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(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(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.");
}
}
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);
}
}
static void Main()
{
Debug.Assert((CRootContainer.getRoot() != null));
// create a new datamodel
CDataModel dataModel = CRootContainer.addDatamodel();
Debug.Assert((dataModel != null));
Debug.Assert((CRootContainer.getDatamodelList().size() == 1));
// next we import a simple SBML model from a string
// clear the message queue so that we only have error messages from the import in the queue
CCopasiMessage.clearDeque();
bool result = true;
try
{
result = dataModel.importSBMLFromString(MODEL_STRING);
}
catch
{
System.Console.Error.WriteLine("Import of model failed miserably.");
System.Environment.Exit(1);
}
// check if the import was successful
int mostSevere = CCopasiMessage.getHighestSeverity();
// if it was a filtered error, we convert it to an unfiltered type
// the filtered error messages have the same value as the unfiltered, but they
// have the 7th bit set which basically adds 128 to the value
mostSevere = mostSevere & 127;
// we assume that the import succeeded if the return value is true and
// the most severe error message is not an error or an exception
if (result != true && mostSevere < CCopasiMessage.ERROR)
{
System.Console.Error.WriteLine("Sorry. Model could not be imported.");
System.Environment.Exit(1);
}
//
// now we tell the model object to calculate the jacobian
//
CModel model = dataModel.getModel();
Debug.Assert((model != null));
if (model != null)
{
// running a task, e.g. a trajectory will automatically make sure that
// the initial values are transferred to the current state before the calculation begins.
// If we use low level calculation methods like the one to calculate the jacobian, we
// have to make sure the the initial values are applied to the state
model.applyInitialValues();
// we need an array that stores the result
// the size of the matrix does not really matter because
// the calculateJacobian autoamtically resizes it to the correct
// size
FloatMatrix jacobian = new FloatMatrix();
// the first parameter to the calculation function is a reference to
// the matrix where the result is to be stored
// the second parameter is the derivationFactor for the calculation
// it basically represents a relative delta value for the calculation of the derivatives
// the third parameter is a boolean indicating whether the jacobian should
// be calculated from the reduced (true) or full (false) system
model.getMathContainer().calculateJacobian(jacobian, 1e-12, false);
// now we print the result
// the jacobian stores the values in the order they are
// given in the user order in the state template so it is not really straight
// forward to find out which column/row corresponds to which species
CStateTemplate stateTemplate = model.getStateTemplate();
// and we need the user order
SizeTVector userOrder = stateTemplate.getUserOrder();
// from those two, we can construct an new vector that contains
// the names of the entities in the jacobian in the order in which they appear in
// the jacobian
System.Collections.Generic.List <string> nameVector = new System.Collections.Generic.List <string>();
CModelEntity entity = null;
int status;
for (uint i = 0; i < userOrder.size(); ++i)
{
entity = stateTemplate.getEntity(userOrder.get(i));
Debug.Assert((entity != null));
// now we need to check if the entity is actually
// determined by an ODE or a reaction
status = entity.getStatus();
if (status == CModelEntity.Status_ODE ||
(status == CModelEntity.Status_REACTIONS && entity.isUsed()))
{
nameVector.Add(entity.getObjectName());
}
}
Debug.Assert((nameVector.Count == jacobian.numRows()));
// now we print the matrix, for this we assume that no
// entity name is longer then 5 character which is a save bet since
// we know the model
System.Console.Out.NewLine = "";
System.Console.WriteLine(System.String.Format("Jacobian Matrix:{0}", System.Environment.NewLine));
System.Console.WriteLine(System.String.Format("size:{0}x{1}{2}", jacobian.numRows(), jacobian.numCols(), System.Environment.NewLine));
System.Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
System.Console.Out.WriteLine(System.String.Format("{0,7}", " "));
for (int i = 0; i < nameVector.Count; ++i)
{
System.Console.Out.WriteLine(System.String.Format("{0,7}", nameVector[i]));
}
System.Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
for (uint i = 0; i < nameVector.Count; ++i)
{
System.Console.Out.WriteLine(System.String.Format("{0,7}", nameVector[(int)i]));
for (uint j = 0; j < nameVector.Count; ++j)
{
System.Console.Out.WriteLine(System.String.Format("{0,7:0.###}", jacobian.get(i, j)));
}
System.Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
}
// we can also calculate the jacobian of the reduced system
// in a similar way
model.getMathContainer().calculateJacobian(jacobian, 1e-12, true);
// this time generating the output is actually simpler because the rows
// and columns are ordered in the same way as the independent variables of the state temple
System.Console.WriteLine(System.String.Format("{0}{0}", System.Environment.NewLine));
System.Console.WriteLine(System.String.Format("Reduced Jacobian Matrix:{0}{0}", System.Environment.NewLine));
System.Console.Out.WriteLine(System.String.Format("{0:6}", " "));
uint iMax = stateTemplate.getNumIndependent();
for (uint i = 0; i < iMax; ++i)
{
System.Console.Out.WriteLine(System.String.Format("\t{0:7}", stateTemplate.getIndependent(i).getObjectName()));
}
System.Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
for (uint i = 0; i < iMax; ++i)
{
System.Console.Out.WriteLine(System.String.Format("{0:7}", stateTemplate.getIndependent(i).getObjectName()));
for (uint j = 0; j < iMax; ++j)
{
System.Console.Out.WriteLine(System.String.Format("{0,7:0.###}", jacobian.get(i, j)));
}
System.Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
}
}
}
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.getValueReference();
Debug.Assert(obj != null);
changedObjects.Add(obj);
Debug.Assert(compartment != null);
Debug.Assert(model.getCompartments().size() == 1);
// create a new metabolite with the name S and an inital
// concentration of 10 nanomol
// the metabolite belongs to the compartment we created and is is to be
// fixed
CMetab S = model.createMetabolite("S", compartment.getObjectName(), 10.0, CModelEntity.Status_FIXED);
obj = S.getInitialConcentrationReference();
Debug.Assert((obj != null));
changedObjects.Add(obj);
Debug.Assert((compartment != null));
Debug.Assert(S != null);
Debug.Assert(model.getMetabolites().size() == 1);
// create a second metabolite called P with an initial
// concentration of 0. This metabolite is to be changed by reactions
CMetab P = model.createMetabolite("P", compartment.getObjectName(), 0.0, CModelEntity.Status_REACTIONS);
Debug.Assert(P != null);
obj = P.getInitialConcentrationReference();
Debug.Assert(obj != null);
changedObjects.Add(obj);
Debug.Assert(model.getMetabolites().size() == 2);
// now we create a reaction
CReaction reaction = model.createReaction("reaction");
Debug.Assert(reaction != null);
Debug.Assert(model.getReactions().size() == 1);
// reaction converts S to P
// we can set these on the chemical equation of the reaction
CChemEq chemEq = reaction.getChemEq();
// S is a substrate with stoichiometry 1
chemEq.addMetabolite(S.getKey(), 1.0, CChemEq.SUBSTRATE);
// P is a product with stoichiometry 1
chemEq.addMetabolite(P.getKey(), 1.0, CChemEq.PRODUCT);
Debug.Assert(chemEq.getSubstrates().size() == 1);
Debug.Assert(chemEq.getProducts().size() == 1);
// this reaction is to be irreversible
reaction.setReversible(false);
Debug.Assert(reaction.isReversible() == false);
CModelValue MV = model.createModelValue("K", 42.0);
// set the status to FIXED
MV.setStatus(CModelEntity.Status_FIXED);
Debug.Assert(MV != null);
obj = MV.getInitialValueReference();
Debug.Assert(obj != null);
changedObjects.Add(obj);
Debug.Assert(model.getModelValues().size() == 1);
// now we ned to set a kinetic law on the reaction
// for this we create a user defined function
CFunctionDB funDB = CRootContainer.getFunctionList();
Debug.Assert(funDB != null);
CFunction function = (CFunction)funDB.createFunction("My Rate Law", CEvaluationTree.UserDefined);
CFunction rateLaw = (CFunction)funDB.findFunction("My Rate Law");
Debug.Assert(rateLaw != null);
// now we create the formula for the function and set it on the function
string formula = "(1-0.4/(EXPONENTIALE^(temp-37)))*0.00001448471257*1.4^(temp-37)*substrate";
var result = function.setInfix(formula);
Debug.Assert(result.isSuccess());
// make the function irreversible
function.setReversible(COPASI.TriFalse);
// the formula string should have been parsed now
// and COPASI should have determined that the formula string contained 2 parameters (temp and substrate)
CFunctionParameters variables = function.getVariables();
// per default the usage of those parameters will be set to VARIABLE
uint index = function.getVariableIndex("temp");
CFunctionParameter param = variables.getParameter(index);
Debug.Assert(param.getUsage() == CFunctionParameter.VARIABLE);
// This is correct for temp, but substrate should get the usage SUBSTRATE in order
// for us to use the function with the reaction created above
// So we need to set the usage for "substrate" manually
index = function.getVariableIndex("substrate");
param = variables.getParameter(index);
param.setUsage(CFunctionParameter.SUBSTRATE);
// set the rate law for the reaction
reaction.setFunction(function);
Debug.Assert(reaction.getFunction() != null);
// COPASI also needs to know what object it has to assocuiate with the individual function parameters
// In our case we need to tell COPASI that substrate is to be replaced by the substrate of the reaction
// and temp is to be replaced by the global parameter K
reaction.setParameterMapping("substrate", S.getKey());
reaction.setParameterMapping("temp", MV.getKey());
// 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("example7.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("example7.xml", true, 2, 3);
}
catch
{
System.Console.Error.WriteLine("Error. Exporting the model to SBML failed.");
}
}
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 a CPS file
if (args.Length == 1)
{
string filename = args[0];
try
{
// load the model without progress report
dataModel.loadModel(filename);
}
catch
{
System.Console.Error.WriteLine("Error while loading the model from file named \"" + filename + "\".");
System.Environment.Exit(1);
}
CModel model = dataModel.getModel();
Debug.Assert(model != null);
System.Console.WriteLine("Model statistics for model \"" + model.getObjectName() + "\".");
// output number and names of all compartments
uint i, iMax = (uint)model.getCompartments().size();
System.Console.WriteLine("Number of Compartments: " + System.Convert.ToString(iMax));
System.Console.WriteLine("Compartments: ");
for (i = 0; i < iMax; ++i)
{
CCompartment compartment = model.getCompartment(i);
Debug.Assert(compartment != null);
System.Console.WriteLine("\t" + compartment.getObjectName());
}
// output number and names of all metabolites
iMax = (uint)model.getMetabolites().size();
System.Console.WriteLine("Number of Metabolites: " + System.Convert.ToString(iMax));
System.Console.WriteLine("Metabolites: ");
for (i = 0; i < iMax; ++i)
{
CMetab metab = model.getMetabolite(i);
Debug.Assert(metab != null);
System.Console.WriteLine("\t" + metab.getObjectName());
}
// output number and names of all reactions
iMax = (uint)model.getReactions().size();
System.Console.WriteLine("Number of Reactions: " + System.Convert.ToString(iMax));
System.Console.WriteLine("Reactions: ");
for (i = 0; i < iMax; ++i)
{
CReaction reaction = model.getReaction(i);
Debug.Assert(reaction != null);
System.Console.WriteLine("\t" + reaction.getObjectName());
}
}
else
{
System.Console.Error.WriteLine("Usage: example2 CPSFILE");
System.Environment.Exit(1);
}
}
static void Main()
{
// initialize the backend library
// since we are not interested in the arguments
// that are passed to main, we pass 0 and NULL to
// init
Debug.Assert(CRootContainer.getRoot() != null);
// create a new datamodel
CDataModel dataModel = CRootContainer.addDatamodel();
Debug.Assert((dataModel != null));
Debug.Assert((CRootContainer.getDatamodelList().size() == 1));
// next we import a simple SBML model from a string
// clear the message queue so that we only have error messages from the import in the queue
CCopasiMessage.clearDeque();
bool result = true;
try
{
result = dataModel.importSBMLFromString(MODEL_STRING);
}
catch
{
System.Console.Error.WriteLine("An exception has occured during the import of the SBML model");
System.Environment.Exit(1);
}
// check if the import was successful
int mostSevere = CCopasiMessage.getHighestSeverity();
// if it was a filtered error, we convert it to an unfiltered type
// the filtered error messages have the same value as the unfiltered, but they
// have the 7th bit set which basically adds 128 to the value
mostSevere = mostSevere & 127;
// we assume that the import succeeded if the return value is true and
// the most severe error message is not an error or an exception
if (result != true && mostSevere < CCopasiMessage.ERROR)
{
System.Console.Error.WriteLine("Sorry. Model could not be imported.");
System.Environment.Exit(1);
}
// get the trajectory task object
CSteadyStateTask task = (CSteadyStateTask)dataModel.getTask("Steady-State");
CCopasiMessage.clearDeque();
try
{
// now we run the actual trajectory
task.processWithOutputFlags(true, (int)CCopasiTask.ONLY_TIME_SERIES);
}
catch
{
System.Console.Error.WriteLine("Error. Running the scan failed.");
String lastErrors = task.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 can get the result of the steady state calculation, e.g. the jacobian
// matrix of the model at the steady state
// here we can either get the jacobian as we did in example 8 as a matrix with
// getJacobian, or we can use getJacobianAnnotated to get an annotated matrix
// Corresponding methods for the reduced jacobian are getJacobianX and getJacobianXAnnotated
CDataArray aj = task.getJacobianAnnotated();
Debug.Assert((aj != null));
if (aj != null)
{
// we do the output, but as in contrast to the jacobian in example 8,
// we now have all the information for the output in one place
// first the array annotation can tell us how many dimensions it has.
// Since the matrix is a 2D array, it should have 2 dimensions
Debug.Assert((aj.dimensionality() == 2));
// since the matrix has a dimensionality of 2, the inde for the underlaying abstract array
// object is a vector with two unsigned int elements
// First element is the index for the outer dimension and the second element is the index
// for the inner dimension
SizeTStdVector index = new SizeTStdVector();
// The constructor does not seem to interpret an integer argument
// as the size
// I though that in C# we might be able to achieve this using the Capacity property
// but that didn't work. Maybe I was using it incorrectly since I don't really know C#
// So for now, we just add two elements to the vector which seems to do the trick.
index.Add(0);
index.Add(0);
// since the rows and columns have the same annotation for the jacobian, it doesn't matter
// for which dimension we get the annotations
StringStdVector annotations = aj.getAnnotationsString(1);
System.Console.Out.NewLine = "";
System.Console.WriteLine(System.String.Format("Jacobian Matrix:{0}{0}", System.Environment.NewLine));
System.Console.Out.WriteLine(System.String.Format("{0,7}", " "));
for (int i = 0; i < annotations.Count; ++i)
{
Console.Out.WriteLine(System.String.Format("{0,7}", annotations[i]));
}
Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
for (int i = 0; i < annotations.Count; ++i)
{
System.Console.Out.WriteLine(System.String.Format("{0,7} ", annotations[i]));
index[0] = (uint)i;
for (int j = 0; j < annotations.Count; ++j)
{
index[1] = (uint)j;
System.Console.Out.WriteLine(System.String.Format("{0,7:G2} ", aj.array().get(index)));
}
System.Console.WriteLine(System.String.Format("{0}", System.Environment.NewLine));
}
}
System.Environment.Exit(0);
}
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);
model.setVolumeUnit(CUnit.fl);
model.setTimeUnit(CUnit.s);
model.setQuantityUnit(CUnit.fMol);
CModelValue fixedModelValue = model.createModelValue("F");
Debug.Assert(fixedModelValue != null);
fixedModelValue.setStatus(CModelEntity.Status_FIXED);
fixedModelValue.setInitialValue(3.0);
CModelValue variableModelValue = model.createModelValue("V");
Debug.Assert(variableModelValue != null);
variableModelValue.setStatus(CModelEntity.Status_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.Method_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.Method_LevenbergMarquardt);
// next we need to set subtask type on the problem
COptProblem optProblem = (COptProblem)optTask.getProblem();
Debug.Assert(optProblem != null);
optProblem.setSubtaskType(CTaskEnum.Task_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 CCommonName("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 CCommonName(fixedModelValue.getObject(new CCommonName("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 CCommonName("-100"));
optItem.setUpperBound(new CCommonName("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.Task_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 CRegisteredCommonName(new CDataString("best value of objective function").getCN().getString()));
header.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString()));
header.Add(new CRegisteredCommonName(new CDataString("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 CRegisteredCommonName(optProblem.getObject(new CCommonName("Reference=Best Value")).getCN().getString()));
body.Add(new CRegisteredCommonName(report.getSeparator().getCN().getString()));
body.Add(new CRegisteredCommonName(fixedModelValue.getObject(new CCommonName("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);
}