def getInitialFields(self, mesh):
        if self.waveformType == "STEPOFF":
            print ">> Step waveform: Non-zero initial condition"
            if mesh._meshType is 'CYL':
                if mesh.isSymmetric:
                    MVP = MagneticLoopVectorPotential(self.loc, mesh, 'Ey', self.radius)
                else:
                    raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
            elif mesh._meshType is 'TENSOR':
                MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
            else:
                raise Exception('Unknown mesh for CircularLoop')
            return {"b": mesh.edgeCurl*MVP}
        elif self.waveformType == "GENERAL":
            print ">> General waveform: Zero initial condition"
            return {"b": np.zeros(mesh.nF)}
        else:
            raise NotImplementedError("Only use STEPOFF or GENERAL")
Function makes a prediction of one sample with a tree model. If y label is defined it returns node identifier and margin.
dataset/ETHPy150Open simpeg/simpeg/SimPEG/EM/TDEM/SurveyTDEM.py/SrcTDEM_CircularLoop_MVP.getInitialFields--crossover with--dataset/ETHPy150Open romanorac/discomll/discomll/ensemble/core/decision_tree.py/predict