Allow export of ElementalNodal fields to VTK formats

[aukselis-c1connections]

Before submitting the issue

• I have checked for Compatibility issues
• I have searched among the existing issues
• I am using a Python virtual environment

Description of the bug

With the latest update of DPF-core, the ElementalNodal data can finally be plotted. However, when attempting to save this data to a VTK file, a file with a mesh but no results is produced.

Is any workaround available before this gets fully implemented?

input rst and output vtk are attached below as txt files (need to be renamed)
file.rst.txt

test.vtk.txt

Steps To Reproduce

import ansys.dpf.core as dpf

model = dpf.Model(R".\file.rst")
op = dpf.operators.result.stress_von_mises(data_sources=model, requested_location="ElementalNodal")
field = op.outputs.fields_container()[0]
field.plot()
exporter = dpf.operators.serialization.vtk_export(fields1=field, file_path="./test.vtk")
exporter.run()

Which Operating System causes the issue?

Windows

Which DPF/Ansys version are you using?

Ansys 2025 R2

Which Python version causes the issue?

3.13, 3.12

Installed packages

aiohappyeyeballs==2.6.1
aiohttp==3.12.15
aiosignal==1.4.0
ansys-api-mapdl==0.5.2
ansys-api-platform-instancemanagement==1.1.3
ansys-dpf-core==0.14.1
ansys-mapdl-core==0.71.0
ansys-mapdl-reader==0.55.1
ansys-math-core==0.2.4
ansys-platform-instancemanagement==1.1.2
ansys-tools-path==0.7.3
ansys-tools-visualization-interface==0.11.0
appdirs==1.4.4
asttokens==3.0.0
attrs==25.3.0
babel==2.17.0
certifi==2025.8.3
charset-normalizer==3.4.3
click==8.2.1
colorama==0.4.6
comm==0.2.3
contourpy==1.3.3
cycler==0.12.1
debugpy==1.8.16
decorator==5.2.1
docxcompose==1.4.0
docxtpl==0.20.1
et-xmlfile==2.0.0
executing==2.2.1
fonttools==4.59.2
frozenlist==1.7.0
geomdl==5.4.0
grpcio==1.75.0
h5py==3.14.0
idna==3.10
importlib-metadata==8.7.0
ipykernel==6.30.1
ipython==9.5.0
ipython-pygments-lexers==1.1.1
jedi==0.19.2
jinja2==3.1.6
jupyter-client==8.6.3
jupyter-core==5.8.1
kiwisolver==1.4.9
lxml==6.0.1
markupsafe==3.0.2
matplotlib==3.10.6
matplotlib-inline==0.1.7
more-itertools==10.7.0
msgpack==1.1.1
multidict==6.6.4
nest-asyncio==1.6.0
numpy==2.3.3
openpyxl==3.1.5
packaging==25.0
pandas==2.3.2
parso==0.8.5
pillow==11.3.0
platformdirs==4.4.0
pooch==1.8.2
prompt-toolkit==3.0.52
propcache==0.3.2
protobuf==4.25.8
psutil==7.0.0
pure-eval==0.2.3
pyansys-tools-versioning==0.6.0
pygments==2.19.2
pyiges==0.3.2
pyparsing==3.2.4
python-dateutil==2.9.0.post0
python-docx==1.2.0
pytz==2025.2
pyvista==0.45.3
pywin32==311
pyyaml==6.0.2
pyzmq==27.1.0
requests==2.32.5
scipy==1.16.2
scooby==0.10.1
setuptools==80.9.0
six==1.17.0
stack-data==0.6.3
tabulate==0.9.0
tornado==6.5.2
tqdm==4.67.1
traitlets==5.14.3
trame==3.12.0
trame-client==3.10.1
trame-common==1.0.1
trame-server==3.6.0
trame-vtk==2.9.1
trame-vuetify==3.0.2
typing-extensions==4.15.0
tzdata==2025.2
urllib3==2.5.0
vtk==9.4.2
wcwidth==0.2.13
websockets==15.0.1
wslink==2.4.0
yarl==1.20.1
zipp==3.23.0

[PProfizi]

Hi @aukselis-c1connections sadly this is a current limitation of serialization.vtk_export and of serialization.vtu_export.

To allow plotting the ElementalNodal fields we use a visualization trick where we split the mesh at each element to duplicate all the nodes and store one data point per node per element.
Right now we do not do this when saving Elemental or Nodal fields to VTK, as we keep the original mesh connectivity.

You could create a VTK file with the mesh split per element, and store ElementalNodal data, but you would loose the original connectivity.

I do not currently see a way to store ElementalNodal data on the VTK mesh with the connectivity kept intact.

Let me know how this fits with your needs and we will decide how to proceed.
Changing this to a feature request for now.

[aukselis-c1connections]

Hi @PProfizi,

Thanks for looking into this. In the end, we made our own logic to plot with PyVista then it can be saved to VTK or VTU format directly. (Original connectivity is lost as you have mentioned; however, this is sufficient for us.)

Would it be possible for you to add an argument to the plot function so that, instead of plotting to the screen, it would be able to save the plot to a file (or to return a PyVista plotter without plotting to the screen)? This would help us not to maintain an equivalent plot function in parallel to yours that does 99.9% the same. (Note: change the data series label from 'Data' to the actual name of the result)

Currently, you return the PyVista plot object; however, after plotting to the screen, PyVista clears everything from it, therefore, it cannot be used to save the data to a file.

[PProfizi]

Hi @aukselis-c1connections, the plotter offers the off_screen kwarg argument from the PyVista plotter. Would that be sufficient?
We also expose the screenshot kwarg argument from the PyVista Plotter.show_figure method.

You can give both arguments screenshot="file.png" and off_screen=True as kwargs to any of the plot methods of PyDPF classes such as Field.plot.

You can also start a DpfPlotter with off_screen=True and then use DpfPlotter.show_figure(screenshot="file.png").

I would have to check if using off_screen=True prevents pyvista from clearing the data.
You could also use the DpfPlotter directly to create a scene by adding data to it, and then save the scene with DpfPlotter._internal_plotter.save_graphic to a file without ever using DpfPlotter.show_figure.

[aukselis-c1connections]

@PProfizi, What I meant by 'to file' is saving vtu or vtk files. Perhaps something like DpfPlotter._internal_plotter.mesh.save('file.vtu') would work with the off_screen=True argument?

[PProfizi]

Hi @aukselis-c1connections you apparently do not need the off_screen=True argument, and you can also save after a call to DpfPlotter.show_figure() as shown in this example:

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


model = dpf.Model(find_simple_bar())
print(model)
fc = model.results.element_nodal_forces().eval()
print(fc)

plt = DpfPlotter()
plt.add_field(field=fc[0])
grid = plt._internal_plotter._plotter.mesh
plt.show_figure()
grid.save("bar.vtu")

Let me know if this is what you were looking for.
If so, I will look into exposing plt._internal_plotter._plotter.mesh and/or its save method for easy access directly from the DpfPlotter.