def test_runDeterministicSimulationOnExtendedModel(self):
  Test_CreateSimpleModel.extendModel(self.datamodel)
  task=runDeterministicSimulation(self.datamodel)
  self.assert_(task!=None)
  self.assert_(task.__class__==COPASI.CTrajectoryTask)
  timeseries=task.getTimeSeries()
  self.assert_(timeseries!=None)
  self.assert_(timeseries.__class__==COPASI.CTimeSeries)
  self.assert_(timeseries.getRecordedSteps()==10001)
  self.assert_(timeseries.getNumVariables()==5)
  value=timeseries.getConcentrationData(3574,0)
  self.assert_(math.fabs((value-3.574)/3.574)<0.001)
  value=timeseries.getConcentrationData(3574,1)
  value2=timeseries.getConcentrationData(3574,3)
  self.assert_(math.fabs((value-value2)/value)<0.001)
 def test_runHybridSimulationOnExtendedModel(self):
  Test_CreateSimpleModel.extendModel(self.datamodel)
  values=[]
  for x in range(0,self.NUM_REPEATS):
    task=runHybridSimulation(self.datamodel)
    self.assert_(task!=None)
    self.assert_(task.__class__==COPASI.CTrajectoryTask)
    timeseries=task.getTimeSeries()
    self.assert_(timeseries!=None)
    self.assert_(timeseries.__class__==COPASI.CTimeSeries)
    self.assert_(timeseries.getRecordedSteps()==10001)
    self.assert_(timeseries.getNumVariables()==5)
    values.append([timeseries.getConcentrationData(3574,0),timeseries.getConcentrationData(3574,1),timeseries.getConcentrationData(3574,3)])
  average=[0.0,0.0,0.0]
  for x in range(0,len(values)):
    average[0]+=values[x][0]
    average[1]+=values[x][1]
    average[2]+=values[x][2]
  average[0]=average[0]/len(values)
  average[1]=average[1]/len(values)
  average[2]=average[2]/len(values)
  self.assert_(math.fabs((average[0]-3.574)/3.574)<0.001)
  self.assert_(math.fabs((average[1]-average[2])/average[1])<0.01)
 def test_runParameterFittingOnExtendedModel(self):
     Test_CreateSimpleModel.extendModel(self.model)
 def test_runParameterFittingOnExtendedModel(self):
      Test_CreateSimpleModel.extendModel(self.model)