDomain<? extends Serializable>) domain) - .getCardinality(); - } - } - } + levels += ((ContinuousDomain) domain) + .getCardinality(); - // Adding the grid.jump parameter - rInstruction = rInstruction + "),grid.jump=c("; + gridJump += (Integer) (((ContinuousDomain) domain) + .getCardinality() / 2); - // Creating the grid.jump 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 - + (Integer) (((DiscreteDomain<? extends Serializable>) domain) - .getValues().size() / 2) + ","; - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + (Integer) (((ContinuousDomain<? extends Serializable>) domain) - .getCardinality() / 2) + ","; - } - } else { - if (domain instanceof DiscreteDomain) { - rInstruction = rInstruction - + (Integer) (((DiscreteDomain<? extends Serializable>) domain) - .getValues().size() / 2); - } else if (domain instanceof ContinuousDomain) { - rInstruction = rInstruction - + (Integer) (((ContinuousDomain<? extends Serializable>) domain) - .getCardinality() / 2); - } - } + binf += ((ContinuousDomain) domain) + .getMinBound(); + + bsup += ((ContinuousDomain) domain) + .getMaxBound(); } - rInstruction += ")),binf=c("; + String rInstruction = "a<-morris(model=NULL,factors=c(%s),r=%s,design=list(type=\"oat\",levels=c(%s),grid.jump=c(%s)),binf=c(%s),bsup=c(%s))"; - // 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(); - } - } - } + String rCall = String.format(rInstruction, factorNames, param_r, + levels, gridJump, binf, bsup); - // 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(); - } - } + if (param_modifR) { + JLabel label = new JLabel( + "Modifier le code R envoyé si vous le souhaitez"); + JTextPane text = new JTextPane(); + text.setText(rCall); + text.setSize(400, 400); + text.setPreferredSize(text.getSize()); + + Box box = Box.createVerticalBox(); + box.add(label); + box.add(new JScrollPane(text)); + + JOptionPane.showMessageDialog(null, box, "R modif", + JOptionPane.QUESTION_MESSAGE); + rCall = text.getText(); } - rInstruction = rInstruction + "))"; REngine engine = new RProxy(); try { // Load sensitivity package into R (if package already loaded, // nothing happens. engine.voidEval("library(sensitivity)"); - log.info("Message sent to R" + "library(sensitivity)"); + log.info("Message sent to R : " + "library(sensitivity)"); // Run sensitivity analysis engine.voidEval(rInstruction); - log.info("Message sent to R" + rInstruction); + log.info("Message sent to R : " + rCall); // Creating the factors vector. - rInstruction = "factornames<-c("; - for (int i = 0; i < factorNumber; i++) { - if (i != (factorNumber - 1)) { - rInstruction = rInstruction + "\"" - + factors.get(i).getName() + "\","; - } else { - rInstruction = rInstruction + "\"" - + factors.get(i).getName() + "\""; - } - } + rInstruction = "factornames<-c(%s)"; + rCall = String.format(rInstruction, factorNames); - rInstruction += ")"; - engine.voidEval(rInstruction); - log.info("Message sent to R" + rInstruction); + engine.voidEval(rCall); + log.info("Message sent to R" + rCall); // Set output directory engine.voidEval("setwd(\"" + outputdirectory.getAbsolutePath() @@ -268,8 +207,9 @@ nbExperiments = dataframe.length / factorNumber; - } catch (RException e) { - e.printStackTrace(); + } catch (RException eee) { + eee.printStackTrace(); + throw new RuntimeException("R evaluation failed", eee); // Error while retrieving scenario } @@ -283,11 +223,10 @@ 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 factor = factors.get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { - factor.setValueForIdentifier(Double.valueOf( - morris.getValue(new int[] { i, j })).toString()); + factor.setValueForIdentifier((Double)morris.getValue(i, j)); } else { factor.setValueForIdentifier(morris.getValue(new int[] { i, j })); Modified: trunk/sensitivity/SensitivityCalculatorROptimumLHS.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorROptimumLHS.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorROptimumLHS.java 2009-04-17 09:51:03 UTC (rev 109) @@ -35,6 +35,7 @@ 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityException; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; @@ -42,7 +43,7 @@ import fr.ifremer.isisfish.simulator.sensitivity.domain.MatrixContinuousDomain; import fr.ifremer.isisfish.util.Doc; -/** +/**save.image() * Implementation of Optimum Latin Hypercube method using R. * * @author jcouteau @@ -50,7 +51,7 @@ * */ @Doc("Optimum Latin Hypercube") -public class SensitivityCalculatorROptimumLHS implements SensitivityCalculator { +public class SensitivityCalculatorROptimumLHS extends AbstractSensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ static private Log log = LogFactory @@ -77,7 +78,7 @@ throws SensitivityException { int factornumber = plan.getFactors().size(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + List<Factor> factors = plan.getFactors(); double[] dataframe = new double[0]; SensitivityScenarios thisExperiment = new SensitivityScenarios(); List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); @@ -121,7 +122,7 @@ for (int j = 0; j < param_simulationNumber; j++) { Scenario experimentScenario = new Scenario(); for (int i = 0; i < factornumber; i++) { - Factor<? extends Serializable> factor = plan.getFactors() + Factor factor = plan.getFactors() .get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { @@ -130,10 +131,10 @@ morris.getValue(new int[] { i, j })) .toString()); } else { - Double value = (Double) ((ContinuousDomain<?>) factor + Double value = (Double) ((ContinuousDomain) factor .getDomain()).getMinBound() - + ((Double) ((ContinuousDomain<?>) factor - .getDomain()).getMaxBound() - (Double) ((ContinuousDomain<?>) factor + + ((Double) ((ContinuousDomain) factor + .getDomain()).getMaxBound() - (Double) ((ContinuousDomain) factor .getDomain()).getMinBound()) * morris.getValue(new int[] { i, j }); factor.setValueForIdentifier(value); @@ -146,7 +147,7 @@ //Create the factors vectors for (int j = 0; j < factornumber; j++) { - Factor<? extends Serializable> factor = thisExperimentScenarios + Factor factor = thisExperimentScenarios .get(0).getFactors().get(j); if (factor.getDomain() instanceof EquationContinuousDomain) { @@ -154,12 +155,12 @@ for (int i = 0; i < param_simulationNumber; i++) { if (i < (param_simulationNumber - 1)) { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } @@ -173,12 +174,12 @@ for (int i = 0; i < param_simulationNumber; i++) { if (i < (param_simulationNumber - 1)) { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } Modified: trunk/sensitivity/SensitivityCalculatorRRandomLHS.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRRandomLHS.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorRRandomLHS.java 2009-04-17 09:51:03 UTC (rev 109) @@ -35,6 +35,7 @@ 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityException; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; @@ -50,7 +51,7 @@ * */ @Doc("Random Latin Hypercube") -public class SensitivityCalculatorRRandomLHS implements SensitivityCalculator { +public class SensitivityCalculatorRRandomLHS extends AbstractSensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ static private Log log = LogFactory @@ -76,7 +77,7 @@ double[] dataframe = new double[0]; SensitivityScenarios thisExperiment = new SensitivityScenarios(); List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + List<Factor> factors = plan.getFactors(); if ((Integer) param_simulationNumber == 0) { param_simulationNumber = 10; @@ -107,7 +108,7 @@ for (int j = 0; j < param_simulationNumber; j++) { Scenario experimentScenario = new Scenario(); for (int i = 0; i < factornumber; i++) { - Factor<? extends Serializable> factor = plan.getFactors() + Factor factor = plan.getFactors() .get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { @@ -116,10 +117,10 @@ morris.getValue(new int[] { i, j })) .toString()); } else { - Double value = (Double) ((ContinuousDomain<?>) factor + Double value = (Double) ((ContinuousDomain) factor .getDomain()).getMinBound() - + ((Double) ((ContinuousDomain<?>) factor - .getDomain()).getMaxBound() - (Double) ((ContinuousDomain<?>) factor + + ((Double) ((ContinuousDomain) factor + .getDomain()).getMaxBound() - (Double) ((ContinuousDomain) factor .getDomain()).getMinBound()) * morris.getValue(new int[] { i, j }); factor.setValueForIdentifier(value); @@ -132,7 +133,7 @@ //Create the factors vectors for (int j = 0; j < factornumber; j++) { - Factor<? extends Serializable> factor = thisExperimentScenarios + Factor factor = thisExperimentScenarios .get(0).getFactors().get(j); if (factor.getDomain() instanceof EquationContinuousDomain) { @@ -140,12 +141,12 @@ for (int i = 0; i < param_simulationNumber; i++) { if (i < (param_simulationNumber - 1)) { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((EquationContinuousDomain<?>) thisExperimentScenarios + + ((EquationContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } @@ -159,12 +160,12 @@ for (int i = 0; i < param_simulationNumber; i++) { if (i < (param_simulationNumber - 1)) { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue() + ","; } else { vector = vector - + ((MatrixContinuousDomain<?>) thisExperimentScenarios + + ((MatrixContinuousDomain) thisExperimentScenarios .get(i).getFactors().get(j) .getDomain()).getValue(); } Modified: trunk/sensitivity/SensitivityCalculatorRSobol.java =================================================================== --- trunk/sensitivity/SensitivityCalculatorRSobol.java 2009-04-16 13:25:07 UTC (rev 108) +++ trunk/sensitivity/SensitivityCalculatorRSobol.java 2009-04-17 09:51:03 UTC (rev 109) @@ -37,6 +37,7 @@ 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.AbstractSensitivityCalculator; import fr.ifremer.isisfish.simulator.sensitivity.SensitivityScenarios; import fr.ifremer.isisfish.simulator.sensitivity.domain.ContinuousDomain; import fr.ifremer.isisfish.simulator.sensitivity.domain.DiscreteDomain; @@ -54,7 +55,7 @@ * $Author: jcouteau $ */ -public class SensitivityCalculatorRSobol implements SensitivityCalculator { +public class SensitivityCalculatorRSobol extends AbstractSensitivityCalculator { /** to use log facility, just put in your code: log.info("..."); */ private static Log log = LogFactory @@ -84,7 +85,7 @@ double[] dataframe = new double[0]; int nbExperiments = 0; int factorNumber = plan.getFactors().size(); - List<Factor<? extends Serializable>> factors = plan.getFactors(); + List<Factor> factors = plan.getFactors(); SensitivityScenarios thisExperiment = new SensitivityScenarios(); List<Scenario> thisExperimentScenarios = thisExperiment.getScenarios(); @@ -188,17 +189,17 @@ for (int j = 0; j < nbExperiments; j++) { Scenario experimentScenario = new Scenario(); for (int i = 0; i < factorNumber; i++) { - Factor<? extends Serializable> factor = plan.getFactors() + Factor factor = plan.getFactors() .get(i); if ((factor.getDomain() instanceof MatrixContinuousDomain) || (factor.getDomain() instanceof EquationContinuousDomain)) { factor.setValueForIdentifier(Double.valueOf( fast.getValue(new int[] { i, j })).toString()); } else { - Double value = (Double) ((ContinuousDomain<?>) factor + Double value = (Double) ((ContinuousDomain) factor .getDomain()).getMinBound() - + ((Double) ((ContinuousDomain<?>) factor - .getDomain()).getMaxBound() - (Double) ((ContinuousDomain<?>) factor + + ((Double) ((ContinuousDomain) factor + .getDomain()).getMaxBound() - (Double) ((ContinuousDomain) factor .getDomain()).getMinBound()) * fast.getValue(new int[] { i, j }); factor.setValueForIdentifier(value); @@ -360,7 +361,7 @@ } public String getDescription() { - return "Implementation of FAST method using R"; + return "Implementation of Sobol method using R"; } }

1 0

r108 - trunk/exports
by jcouteau＠users.labs.libre-entreprise.org 16 Apr '09

16 Apr '09

Author: jcouteau Date: 2009-04-16 13:25:07 +0000 (Thu, 16 Apr 2009) New Revision: 108 Added: trunk/exports/SensitivityBiomassRelativeReferenceY12.java trunk/exports/SensitivityCapturesWeightReferenceY7.java trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java trunk/exports/SensitivityGenitorBiomassReferenceY8.java trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java Modified: trunk/exports/SensitivityBiomassReferenceY9.java trunk/exports/SensitivityBiomassRelativeY6.java trunk/exports/SensitivityGenitorBiomassRelativeY5.java Log: Implementation of reference exports. Modified: trunk/exports/SensitivityBiomassReferenceY9.java =================================================================== --- trunk/exports/SensitivityBiomassReferenceY9.java 2009-04-16 12:00:03 UTC (rev 107) +++ trunk/exports/SensitivityBiomassReferenceY9.java 2009-04-16 13:25:07 UTC (rev 108) @@ -2,12 +2,10 @@ import static org.codelutin.i18n.I18n._; -import java.io.File; 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; @@ -22,39 +20,47 @@ public class SensitivityBiomassReferenceY9 implements SensitivityExport { /** to use log facility, just put in your code: log.info("..."); */ - static private Log log = LogFactory.getLog(SensitivityBiomassReferenceY9.class); + static private Log log = LogFactory + .getLog(SensitivityBiomassReferenceY9.class); protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; @Doc("Population") public Population param_pop; - - @Doc("Path to the reference simulation exports") - public String param_referenceExports; + @Doc("Name of the reference simulation") + public String param_referenceSimulation = ""; + @Override public void export(SimulationStorage simulation, Writer out) throws Exception { - File referenceExports=new File (param_referenceExports); - Date lastDate = simulation.getResultStorage().getLastDate(); - double biomass = 0.0; + SimulationStorage referenceSimulation = SimulationStorage + .getSimulation(param_referenceSimulation); + ResultStorage referenceResultStorage = referenceSimulation + .getResultStorage(); + ResultStorage resultStorage = simulation.getResultStorage(); + Date lastDate = resultStorage.getLastDate(); + Double biomass = 0.0; + Double referenceBiomass = 0.0; + for (Population pop : simulation.getParameter().getPopulations()) { if (pop.getName().equals(param_pop.getName())) { - MatrixND mat = simulation.getResultStorage().getMatrix(pop, + + //Get the biomass of the last time step + MatrixND matlastdate = resultStorage.getMatrix(lastDate, pop, ResultName.MATRIX_BIOMASS); - for (MatrixIterator i = mat.iterator(); i.hasNext();) { - i.next(); - Object[] sems = i.getSemanticsCoordinates(); - Date date = (Date) sems[0]; + biomass = matlastdate.sumAll(); - if (date.afterOrEquals(lastDate)) { - biomass = biomass + i.getValue(); - } - } + //Get the reference biomass of the last time step + MatrixND matreferencelastdate = referenceResultStorage + .getMatrix(lastDate, pop, ResultName.MATRIX_BIOMASS); + referenceBiomass = matreferencelastdate.sumAll(); + } } - out.write(Double.toString(biomass)); + out.write(Double.toString(biomass / referenceBiomass)); + } @Override @@ -64,7 +70,7 @@ @Override public String getExportFilename() { - return "SensitivityBiomass"; + return "SensitivityBiomassReferenceY9"; } @Override Added: trunk/exports/SensitivityBiomassRelativeReferenceY12.java =================================================================== --- trunk/exports/SensitivityBiomassRelativeReferenceY12.java (rev 0) +++ trunk/exports/SensitivityBiomassRelativeReferenceY12.java 2009-04-16 13:25:07 UTC (rev 108) @@ -0,0 +1,101 @@ +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.MatrixND; + +import scripts.ResultName; +import fr.ifremer.isisfish.datastore.ResultStorage; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; +import fr.ifremer.isisfish.util.Doc; + +@Doc("Doc for SensitivityBiomass") +public class SensitivityBiomassRelativeReferenceY12 implements + SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory + .getLog(SensitivityBiomassRelativeReferenceY12.class); + + protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; + + @Doc("Population") + public Population param_pop; + + @Doc("Name of the reference simulation") + public String param_referenceSimulation=""; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + SimulationStorage referenceSimulation = SimulationStorage + .getSimulation(param_referenceSimulation); + ResultStorage resultStorage = simulation.getResultStorage(); + ResultStorage referenceResultStorage = referenceSimulation + .getResultStorage(); + Date lastDate = resultStorage.getLastDate(); + Date firstDate = new Date(11); + double biomass = 0.0; + double firstbiomass = 0.0; + double biomassReference = 0.0; + double firstbiomassReference = 0.0; + + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals(param_pop.getName())) { + + //Get the biomass on december of the first year + MatrixND matfirstdate = resultStorage.getMatrix(firstDate, pop, + ResultName.MATRIX_BIOMASS); + firstbiomass = matfirstdate.sumAll(); + + //Get the biomass of the last time step + MatrixND matlastdate = resultStorage.getMatrix(lastDate, pop, + ResultName.MATRIX_BIOMASS); + biomass = matlastdate.sumAll(); + + //Get the biomass on december of the first year + MatrixND matfirstdatereference = referenceResultStorage + .getMatrix(firstDate, pop, ResultName.MATRIX_BIOMASS); + firstbiomassReference = matfirstdatereference.sumAll(); + + //Get the biomass of the last time step + MatrixND matlastdatereference = referenceResultStorage + .getMatrix(lastDate, pop, ResultName.MATRIX_BIOMASS); + biomassReference = matlastdatereference.sumAll(); + + } + } + + out.write(Double.toString((biomass / firstbiomass) + / (biomassReference / firstbiomassReference))); + + } + + @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 "SensitivityBiomassRelativeReferenceY12"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} \ No newline at end of file Modified: trunk/exports/SensitivityBiomassRelativeY6.java =================================================================== --- trunk/exports/SensitivityBiomassRelativeY6.java 2009-04-16 12:00:03 UTC (rev 107) +++ trunk/exports/SensitivityBiomassRelativeY6.java 2009-04-16 13:25:07 UTC (rev 108) @@ -31,14 +31,14 @@ @Override public void export(SimulationStorage simulation, Writer out) throws Exception { - Date lastDate = simulation.getResultStorage().getLastDate(); + ResultStorage resultStorage = simulation.getResultStorage(); + Date lastDate = resultStorage.getLastDate(); Date firstDate = new Date(11); double biomass = 0.0; double firstbiomass = 0.0; for (Population pop : simulation.getParameter().getPopulations()) { - if (pop.getName().equals(param_pop.getName())) { - ResultStorage resultStorage = simulation.getResultStorage(); + if (pop.getName().equals(param_pop.getName())) { //Get the biomass on december of the first year MatrixND matfirstdate = resultStorage.getMatrix(firstDate, pop, Added: trunk/exports/SensitivityCapturesWeightReferenceY7.java =================================================================== --- trunk/exports/SensitivityCapturesWeightReferenceY7.java (rev 0) +++ trunk/exports/SensitivityCapturesWeightReferenceY7.java 2009-04-16 13:25:07 UTC (rev 108) @@ -0,0 +1,94 @@ +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.MatrixND; + +import scripts.ResultName; +import fr.ifremer.isisfish.datastore.ResultStorage; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; +import fr.ifremer.isisfish.util.Doc; + +@Doc("Doc for SensitivityCapturesPoids") +public class SensitivityCapturesWeightReferenceY7 implements SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory + .getLog(SensitivityCapturesWeightReferenceY7.class); + + protected String[] necessaryResult = { ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP }; + + @Doc("Population") + public Population param_pop; + + @Doc("Name of the reference simulation") + public String param_referenceSimulation=""; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + SimulationStorage referenceSimulation = SimulationStorage + .getSimulation(param_referenceSimulation); + ResultStorage referenceResultStorage = referenceSimulation + .getResultStorage(); + ResultStorage resultStorage = simulation.getResultStorage(); + Date lastDate = resultStorage.getLastDate(); + Double capturesWeight = 0.0; + Double capturesWeightReference = 0.0; + + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals(param_pop.getName())) { + for (int i = 0; i < 12; i++) { + + //Get the captures Weight of each month of the last year + MatrixND matlastdate = resultStorage + .getMatrix( + new Date(lastDate.getDate() - i), + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + capturesWeight += matlastdate.sumAll(); + + //Get the reference captures Weight of each month of the last year + MatrixND matlastdatereference = referenceResultStorage + .getMatrix( + new Date(lastDate.getDate() - i), + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + capturesWeightReference += matlastdatereference.sumAll(); + + } + + } + } + + out.write(Double.toString(capturesWeight / capturesWeightReference)); + } + + @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 "SensitivityCapturesWeightReferenceY7"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} \ No newline at end of file Added: trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java =================================================================== --- trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java (rev 0) +++ trunk/exports/SensitivityCapturesWeightRelativeReferenceY10.java 2009-04-16 13:25:07 UTC (rev 108) @@ -0,0 +1,112 @@ +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.MatrixND; + +import scripts.ResultName; +import fr.ifremer.isisfish.datastore.ResultStorage; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; +import fr.ifremer.isisfish.util.Doc; + +@Doc("Doc for SensitivityCapturesPoids") +public class SensitivityCapturesWeightRelativeReferenceY10 implements + SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory + .getLog(SensitivityCapturesWeightRelativeReferenceY10.class); + + protected String[] necessaryResult = { ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP }; + + @Doc("Population") + public Population param_pop; + + @Doc("Name of the reference simulation") + public String param_referenceSimulation = ""; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + SimulationStorage referenceSimulation = SimulationStorage + .getSimulation(param_referenceSimulation); + ResultStorage referenceResultStorage = referenceSimulation + .getResultStorage(); + ResultStorage resultStorage = simulation.getResultStorage(); + Date lastDate = resultStorage.getLastDate(); + Double capturesWeight = 0.0; + Double capturesWeightfirst = 0.0; + Double capturesWeightreference = 0.0; + Double capturesWeightfirstreference = 0.0; + + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals(param_pop.getName())) { + for (int i = 0; i < 12; i++) { + + //Get the captures Weight of each month of the last year + MatrixND matlastdate = resultStorage + .getMatrix( + new Date(lastDate.getDate() - i), + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + capturesWeight += matlastdate.sumAll(); + + //Get the captures Weight of each month of the first year + MatrixND matfirstdate = resultStorage + .getMatrix( + new Date(i), + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + capturesWeightfirst += matfirstdate.sumAll(); + + //Get the reference captures Weight of each month of the last year + MatrixND matlastdatereference = referenceResultStorage + .getMatrix( + new Date(lastDate.getDate() - i), + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + capturesWeightreference += matlastdatereference.sumAll(); + + //Get the reference captures Weight of each month of the first year + MatrixND matfirstdatereference = referenceResultStorage + .getMatrix( + new Date(i), + pop, + ResultName.MATRIX_CATCH_WEIGHT_PER_STRATEGY_MET_PER_ZONE_POP); + capturesWeightfirstreference += matfirstdatereference + .sumAll(); + } + } + } + out.write(Double.toString((capturesWeight / capturesWeightfirst) + / (capturesWeightreference / capturesWeightfirstreference))); + } + + @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 "SensitivityCapturesWeightRelativeReferenceY10"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} Added: trunk/exports/SensitivityGenitorBiomassReferenceY8.java =================================================================== --- trunk/exports/SensitivityGenitorBiomassReferenceY8.java (rev 0) +++ trunk/exports/SensitivityGenitorBiomassReferenceY8.java 2009-04-16 13:25:07 UTC (rev 108) @@ -0,0 +1,103 @@ +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.ResultStorage; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.entities.PopulationGroup; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; +import fr.ifremer.isisfish.util.Doc; + +@Doc("Doc for SensitivityBiomass") +public class SensitivityGenitorBiomassReferenceY8 implements SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory + .getLog(SensitivityGenitorBiomassReferenceY8.class); + + protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; + + @Doc("Population") + public Population param_pop; + + @Doc("Name of the reference simulation") + public String param_referenceSimulation = ""; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + SimulationStorage referenceSimulation = SimulationStorage + .getSimulation(param_referenceSimulation); + ResultStorage referenceResultStorage = referenceSimulation + .getResultStorage(); + ResultStorage resultStorage = simulation.getResultStorage(); + Date lastDate = resultStorage.getLastDate(); + Double biomass = 0.0; + Double referenceBiomass = 0.0; + + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals(param_pop.getName())) { + + //Get the biomass of the last time step + MatrixND matlastdate = resultStorage.getMatrix(pop, + ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = matlastdate.iterator(); i.hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + PopulationGroup group = (PopulationGroup) sems[1]; + Date date = (Date) sems[0]; + if (date.equals(lastDate)) { + biomass += i.getValue() * group.getReproductionRate(); + } + } + + //Get the reference biomass of the last time step + MatrixND matlastdatereference = referenceResultStorage + .getMatrix(pop, ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = matlastdatereference.iterator(); i + .hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + PopulationGroup group = (PopulationGroup) sems[1]; + Date date = (Date) sems[0]; + if (date.equals(lastDate)) { + referenceBiomass += i.getValue() + * group.getReproductionRate(); + } + } + } + } + out.write(Double.toString(biomass / referenceBiomass)); + } + + @Override + public String getDescription() { + return _("Biomass of the genitors for the last time step. Biomass is the sum on the groups and zones"); + } + + @Override + public String getExportFilename() { + return "SensitivityGenitorBiomassReferenceY8"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} Added: trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java =================================================================== --- trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java (rev 0) +++ trunk/exports/SensitivityGenitorBiomassRelativeReferenceY11.java 2009-04-16 13:25:07 UTC (rev 108) @@ -0,0 +1,138 @@ +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.ResultStorage; +import fr.ifremer.isisfish.datastore.SimulationStorage; +import fr.ifremer.isisfish.entities.Population; +import fr.ifremer.isisfish.entities.PopulationGroup; +import fr.ifremer.isisfish.export.SensitivityExport; +import fr.ifremer.isisfish.types.Date; +import fr.ifremer.isisfish.util.Doc; + +@Doc("Doc for SensitivityBiomass") +public class SensitivityGenitorBiomassRelativeReferenceY11 implements + SensitivityExport { + + /** to use log facility, just put in your code: log.info("..."); */ + static private Log log = LogFactory + .getLog(SensitivityGenitorBiomassRelativeReferenceY11.class); + + protected String[] necessaryResult = { ResultName.MATRIX_BIOMASS }; + + @Doc("Population") + public Population param_pop; + + @Doc("Name of the reference simulation") + public String param_referenceSimulation = ""; + + @Override + public void export(SimulationStorage simulation, Writer out) + throws Exception { + SimulationStorage referenceSimulation = SimulationStorage + .getSimulation(param_referenceSimulation); + ResultStorage resultStorage = simulation.getResultStorage(); + ResultStorage referenceResultStorage = referenceSimulation + .getResultStorage(); + Date lastDate = resultStorage.getLastDate(); + Date firstDate = new Date(11); + double biomass = 0.0; + double firstbiomass = 0.0; + double biomassReference = 0.0; + double firstbiomassReference = 0.0; + + for (Population pop : simulation.getParameter().getPopulations()) { + if (pop.getName().equals(param_pop.getName())) { + + //Get the biomass of the first time step + MatrixND matfirstdate = resultStorage.getMatrix(pop, + ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = matfirstdate.iterator(); i.hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + PopulationGroup group = (PopulationGroup) sems[1]; + Date date = (Date) sems[0]; + if (date.equals(firstDate)) { + firstbiomass += i.getValue() + * group.getReproductionRate(); + } + } + + //Get the biomass of the last time step + MatrixND matlastdate = resultStorage.getMatrix(pop, + ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = matlastdate.iterator(); i.hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + PopulationGroup group = (PopulationGroup) sems[1]; + Date date = (Date) sems[0]; + if (date.equals(lastDate)) { + biomass = biomass + i.getValue() + * group.getReproductionRate(); + } + } + + //Get the reference biomass of the first time step + MatrixND matfirstdatereference = referenceResultStorage + .getMatrix(pop, ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = matfirstdatereference.iterator(); i + .hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + PopulationGroup group = (PopulationGroup) sems[1]; + Date date = (Date) sems[0]; + if (date.equals(firstDate)) { + firstbiomassReference += i.getValue() + * group.getReproductionRate(); + } + } + + //Get the reference biomass of the last time step + MatrixND matlastdatereference = referenceResultStorage + .getMatrix(pop, ResultName.MATRIX_BIOMASS); + for (MatrixIterator i = matlastdatereference.iterator(); i + .hasNext();) { + i.next(); + Object[] sems = i.getSemanticsCoordinates(); + PopulationGroup group = (PopulationGroup) sems[1]; + Date date = (Date) sems[0]; + if (date.equals(lastDate)) { + biomassReference += i.getValue() + * group.getReproductionRate(); + } + } + } + } + out.write(Double.toString((biomass / firstbiomass) + / (biomassReference / firstbiomassReference))); + } + + @Override + public String getDescription() { + return _("Biomass of the genitors for the last time step. Biomass is the sum on the groups and zones"); + } + + @Override + public String getExportFilename() { + return "SensitivityGenitorBiomassRelativeReferenceY11"; + } + + @Override + public String getExtensionFilename() { + return ".csv"; + } + + @Override + public String[] getNecessaryResult() { + return this.necessaryResult; + } + +} \ No newline at end of file Modified: trunk/exports/SensitivityGenitorBiomassRelativeY5.java =================================================================== --- trunk/exports/SensitivityGenitorBiomassRelativeY5.java 2009-04-16 12:00:03 UTC (rev 107) +++ trunk/exports/SensitivityGenitorBiomassRelativeY5.java 2009-04-16 13:25:07 UTC (rev 108) @@ -42,7 +42,7 @@ if (pop.getName().equals(param_pop.getName())) { ResultStorage resultStorage = simulation.getResultStorage(); - //Get the biomass of the last time step + //Get the biomass of the first time step MatrixND matfirstdate = resultStorage.getMatrix(pop, ResultName.MATRIX_BIOMASS); for (MatrixIterator i = matfirstdate.iterator(); i.hasNext();) {

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