Contours an input dataset by an array. ``isosurfaces`` can be an integer
        specifying the number of isosurfaces in the data range or an iterable set of
        values for explicitly setting the isosurfaces.

        Parameters
        ----------
        isosurfaces : int or iterable
            Number of isosurfaces to compute across valid data range or an
            iterable of float values to explicitly use as the isosurfaces.

        scalars : str, optional
            Name of scalars to threshold on. Defaults to currently active scalars.

        compute_normals : bool, optional

        compute_gradients : bool, optional
            Desc

        compute_scalars : bool, optional
            Preserves the scalar values that are being contoured

        rng : tuple(float), optional
            If an integer number of isosurfaces is specified, this is the range
            over which to generate contours. Default is the scalar arrays's full
            data range.

        preference : str, optional
            When scalars is specified, this is the perfered scalar type to
            search for in the dataset.  Must be either ``'point'`` or ``'cell'``

def contour(dataset, isosurfaces=10, scalars=None, compute_normals=False,
                compute_gradients=False, compute_scalars=True,  rng=None,
                preference='point'):
        """Contours an input dataset by an array. ``isosurfaces`` can be an integer
        specifying the number of isosurfaces in the data range or an iterable set of
        values for explicitly setting the isosurfaces.

        Parameters
        ----------
        isosurfaces : int or iterable
            Number of isosurfaces to compute across valid data range or an
            iterable of float values to explicitly use as the isosurfaces.

        scalars : str, optional
            Name of scalars to threshold on. Defaults to currently active scalars.

        compute_normals : bool, optional

        compute_gradients : bool, optional
            Desc

        compute_scalars : bool, optional
            Preserves the scalar values that are being contoured

        rng : tuple(float), optional
            If an integer number of isosurfaces is specified, this is the range
            over which to generate contours. Default is the scalar arrays's full
            data range.

        preference : str, optional
            When scalars is specified, this is the perfered scalar type to
            search for in the dataset.  Must be either ``'point'`` or ``'cell'``

        """
        # Make sure the input has scalars to contour on
        if dataset.n_scalars < 1:
            raise AssertionError('Input dataset for the contour filter must have scalar data.')
        alg = vtk.vtkContourFilter()
        alg.SetInputDataObject(dataset)
        alg.SetComputeNormals(compute_normals)
        alg.SetComputeGradients(compute_gradients)
        alg.SetComputeScalars(compute_scalars)
        # set the array to contour on
        if scalars is None:
            field, scalars = dataset.active_scalar_info
        else:
            _, field = get_scalar(dataset, scalars, preference=preference, info=True)
        # NOTE: only point data is allowed? well cells works but seems buggy?
        if field != vtki.POINT_DATA_FIELD:
            raise AssertionError('Contour filter only works on Point data. Array ({}) is in the Cell data.'.format(scalars))
        alg.SetInputArrayToProcess(0, 0, 0, field, scalars) # args: (idx, port, connection, field, name)
        # set the isosurfaces
        if isinstance(isosurfaces, int):
            # generate values
            if rng is None:
                rng = dataset.get_data_range(scalars)
            alg.GenerateValues(isosurfaces, rng)
        elif isinstance(isosurfaces, collections.Iterable):
            alg.SetNumberOfContours(len(isosurfaces))
            for i, val in enumerate(isosurfaces):
                alg.SetValue(i, val)
        else:
            raise RuntimeError('isosurfaces not understood.')
        alg.Update()
        return _get_output(alg)