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);
// 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()
{
// 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);
}