How do I generate an RBF mapping with PyDPF?

Ayush Kumar

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Ayush Kumar

The RBF (Radial Basis Function) Filter is used to smooth or interpolate data across a mesh. It calculates the value at any given point by weighing the values of surrounding nodes based on their distance.

The Radius is the "smoothing scale" of the filter.

Function: It determines how quickly the influence of a neighboring node drops off. It acts as the standard deviation in the Gaussian weighting function.
Impact on Results - Small Radius: Captures local gradients and peak values (e.g., sharp stress concentrations).
- Large Radius: Blurs the data, averaging peaks with surrounding lower values to show general trends.

The Influence Box is a computational optimization (bounding box).

Function: It defines the spatial "search window" around a target point.

from ansys.dpf import core as dpf

from ansys.dpf.core.plotter import DpfPlotter


dpf.start_local_server(ansys_path=r"C:\Program Files\ANSYS Inc\v252")


rbf_ri = [1.0, 3.0, 5.0, 8.0]

inf_box = 25.0


s_rst = r"D:\…\file.rst"

s_model = dpf.Model(s_rst)

s_mesh = s_model.metadata.meshed_region


s = s_model.results.stress()

s.inputs.requested_location.connect("Nodal")

vm_s = dpf.operators.invariant.von_mises_eqv_fc(fields_container=s).eval()


t_rst = r"D:\…\file.rst"

t_model = dpf.Model(t_rst)


t_mesh = t_model.metadata.meshed_region


for rbf_r in rbf_ri:

    # RBF Mapping

    rbf_map = dpf.operators.mapping.prepare_mapping_workflow(

        input_support=s_mesh, output_support=t_mesh, filter_radius=float(rbf_r), influence_box=inf_box)

    rbf_map_wf = rbf_map.outputs.mapping_workflow()

    rbf_map_wf.connect("source", vm_s[0])

    rbf_map_wf_fc = rbf_map_wf.get_output("target", dpf.Field)

    print(rbf_map_wf_fc)


    pl = DpfPlotter()

    pl.add_field(rbf_map_wf_fc, t_mesh)

    # Plot the result.

    pl.show_figure(show_axes=True)