Python plugin paraview

@smproxy.filter()
@smproperty.input(name="InputTable")
@smdomain.datatype(dataTypes=["vtkTable"], port_index=1, composite_data_supported=False)

class AverageTable(VTKPythonAlgorithmBase):
    """
    Example filter demonstrating how to write a filter that preserves the input
    dataset type.
    """
    @smproperty.intvector(name="ReductionFactor", default_values=16)
    def SetReductionFactor(self, x):
        if x <= 0:
            print("Error : the reduction factor has to be a greater or equal to 1")
            raise Exception("the reduction factor has to be a greater or equal to 1")
        self._realAlgorithm.SetReductionFactor(x)
        self.Modified()



    def __init__(self):
        super().__init__(nInputPorts=1, nOutputPorts=1, outputType="vtkTable")

    def RequestDataObject(self, request, inInfo, outInfo):
        inData = self.GetInputData(inInfo, 0, 0)
        outData = self.GetOutputData(outInfo, 0)
        assert inData is not None
        if outData is None or (not outData.IsA(inData.GetClassName())):
            outData = inData.NewInstance()
            outInfo.GetInformationObject(0).Set(outData.DATA_OBJECT(), outData)
        return super().RequestDataObject(request, inInfo, outInfo)

    def RequestData(self, request, inInfo, outInfo):
        import numpy as np
        inData = self.GetInputData(inInfo, 0, 0)
        outData = self.GetOutputData(outInfo, 0)
        for name in inData.dtype.names:
            a = np.array(inData[name])
            m = 1000
            b=a[:len(a)//m*m].reshape(-1, m).mean(1)
            # You can directly pass a NumPy array to the pipeline.
            # Since ParaView expects all arrays to be named, you
            # need to assign it a name in the 'append' call.
            outData.RowData.append(b, name)
        # print("input type =", inData.GetClassName())
        # print("output type =", outData.GetClassName())
        # assert outData.IsA(inData.GetClassName())
        return outData