docs: add tutorial for elemental nodal results on mixed-element meshes - #3296
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…ement meshes Adds a new sphinx-gallery tutorial under post_processing_basics that shows how to: - Discover element types in bulk via Elements.element_types_field (PropertyField) and dpf.element_types.descriptor() (n_nodes, is_solid, is_shell, is_beam, is_quadratic). - Read an ElementalNodal stress field on a mixed-element mesh and use Field.get_entity_data_by_id() to expose the variable per-element row count. - Use the split_shells argument on result operators to obtain a per-shape FieldsContainer with an elshape label and run vectorised numpy operations on one uniform sub-field. - Use extend_to_mid_nodes to fill mid-side node values on a corner-only ElementalNodal field for quadratic elements. Dataset: examples.download_all_kinds_of_complexity().
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June 30, 2026 14:47
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
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split_shells groups by stress category (Solid/Shell-with-N-layers), not geometric type, and mixes Tet10+Hex20 inside elshape=2 so per-shape sub-fields are not uniform. The correct mechanism for uniform per-shape ElementalNodal fields is to build a Scoping from element_types_field via a numpy mask and pass it as mesh_scoping. Also fixes the false 'rows = n_nodes' claim (rows = n_corner_nodes for solids, nodes*layers for shells) and replaces the no-op nodal_to_elemental_nodal->extend_to_mid_nodes demo by feeding the per-shape Tet10 field straight into extend_to_mid_nodes_fc, which now visibly grows (4,6) -> (10,6).
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The documentation for this pull request will be available at https://dpf.docs.pyansys.com/pull/3296. Please allow some time for the documentation to be deployed. |
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Summary
New PyDPF-Core sphinx-gallery tutorial under
post_processing_basics/titledProcess elemental nodal results on mixed-element meshes.
The tutorial demonstrates the recommended workflow for handling
ElementalNodalresults on a mesh that mixes several element types (different node counts per
element):
Elements.element_types_field(aPropertyField) and map each type to itsElementDescriptor(n_nodes,is_solid,is_shell,is_beam,is_quadratic).ElementalNodalstress field; show thatField.get_entity_data_by_id()returns a variable-shape array whose row countequals the element's
n_nodes.split_shellsargument on result operators to obtain a per-shapeFieldsContainer(carrying theelshapelabel). Within each per-shapesub-field the node count is uniform, so the flat
dataarray can be reshapedto
(n_elements, n_nodes, n_components)and processed with numpy.extend_to_mid_nodesto fill the mid-side node values of a corner-onlyElementalNodalfield on quadratic elements.Dataset:
examples.download_all_kinds_of_complexity().Files
doc/sphinx_gallery_tutorials/post_processing_basics/mixed_element_results.py-- new tutorial (
_order: 2, labelref_tutorials_mixed_element_results).doc/sphinx_gallery_tutorials/post_processing_basics/GALLERY_HEADER.rst-- new grid card.
Validation
python -m py_compileon the tutorial file passes.src/ansys/dpf/core/.(
deploy-pr-doclabel).