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)