.. _sphx_glr_tutorials_mapping: .. _ref_tutorials_mapping: ======= Mapping ======= Mapping is the process of transferring or interpolating field data from one spatial support to another. PyDPF-Core provides several mapping operators, each designed for specific use cases, from quick shape-function interpolation to RBF-based mesh-to-mesh transfer. .. grid:: 1 1 2 2 :gutter: 2 :padding: 2 :margin: 2 .. grid-item-card:: Interpolation at coordinates :link: ref_tutorials_mapping_on_coordinates :link-type: ref :text-align: center Uses ``on_coordinates`` to interpolate field values at arbitrary spatial coordinates using mesh shape functions. Ideal for extracting results along paths or at sensor locations. .. grid-item-card:: Reduced coordinates mapping :link: ref_tutorials_mapping_on_reduced_coordinates :link-type: ref :text-align: center Uses ``find_reduced_coordinates`` and ``on_reduced_coordinates`` for a two-step high-precision mapping process. Useful for Gauss point mapping and mesh-to-mesh transfer. .. grid-item-card:: Solid-to-skin mapping :link: ref_tutorials_mapping_solid_to_skin :link-type: ref :text-align: center Uses ``solid_to_skin`` to transfer field data from volume elements to surface elements. Supports elemental, nodal, and elemental-nodal locations. .. grid-item-card:: RBF-based workflow mapping :link: ref_tutorials_mapping_prepare_workflow :link-type: ref :text-align: center Uses ``prepare_mapping_workflow`` to generate reusable workflows based on Radial Basis Function (RBF) filters for mapping results between non-conforming meshes. .. raw:: html .. raw:: html