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() { Debug.Assert(CRootContainer.getRoot() != null); // create a new datamodel CDataModel dataModel = CRootContainer.addDatamodel(); Debug.Assert(CRootContainer.getDatamodelList().size() == 1); // get the model from the datamodel CModel model = dataModel.getModel(); Debug.Assert(model != null); // set the units for the model // we want seconds as the time unit // microliter as the volume units // and nanomole as the substance units model.setTimeUnit(CUnit.s); model.setVolumeUnit(CUnit.microl); model.setQuantityUnit(CUnit.nMol); // we have to keep a set of all the initial values that are changed during // the model building process // They are needed after the model has been built to make sure all initial // values are set to the correct initial value ObjectStdVector changedObjects = new ObjectStdVector(); // create a compartment with the name cell and an initial volume of 5.0 // microliter CCompartment compartment = model.createCompartment("cell", 5.0); CDataObject obj = compartment.getInitialValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); Debug.Assert(compartment != null); Debug.Assert(model.getCompartments().size() == 1); // create a new metabolite with the name glucose and an inital // concentration of 10 nanomol // the metabolite belongs to the compartment we created and is is to be // fixed CMetab glucose = model.createMetabolite("glucose", compartment.getObjectName(), 10.0, CModelEntity.Status_FIXED); obj = glucose.getInitialValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); Debug.Assert(glucose != null); Debug.Assert(model.getMetabolites().size() == 1); // create a second metabolite called glucose-6-phosphate with an initial // concentration of 0. This metabolite is to be changed by reactions CMetab g6p = model.createMetabolite("glucose-6-phosphate", compartment.getObjectName(), 0.0, CModelEntity.Status_REACTIONS); Debug.Assert(g6p != null); obj = g6p.getInitialValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); Debug.Assert(model.getMetabolites().size() == 2); // another metabolite for ATP, also fixed CMetab atp = model.createMetabolite("ATP", compartment.getObjectName(), 10.0, CModelEntity.Status_FIXED); Debug.Assert(atp != null); obj = atp.getInitialValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); Debug.Assert(model.getMetabolites().size() == 3); // and one for ADP CMetab adp = model.createMetabolite("ADP", compartment.getObjectName(), 0.0, CModelEntity.Status_REACTIONS); Debug.Assert(adp != null); obj = adp.getInitialValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); Debug.Assert(model.getMetabolites().size() == 4); // now we create a reaction CReaction reaction = model.createReaction("hexokinase"); Debug.Assert(reaction != null); Debug.Assert(model.getReactions().size() == 1); // hexokinase converts glucose and ATP to glucose-6-phosphate and ADP // we can set these on the chemical equation of the reaction CChemEq chemEq = reaction.getChemEq(); // glucose is a substrate with stoichiometry 1 chemEq.addMetabolite(glucose.getKey(), 1.0, CChemEq.SUBSTRATE); // ATP is a substrate with stoichiometry 1 chemEq.addMetabolite(atp.getKey(), 1.0, CChemEq.SUBSTRATE); // glucose-6-phosphate is a product with stoichiometry 1 chemEq.addMetabolite(g6p.getKey(), 1.0, CChemEq.PRODUCT); // ADP is a product with stoichiometry 1 chemEq.addMetabolite(adp.getKey(), 1.0, CChemEq.PRODUCT); Debug.Assert(chemEq.getSubstrates().size() == 2); Debug.Assert(chemEq.getProducts().size() == 2); // this reaction is to be irreversible reaction.setReversible(false); Debug.Assert(reaction.isReversible() == false); // now we ned to set a kinetic law on the reaction // maybe constant flux would be OK // we need to get the function from the function database CFunctionDB funDB = CRootContainer.getFunctionList(); Debug.Assert(funDB != null); // it should be in the list of suitable functions // lets get all suitable functions for an irreversible reaction with 2 substrates // and 2 products CFunctionStdVector suitableFunctions = funDB.suitableFunctions(2, 2, COPASI.TriFalse); Debug.Assert((suitableFunctions.Count > 0)); int i, iMax = (int)suitableFunctions.Count; for (i = 0; i < iMax; ++i) { // we just assume that the only suitable function with Constant in // it's name is the one we want if (suitableFunctions[i].getObjectName().IndexOf("Constant") != -1) { break; } } if (i != iMax) { // we set the function // the method should be smart enough to associate the reaction entities // with the correct function parameters reaction.setFunction(suitableFunctions[i]); Debug.Assert(reaction.getFunction() != null); // constant flux has only one function parameter Debug.Assert(reaction.getFunctionParameters().size() == 1); // so there should be only one entry in the parameter mapping as well Debug.Assert(reaction.getParameterCNs().Count == 1); CCopasiParameterGroup parameterGroup = reaction.getParameters(); Debug.Assert(parameterGroup.size() == 1); CCopasiParameter parameter = parameterGroup.getParameter(0); // make sure the parameter is a local parameter Debug.Assert(reaction.isLocalParameter(parameter.getObjectName())); // now we set the value of the parameter to 0.5 Debug.Assert(parameter.getType() == CCopasiParameter.Type_DOUBLE); parameter.setDblValue(0.5); obj = parameter.getValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); } else { System.Console.Error.WriteLine("Error. Could not find a kinetic law that conatins the term \"Constant\"."); System.Environment.Exit(1); } // now we also create a separate reaction for the backwards reaction and // set the kinetic law to irreversible mass action // now we create a reaction reaction = model.createReaction("hexokinase-backwards"); Debug.Assert(reaction != null); Debug.Assert(model.getReactions().size() == 2); chemEq = reaction.getChemEq(); // glucose is a product with stoichiometry 1 chemEq.addMetabolite(glucose.getKey(), 1.0, CChemEq.PRODUCT); // ATP is a product with stoichiometry 1 chemEq.addMetabolite(atp.getKey(), 1.0, CChemEq.PRODUCT); // glucose-6-phosphate is a substrate with stoichiometry 1 chemEq.addMetabolite(g6p.getKey(), 1.0, CChemEq.SUBSTRATE); // ADP is a substrate with stoichiometry 1 chemEq.addMetabolite(adp.getKey(), 1.0, CChemEq.SUBSTRATE); Debug.Assert(chemEq.getSubstrates().size() == 2); Debug.Assert(chemEq.getProducts().size() == 2); // this reaction is to be irreversible reaction.setReversible(false); Debug.Assert(reaction.isReversible() == false); // now we ned to set a kinetic law on the reaction CFunction massAction = (CFunction)funDB.findFunction("Mass action (irreversible)"); Debug.Assert(massAction != null); // we set the function // the method should be smart enough to associate the reaction entities // with the correct function parameters reaction.setFunction(massAction); Debug.Assert(reaction.getFunction() != null); Debug.Assert(reaction.getFunctionParameters().size() == 2); // so there should be two entries in the parameter mapping as well Debug.Assert(reaction.getParameterCNs().Count == 2); // mass action is a special case since the parameter mappings for the // substrates (and products) are in a vector // Let us create a global parameter that is determined by an assignment // and that is used as the rate constant of the mass action kinetics // it gets the name rateConstant and an initial value of 1.56 CModelValue modelValue = model.createModelValue("rateConstant", 1.56); Debug.Assert(modelValue != null); obj = modelValue.getInitialValueReference(); Debug.Assert(obj != null); changedObjects.Add(obj); Debug.Assert(model.getModelValues().size() == 1); // set the status to assignment modelValue.setStatus(CModelEntity.Status_ASSIGNMENT); // the assignment does not have to make sense modelValue.setExpression("1.0 / 4.0 + 2.0"); // now we have to adjust the parameter mapping in the reaction so // that the kinetic law uses the global parameter we just created instead // of the local one that is created by default // The first parameter is the one for the rate constant, so we point it to // the key of out model value reaction.setParameterObject(0, modelValue); // now we have to set the parameter mapping for the substrates reaction.addParameterObject("substrate", g6p); reaction.addParameterObject("substrate", adp); // finally compile the model // compile needs to be done before updating all initial values for // the model with the refresh sequence model.compileIfNecessary(); // now that we are done building the model, we have to make sure all // initial values are updated according to their dependencies model.updateInitialValues(changedObjects); // save the model to a COPASI file // we save to a file named example1.cps // and we want to overwrite any existing file with the same name // Default tasks are automatically generated and will always appear in cps // file unless they are explicitley deleted before saving. dataModel.saveModel("example1.cps", true); // export the model to an SBML file // we save to a file named example1.xml, we want to overwrite any // existing file with the same name and we want SBML L2V3 try { dataModel.exportSBML("example1.xml", true, 2, 3); } catch { System.Console.Error.WriteLine("Error. Exporting the model to SBML failed."); } }
/// <summary> /// Updates a reaction. /// </summary> /// <param name="reaction">COPASI Reaction.</param> /// <param name="reagents">Reagents.</param> /// <param name="products">Products.</param> /// <param name="rate">Rate.</param> public void UpdateReaction(CReaction reaction, MoleculeSpecies[] reagents, MoleculeSpecies[] products, double rate) { // we can set these on the chemical equation of the reaction CChemEq chemEq = reaction.getChemEq(); // remove all existing metabolites chemEq.getSubstrates().clear(); chemEq.getProducts().clear(); // add substrates CMetab[] substrates = GetMetabs(reagents); foreach (CMetab item in substrates) { // add substrate with stoichiometry 1 chemEq.addMetabolite(item.getKey(), 1.0, CChemEq.SUBSTRATE); } // add products CMetab[] metabProducts = GetMetabs(products); foreach (CMetab item in metabProducts) { // add product with stoichiometry 1 chemEq.addMetabolite(item.getKey(), 1.0, CChemEq.PRODUCT); } // this reaction is to be irreversible reaction.setReversible(false); // now we ned to set a kinetic law on the reaction // maybe constant flux would be OK // we need to get the function from the function database CFunctionDB funDB = CCopasiRootContainer.getFunctionList(); // it should be in the list of suitable functions // lets get all suitable functions for an irreversible reaction with x substrates // and y products CFunctionStdVector suitableFunctions = funDB.suitableFunctions((uint)substrates.Length, (uint)products.Length, COPASI.TriFalse); CFunction function = null; for (int i = 0; i < suitableFunctions.Count; i++) { // we just assume that the only suitable function with mass action in // it's name is the one we want if (suitableFunctions[i].getObjectName().ToLower().Contains("mass action")) { function = suitableFunctions[i]; break; } } if (function != null) { reaction.setFunction(function); CCopasiParameterGroup parameterGroup = reaction.getParameters(); CCopasiParameter parameter = parameterGroup.getParameter(0); // make sure the parameter is a local parameter System.Diagnostics.Debug.Assert(reaction.isLocalParameter(parameter.getObjectName())); // now we set the value of the parameter to 0.5 System.Diagnostics.Debug.Assert(parameter.getType() == CCopasiParameter.DOUBLE); parameter.setDblValue(rate); CCopasiObject obj = parameter.getValueReference(); changedObjects.Add(obj); //reaction.getParameterMappings().Clear(); foreach (var substrate in substrates) { reaction.addParameterMapping("substrate", substrate.getKey()); } } else { throw new System.Exception("Error. Could not find a kinetic law that conatins the term \"mass action\"."); } }