How to use the amici.parameterScalingFromIntVector function in amici

self.model.setParameterList([
            i for i in reversed(self.model.getParameterList())
        ])

        # set ExpData parameters
        self.edata.parameters = self.model.getParameters()
        # perturb model parameters
        self.model.setParameters(tuple(
            p * 2 for p in self.model.getParameters()
        ))

        # set ExpData pscale
        self.edata.pscale = self.model.getParameterScale()
        # perturb model pscale, needs to be done after getting parameters,
        # otherwise we will mess up parameter value
        self.model.setParameterScale(amici.parameterScalingFromIntVector([
            amici.ParameterScaling_log10
            if scaling == amici.ParameterScaling_none
            else amici.ParameterScaling_none
            for scaling in self.model.getParameterScale()
        ]))

        self.edata.x0 = rdata['x_ss']
        self.edata.sx0 = rdata['sx_ss'].flatten()

        # perturb model initial states
        self.model.setInitialStates(rdata['x_ss'] * 4)
        self.model.setInitialStateSensitivities(rdata['sx_ss'].flatten() / 2)

        rdata_edata = amici.runAmiciSimulation(
            self.model, self.solver, self.edata
        )

def test_parameterScalingFromIntVector(self):
        """Ensure we can generate a ParameterScaling vector from Python"""
        scale_vector = amici.parameterScalingFromIntVector(
            [
                amici.ParameterScaling_log10,
                amici.ParameterScaling_ln,
                amici.ParameterScaling_none
            ])
        assert scale_vector[0] == amici.ParameterScaling_log10
        assert scale_vector[1] == amici.ParameterScaling_ln
        assert scale_vector[2] == amici.ParameterScaling_none

self.edata.fixedParametersPresimulation
        self.edata_presim.fixedParametersPresimulation = ()
        self.edata_presim.fixedParametersPreequilibration = ()

        self.edata_sim = amici.ExpData(self.edata)
        self.edata_sim.t_presim = 0
        self.edata_sim.setTimepoints(self.edata.getTimepoints())
        self.edata_sim.fixedParameters = \
            self.edata.fixedParameters
        self.edata_sim.fixedParametersPresimulation = ()
        self.edata_sim.fixedParametersPreequilibration = ()

        self.pscales = [
            amici.ParameterScaling_log10, amici.ParameterScaling_ln,
            amici.ParameterScaling_none,
            amici.parameterScalingFromIntVector([
                amici.ParameterScaling_log10, amici.ParameterScaling_ln,
                amici.ParameterScaling_none, amici.ParameterScaling_log10,
                amici.ParameterScaling_ln, amici.ParameterScaling_none
            ])
        ]

        self.plists = [
            [3, 1, 2, 4], [0, 1, 2, 3, 4, 5], [5, 3, 2, 0, 4, 1],
            [1, 2, 3, 4, 5], [1, 1, 1],
        ]