public void InitTrajectoryTask() { TaskVectorN taskList = dataModel.getTaskList(); // get the trajectory task object trajectoryTask = (CTrajectoryTask)taskList.getByName("Time-Course"); // if there isn't one if (trajectoryTask == null) { // create a new one trajectoryTask = new CTrajectoryTask(); // remove any existing trajectory task just to be sure since in // theory only the cast might have failed above taskList.removeByName("Time-Course"); // add the new time course task to the task list taskList.add(trajectoryTask, true); } // run a deterministic time course trajectoryTask.setMethodType(CCopasiMethod.deterministic); // get the problem for the task to set some parameters CTrajectoryProblem problem = (CTrajectoryProblem)trajectoryTask.getProblem(); // pass a pointer of the model to the problem problem.setModel(dataModel.getModel()); // we want the model to be updated for each simulation trajectoryTask.setUpdateModel(true); // simulate only one step problem.setStepNumber(1); model.setInitialTime(0.0); // set some parameters for the LSODA method through the method CTrajectoryMethod method = (CTrajectoryMethod)trajectoryTask.getMethod(); CCopasiParameter parameter = method.getParameter("Absolute Tolerance"); parameter.setDblValue(1.0e-12); }
static void Main(string[] args) { Debug.Assert(CRootContainer.getRoot() != null); // create a new datamodel CDataModel dataModel = CRootContainer.addDatamodel(); Debug.Assert(CRootContainer.getDatamodelList().size() == 1); // the only argument to the main routine should be the name of an SBML file if (args.Length == 1) { string filename = args[0]; try { // load the model dataModel.importSBML(filename); } catch { System.Console.Error.WriteLine("Error while importing the model from file named \"" + filename + "\"."); System.Environment.Exit(1); } CModel model = dataModel.getModel(); Debug.Assert(model != null); // create a report with the correct filename and all the species against // time. CReportDefinitionVector reports = dataModel.getReportDefinitionList(); // create a new report definition object CReportDefinition report = reports.createReportDefinition("Report", "Output for timecourse"); // set the task type for the report definition to timecourse report.setTaskType(CTaskEnum.Task_timeCourse); // we don't want a table report.setIsTable(false); // the entries in the output should be seperated by a ", " report.setSeparator(new CCopasiReportSeparator(", ")); // we need a handle to the header and the body // the header will display the ids of the metabolites and "time" for // the first column // the body will contain the actual timecourse data ReportItemVector header = report.getHeaderAddr(); ReportItemVector body = report.getBodyAddr(); body.Add(new CRegisteredCommonName(model.getObject(new CCommonName("Reference=Time")).getCN().getString())); body.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); header.Add(new CRegisteredCommonName(new CDataString("time").getCN().getString())); header.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); uint i, iMax = (uint)model.getMetabolites().size(); for (i = 0; i < iMax; ++i) { CMetab metab = model.getMetabolite(i); Debug.Assert(metab != null); // we don't want output for FIXED metabolites right now if (metab.getStatus() != CModelEntity.Status_FIXED) { // we want the concentration oin the output // alternatively, we could use "Reference=Amount" to get the // particle number body.Add(new CRegisteredCommonName(metab.getObject(new CCommonName("Reference=Concentration")).getCN().getString())); // add the corresponding id to the header header.Add(new CRegisteredCommonName(new CDataString(metab.getSBMLId()).getCN().getString())); // after each entry, we need a seperator if (i != iMax - 1) { body.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); header.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); } } } // get the trajectory task object CTrajectoryTask trajectoryTask = (CTrajectoryTask)dataModel.getTask("Time-Course"); // run a deterministic time course trajectoryTask.setMethodType(CTaskEnum.Method_deterministic); // pass a pointer of the model to the problem trajectoryTask.getProblem().setModel(dataModel.getModel()); // actiavate the task so that it will be run when the model is saved // and passed to CopasiSE trajectoryTask.setScheduled(true); // set the report for the task trajectoryTask.getReport().setReportDefinition(report); // set the output filename trajectoryTask.getReport().setTarget("example3.txt"); // don't append output if the file exists, but overwrite the file trajectoryTask.getReport().setAppend(false); // get the problem for the task to set some parameters CTrajectoryProblem problem = (CTrajectoryProblem)trajectoryTask.getProblem(); // simulate 100 steps problem.setStepNumber(100); // start at time 0 dataModel.getModel().setInitialTime(0.0); // simulate a duration of 10 time units problem.setDuration(10); // tell the problem to actually generate time series data problem.setTimeSeriesRequested(true); // set some parameters for the LSODA method through the method CTrajectoryMethod method = (CTrajectoryMethod)trajectoryTask.getMethod(); CCopasiParameter parameter = method.getParameter("Absolute Tolerance"); Debug.Assert(parameter != null); Debug.Assert(parameter.getType() == CCopasiParameter.Type_DOUBLE); parameter.setDblValue(1.0e-12); bool result = true; try { // now we run the actual trajectory result = trajectoryTask.processWithOutputFlags(true, (int)CCopasiTask.ONLY_TIME_SERIES); } catch { System.Console.Error.WriteLine("Error. Running the time course simulation failed."); String lastErrors = trajectoryTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } if (result == false) { System.Console.Error.WriteLine("An error occured while running the time course simulation."); String lastErrors = trajectoryTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } // look at the timeseries CTimeSeries timeSeries = trajectoryTask.getTimeSeries(); // we simulated 100 steps, including the initial state, this should be // 101 step in the timeseries Debug.Assert(timeSeries.getRecordedSteps() == 101); System.Console.WriteLine("The time series consists of " + System.Convert.ToString(timeSeries.getRecordedSteps()) + "."); System.Console.WriteLine("Each step contains " + System.Convert.ToString(timeSeries.getNumVariables()) + " variables."); System.Console.WriteLine("The final state is: "); iMax = (uint)timeSeries.getNumVariables(); uint lastIndex = (uint)timeSeries.getRecordedSteps() - 1; for (i = 0; i < iMax; ++i) { // here we get the particle number (at least for the species) // the unit of the other variables may not be particle numbers // the concentration data can be acquired with getConcentrationData System.Console.WriteLine(timeSeries.getTitle(i) + ": " + System.Convert.ToString(timeSeries.getData(lastIndex, i))); } } else { System.Console.Error.WriteLine("Usage: example3 SBMLFILE"); System.Environment.Exit(1); } }
static void Main() { Debug.Assert(CCopasiRootContainer.getRoot() != null); // create a new datamodel CCopasiDataModel dataModel = CCopasiRootContainer.addDatamodel(); Debug.Assert(CCopasiRootContainer.getDatamodelList().size() == 1); // get the model from the datamodel CModel model = dataModel.getModel(); Debug.Assert(model != null); model.setVolumeUnit(CUnit.fl); model.setTimeUnit(CUnit.s); model.setQuantityUnit(CUnit.fMol); CModelValue fixedModelValue = model.createModelValue("F"); Debug.Assert(fixedModelValue != null); fixedModelValue.setStatus(CModelEntity.FIXED); fixedModelValue.setInitialValue(3.0); CModelValue variableModelValue = model.createModelValue("V"); Debug.Assert(variableModelValue != null); variableModelValue.setStatus(CModelEntity.ASSIGNMENT); // we create a very simple assignment that is easy on the optimization // a parabole with the minimum at x=6 should do just fine string s = fixedModelValue.getValueReference().getCN().getString(); s = "(<" + s + "> - 6.0)^2"; variableModelValue.setExpression(s); // now we compile the model and tell COPASI which values have changed so // that COPASI can update the values that depend on those model.compileIfNecessary(); ObjectStdVector changedObjects = new ObjectStdVector(); changedObjects.Add(fixedModelValue.getInitialValueReference()); changedObjects.Add(variableModelValue.getInitialValueReference()); model.updateInitialValues(changedObjects); // now we set up the optimization // we want to do an optimization for the time course // so we have to set up the time course task first CTrajectoryTask timeCourseTask = (CTrajectoryTask)dataModel.getTask("Time-Course"); Debug.Assert(timeCourseTask != null); // since for this example it really doesn't matter how long we run the time course // we run for 1 second and calculate 10 steps // run a deterministic time course timeCourseTask.setMethodType(CTaskEnum.deterministic); // pass a pointer of the model to the problem timeCourseTask.getProblem().setModel(dataModel.getModel()); // get the problem for the task to set some parameters CTrajectoryProblem problem = (CTrajectoryProblem)timeCourseTask.getProblem(); Debug.Assert(problem != null); // simulate 10 steps problem.setStepNumber(10); // start at time 0 dataModel.getModel().setInitialTime(0.0); // simulate a duration of 1 time units problem.setDuration(1); // tell the problem to actually generate time series data problem.setTimeSeriesRequested(true); // get the optimization task COptTask optTask = (COptTask)dataModel.getTask("Optimization"); Debug.Assert(optTask != null); // we want to use Levenberg-Marquardt as the optimization method optTask.setMethodType(CTaskEnum.LevenbergMarquardt); // next we need to set subtask type on the problem COptProblem optProblem = (COptProblem)optTask.getProblem(); Debug.Assert(optProblem != null); optProblem.setSubtaskType(CTaskEnum.timeCourse); // we create the objective function // we want to minimize the value of the variable model value at the end of // the simulation // the objective function is normally minimized string objectiveFunction = variableModelValue.getObject(new CCopasiObjectName("Reference=Value")).getCN().getString(); // we need to put the angled brackets around the common name of the object objectiveFunction = "<" + objectiveFunction + ">"; // now we set the objective function in the problem optProblem.setObjectiveFunction(objectiveFunction); // now we create the optimization items // i.e. the model elements that have to be changed during the optimization // in order to get to the optimal solution COptItem optItem = optProblem.addOptItem(new CCopasiObjectName(fixedModelValue.getObject(new CCopasiObjectName("Reference=InitialValue")).getCN())); // we want to change the fixed model value from -100 to +100 with a start // value of 50 optItem.setStartValue(50.0); optItem.setLowerBound(new CCopasiObjectName("-100")); optItem.setUpperBound(new CCopasiObjectName("100")); // now we set some parameters on the method // these parameters are specific to the method type we set above // (in this case Levenberg-Marquardt) COptMethod optMethod = (COptMethod)optTask.getMethod(); Debug.Assert(optMethod != null); // now we set some method parameters for the optimization method // iteration limit CCopasiParameter parameter = optMethod.getParameter("Iteration Limit"); Debug.Assert(parameter != null); parameter.setIntValue(2000); // tolerance parameter = optMethod.getParameter("Tolerance"); Debug.Assert(parameter != null); parameter.setDblValue(1.0e-5); // create a report with the correct filename and all the species against // time. CReportDefinitionVector reports = dataModel.getReportDefinitionList(); // create a new report definition object CReportDefinition report = reports.createReportDefinition("Report", "Output for optimization"); // set the task type for the report definition to timecourse report.setTaskType(CTaskEnum.optimization); // we don't want a table report.setIsTable(false); // the entries in the output should be seperated by a ", " report.setSeparator(new CCopasiReportSeparator(", ")); // we need a handle to the header and the body // the header will display the ids of the metabolites and "time" for // the first column // the body will contain the actual timecourse data ReportItemVector header = report.getHeaderAddr(); ReportItemVector body = report.getBodyAddr(); // in the report header we write two strings and a separator header.Add(new CRegisteredObjectName(new CCopasiStaticString("best value of objective function").getCN().getString())); header.Add(new CRegisteredObjectName(report.getSeparator().getCN().getString())); header.Add(new CRegisteredObjectName(new CCopasiStaticString("initial value of F").getCN().getString())); // in the report body we write the best value of the objective function and // the initial value of the fixed parameter separated by a komma body.Add(new CRegisteredObjectName(optProblem.getObject(new CCopasiObjectName("Reference=Best Value")).getCN().getString())); body.Add(new CRegisteredObjectName(report.getSeparator().getCN().getString())); body.Add(new CRegisteredObjectName(fixedModelValue.getObject(new CCopasiObjectName("Reference=InitialValue")).getCN().getString())); // set the report for the task optTask.getReport().setReportDefinition(report); // set the output filename optTask.getReport().setTarget("example5.txt"); // don't append output if the file exists, but overwrite the file optTask.getReport().setAppend(false); bool result = false; try { result = optTask.processWithOutputFlags(true, (int)CCopasiTask.ONLY_TIME_SERIES); } catch (System.ApplicationException e) { System.Console.Error.WriteLine("ERROR: " + e.Message); String lastErrors = optTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } if (!result) { System.Console.Error.WriteLine("Running the optimization failed."); String lastErrors = optTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } // now we check if the optimization actually got the correct result // the best value it should have is 0 and the best parameter value for // that result should be 6 for the initial value of the fixed parameter double bestValue = optProblem.getSolutionValue(); Debug.Assert(System.Math.Abs(bestValue) < 1e-3); // we should only have one solution variable since we only have one // optimization item Debug.Assert(optProblem.getSolutionVariables().size() == 1); double solution = optProblem.getSolutionVariables().get(0); Debug.Assert(System.Math.Abs((solution - 6.0) / 6.0) < 1e-3); }
static void Main(string[] args) { Debug.Assert(CRootContainer.getRoot() != null); // create a new datamodel CDataModel dataModel = CRootContainer.addDatamodel(); Debug.Assert(CRootContainer.getDatamodelList().size() == 1); // first we load a simple model try { // load the model dataModel.importSBMLFromString(MODEL_STRING); } catch { System.Console.Error.WriteLine("Error while importing the model."); System.Environment.Exit(1); } // now we need to run some time course simulation to get data to fit // against // get the trajectory task object CTrajectoryTask trajectoryTask = (CTrajectoryTask)dataModel.getTask("Time-Course"); // run a deterministic time course trajectoryTask.setMethodType(CTaskEnum.Method_deterministic); // pass a pointer of the model to the problem trajectoryTask.getProblem().setModel(dataModel.getModel()); // activate the task so that it will be run when the model is saved // and passed to CopasiSE trajectoryTask.setScheduled(true); // get the problem for the task to set some parameters CTrajectoryProblem problem = (CTrajectoryProblem)trajectoryTask.getProblem(); // simulate 4000 steps problem.setStepNumber(4000); // start at time 0 dataModel.getModel().setInitialTime(0.0); // simulate a duration of 400 time units problem.setDuration(400); // tell the problem to actually generate time series data problem.setTimeSeriesRequested(true); // set some parameters for the LSODA method through the method // Currently we don't use the method to set anything //CTrajectoryMethod method = (CTrajectoryMethod)trajectoryTask.getMethod(); bool result = true; try { // now we run the actual trajectory result = trajectoryTask.processWithOutputFlags(true, (int)CCopasiTask.ONLY_TIME_SERIES); } catch { System.Console.Error.WriteLine("Error. Running the time course simulation failed."); String lastErrors = trajectoryTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } if (result == false) { System.Console.Error.WriteLine("An error occured while running the time course simulation."); String lastErrors = trajectoryTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } // we write the data to a file and add some noise to it // This is necessary since COPASI can only read experimental data from // file. CTimeSeries timeSeries = trajectoryTask.getTimeSeries(); // we simulated 100 steps, including the initial state, this should be // 101 step in the timeseries Debug.Assert(timeSeries.getRecordedSteps() == 4001); uint i; uint iMax = (uint)timeSeries.getNumVariables(); // there should be four variables, the three metabolites and time Debug.Assert(iMax == 5); uint lastIndex = (uint)timeSeries.getRecordedSteps() - 1; // open the file // we need to remember in which order the variables are written to file // since we need to specify this later in the parameter fitting task List <uint> indexSet = new List <uint>(); List <CMetab> metabVector = new List <CMetab>(); // write the header // the first variable in a time series is a always time, for the rest // of the variables, we use the SBML id in the header double random = 0.0; System.Random rand_gen = new System.Random(); try { System.IO.StreamWriter os = new System.IO.StreamWriter("fakedata_example6.txt"); os.Write("# time "); CKeyFactory keyFactory = CRootContainer.getKeyFactory(); Debug.Assert(keyFactory != null); for (i = 1; i < iMax; ++i) { string key = timeSeries.getKey(i); CDataObject obj = keyFactory.get(key); Debug.Assert(obj != null); // only write header data or metabolites System.Type type = obj.GetType(); if (type.FullName.Equals("org.COPASI.CMetab")) { os.Write(", "); os.Write(timeSeries.getSBMLId(i, dataModel)); CMetab m = (CMetab)obj; indexSet.Add(i); metabVector.Add(m); } } os.Write("\n"); double data = 0.0; for (i = 0; i < lastIndex; ++i) { uint j; string s = ""; for (j = 0; j < iMax; ++j) { // we only want to write the data for metabolites // the compartment does not interest us here if (j == 0 || indexSet.Contains(j)) { // write the data with some noise (+-5% max) random = rand_gen.NextDouble(); data = timeSeries.getConcentrationData(i, j); // don't add noise to the time if (j != 0) { data += data * (random * 0.1 - 0.05); } s = s + (System.Convert.ToString(data)); s = s + ", "; } } // remove the last two characters again os.Write(s.Substring(0, s.Length - 2)); os.Write("\n"); } os.Close(); } catch (System.ApplicationException e) { System.Console.Error.WriteLine("Error. Could not write time course data to file."); System.Console.WriteLine(e.Message); System.Environment.Exit(1); } // now we change the parameter values to see if the parameter fitting // can really find the original values random = rand_gen.NextDouble() * 10; CReaction reaction = dataModel.getModel().getReaction(0); // we know that it is an irreversible mass action, so there is one // parameter Debug.Assert(reaction.getParameters().size() == 1); Debug.Assert(reaction.isLocalParameter(0)); // the parameter of a irreversible mass action is called k1 reaction.setParameterValue("k1", random); reaction = dataModel.getModel().getReaction(1); // we know that it is an irreversible mass action, so there is one // parameter Debug.Assert(reaction.getParameters().size() == 1); Debug.Assert(reaction.isLocalParameter(0)); reaction.setParameterValue("k1", random); CFitTask fitTask = (CFitTask)dataModel.addTask(CTaskEnum.Task_parameterFitting); Debug.Assert(fitTask != null); // the method in a fit task is an instance of COptMethod or a subclass of // it. COptMethod fitMethod = (COptMethod)fitTask.getMethod(); Debug.Assert(fitMethod != null); // the object must be an instance of COptMethod or a subclass thereof // (CFitMethod) CFitProblem fitProblem = (CFitProblem)fitTask.getProblem(); Debug.Assert(fitProblem != null); CExperimentSet experimentSet = (CExperimentSet)fitProblem.getParameter("Experiment Set"); Debug.Assert(experimentSet != null); // first experiment (we only have one here) CExperiment experiment = new CExperiment(dataModel); Debug.Assert(experiment != null); // tell COPASI where to find the data // reading data from string is not possible with the current C++ API experiment.setFileName("fakedata_example6.txt"); // we have to tell COPASI that the data for the experiment is a komma // separated list (the default is TAB separated) experiment.setSeparator(","); // the data start in row 1 and goes to row 4001 experiment.setFirstRow(1); Debug.Assert(experiment.getFirstRow() == 1); experiment.setLastRow(4001); Debug.Assert(experiment.getLastRow() == 4001); experiment.setHeaderRow(1); Debug.Assert(experiment.getHeaderRow() == 1); experiment.setExperimentType(CTaskEnum.Task_timeCourse); Debug.Assert(experiment.getExperimentType() == CTaskEnum.Task_timeCourse); experiment.setNumColumns(4); Debug.Assert(experiment.getNumColumns() == 4); CExperimentObjectMap objectMap = experiment.getObjectMap(); Debug.Assert(objectMap != null); result = objectMap.setNumCols(4); Debug.Assert(result == true); result = objectMap.setRole(0, CExperiment.time); Debug.Assert(result == true); Debug.Assert(objectMap.getRole(0) == CExperiment.time); CModel model = dataModel.getModel(); Debug.Assert(model != null); CDataObject timeReference = model.getValueReference(); Debug.Assert(timeReference != null); objectMap.setObjectCN(0, timeReference.getCN().getString()); // now we tell COPASI which column contain the concentrations of // metabolites and belong to dependent variables objectMap.setRole(1, CExperiment.dependent); CMetab metab = metabVector[0]; Debug.Assert(metab != null); CDataObject particleReference = metab.getConcentrationReference(); Debug.Assert(particleReference != null); objectMap.setObjectCN(1, particleReference.getCN().getString()); objectMap.setRole(2, CExperiment.dependent); metab = metabVector[1]; Debug.Assert(metab != null); particleReference = metab.getConcentrationReference(); Debug.Assert(particleReference != null); objectMap.setObjectCN(2, particleReference.getCN().getString()); objectMap.setRole(3, CExperiment.dependent); metab = metabVector[2]; Debug.Assert(metab != null); particleReference = metab.getConcentrationReference(); Debug.Assert(particleReference != null); objectMap.setObjectCN(3, particleReference.getCN().getString()); experimentSet.addExperiment(experiment); Debug.Assert(experimentSet.getExperimentCount() == 1); // addExperiment makes a copy, so we need to get the added experiment // again experiment = experimentSet.getExperiment(0); Debug.Assert(experiment != null); // now we have to define the two fit items for the two local parameters // of the two reactions reaction = model.getReaction(0); Debug.Assert(reaction != null); Debug.Assert(reaction.isLocalParameter(0) == true); CCopasiParameter parameter = reaction.getParameters().getParameter(0); Debug.Assert(parameter != null); // define a CFitItem CDataObject parameterReference = parameter.getValueReference(); Debug.Assert(parameterReference != null); CFitItem fitItem1 = new CFitItem(dataModel); Debug.Assert(fitItem1 != null); fitItem1.setObjectCN(parameterReference.getCN()); fitItem1.setStartValue(4.0); fitItem1.setLowerBound(new CCommonName("0.00001")); fitItem1.setUpperBound(new CCommonName("10")); // add the fit item to the correct parameter group CCopasiParameterGroup optimizationItemGroup = (CCopasiParameterGroup)fitProblem.getParameter("OptimizationItemList"); Debug.Assert(optimizationItemGroup != null); optimizationItemGroup.addParameter(fitItem1); reaction = model.getReaction(1); Debug.Assert(reaction != null); Debug.Assert(reaction.isLocalParameter(0) == true); parameter = reaction.getParameters().getParameter(0); Debug.Assert(parameter != null); // define a CFitItem parameterReference = parameter.getValueReference(); Debug.Assert(parameterReference != null); CFitItem fitItem2 = new CFitItem(dataModel); Debug.Assert(fitItem2 != null); fitItem2.setObjectCN(parameterReference.getCN()); fitItem2.setStartValue(4.0); fitItem2.setLowerBound(new CCommonName("0.00001")); fitItem2.setUpperBound(new CCommonName("10")); // add the fit item to the correct parameter group optimizationItemGroup.addParameter(fitItem2); result = true; try { // running the task for this example will probably take some time System.Console.WriteLine("This can take some time..."); result = fitTask.processWithOutputFlags(true, (int)CCopasiTask.ONLY_TIME_SERIES); } catch { System.Console.Error.WriteLine("Error. Parameter fitting failed."); String lastErrors = fitTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } Debug.Assert(result == true); // assert that there are two optimization items Debug.Assert(fitProblem.getOptItemList().Count == 2); // the order should be the order in whih we added the items above COptItem optItem1 = fitProblem.getOptItemList()[0]; COptItem optItem2 = fitProblem.getOptItemList()[1]; // the actual results are stored in the fit problem Debug.Assert(fitProblem.getSolutionVariables().size() == 2); System.Console.WriteLine("value for " + optItem1.getObject().getCN().getString() + ": " + fitProblem.getSolutionVariables().get(0)); System.Console.WriteLine("value for " + optItem2.getObject().getCN().getString() + ": " + fitProblem.getSolutionVariables().get(1)); // depending on the noise, the fit can be quite bad, so we are a litle // relaxed here (we should be within 3% of the original values) Debug.Assert((System.Math.Abs(fitProblem.getSolutionVariables().get(0) - 0.03) / 0.03) < 3e-2); Debug.Assert((System.Math.Abs(fitProblem.getSolutionVariables().get(1) - 0.004) / 0.004) < 3e-2); }
static void Main() { Debug.Assert(CRootContainer.getRoot() != null); // create a new datamodel CDataModel dataModel = CRootContainer.addDatamodel(); Debug.Assert(CRootContainer.getDatamodelList().size() == 1); // the only argument to the main routine should be the name of an SBML file try { // load the model dataModel.importSBMLFromString(MODEL_STRING); } catch { System.Console.Error.WriteLine("Error while importing the model from the given String."); System.Environment.Exit(1); } CModel model = dataModel.getModel(); Debug.Assert(model != null); // create a report with the correct filename and all the species against // time. CReportDefinitionVector reports = dataModel.getReportDefinitionList(); // create a new report definition object CReportDefinition report = reports.createReportDefinition("Report", "Output for timecourse"); // set the task type for the report definition to timecourse report.setTaskType(CTaskEnum.Task_timeCourse); // we don't want a table report.setIsTable(false); // the entries in the output should be seperated by a ", " report.setSeparator(new CCopasiReportSeparator(", ")); // we need a handle to the header and the body // the header will display the ids of the metabolites and "time" for // the first column // the body will contain the actual timecourse data ReportItemVector header = report.getHeaderAddr(); ReportItemVector body = report.getBodyAddr(); body.Add(new CRegisteredCommonName(new CCommonName(dataModel.getModel().getCN().getString() + ",Reference=Time").getString())); body.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); header.Add(new CRegisteredCommonName(new CDataString("time").getCN().getString())); header.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); uint i, iMax = (uint)model.getMetabolites().size(); for (i = 0; i < iMax; ++i) { CMetab metab = model.getMetabolite(i); Debug.Assert(metab != null); // we don't want output for FIXED metabolites right now if (metab.getStatus() != CModelEntity.Status_FIXED) { // we want the concentration oin the output // alternatively, we could use "Reference=Amount" to get the // particle number body.Add(new CRegisteredCommonName(metab.getObject(new CCommonName("Reference=Concentration")).getCN().getString())); // add the corresponding id to the header header.Add(new CRegisteredCommonName(new CDataString(metab.getSBMLId()).getCN().getString())); if (i != iMax - 1) { // after each entry, we need a seperator body.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); // and a seperator header.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString())); } } } // get the trajectory task object CTrajectoryTask trajectoryTask = (CTrajectoryTask)dataModel.getTask("Time-Course"); // run a stochastic time course trajectoryTask.setMethodType(CTaskEnum.Method_stochastic); // pass a pointer of the model to the problem trajectoryTask.getProblem().setModel(dataModel.getModel()); // we don't want the trajectory task to run by itself, but we want to // run it from a scan, so we deactivate the standalone trajectory task trajectoryTask.setScheduled(false); // get the problem for the task to set some parameters CTrajectoryProblem problem = (CTrajectoryProblem)trajectoryTask.getProblem(); // simulate 100 steps problem.setStepNumber(100); // start at time 0 dataModel.getModel().setInitialTime(0.0); // simulate a duration of 10 time units problem.setDuration(10); // tell the problem to actually generate time series data problem.setTimeSeriesRequested(true); // now we set up the scan CScanTask scanTask = (CScanTask)dataModel.getTask("Scan"); // get the problem CScanProblem scanProblem = (CScanProblem)scanTask.getProblem(); Debug.Assert(scanProblem != null); // set the model for the problem scanProblem.setModel(dataModel.getModel()); // activate the task so that is is run // if the model is saved and passed to CopasiSE scanTask.setScheduled(true); // set the report for the task scanTask.getReport().setReportDefinition(report); // set the output file for the report scanTask.getReport().setTarget("example4.txt"); // don't append to an existing file, but overwrite scanTask.getReport().setAppend(false); // tell the scan that we want to make a scan over a trajectory task scanProblem.setSubtask(CTaskEnum.Task_timeCourse); // we just want to run the timecourse task a number of times, so we // create a repeat item with 100 repeats scanProblem.addScanItem(CScanProblem.SCAN_REPEAT, 100); // we want the output from the trajectory task scanProblem.setOutputInSubtask(true); // we don't want to set the initial conditions of the model to the end // state of the last run scanProblem.setContinueFromCurrentState(false); try { // now we run the actual trajectory scanTask.processWithOutputFlags(true, (int)CCopasiTask.ONLY_TIME_SERIES); } catch { System.Console.Error.WriteLine("Error. Running the scan failed."); String lastErrors = scanTask.getProcessError(); // check if there are additional error messages if (!string.IsNullOrEmpty(lastErrors)) { // print the messages in chronological order System.Console.Error.WriteLine(lastErrors); } System.Environment.Exit(1); } }