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((CCopasiRootContainer.getRoot() != null));
// create a new datamodel
CCopasiDataModel dataModel = CCopasiRootContainer.addDatamodel();
Debug.Assert((dataModel != null));
Debug.Assert((CCopasiRootContainer.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.ODE ||
(status == CModelEntity.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));
}
}
}
