==========
PyDPF-Post
==========

Ansys Data Processing Framework (DPF) provides numerical simulation 
users and engineers with a toolbox for accessing and transforming simulation 
data. With DPF, you can perform complex preprocessing or postprocessing of
large amounts of simulation data within a simulation workflow.

The Python `ansys-dpf-post` package provides a high-level, physics-oriented
API for postprocessing. Loading a simulation (defined by its results files)
allows you to extract simulation metadata and results and then apply
postprocessing operations on them.

The latest version of DPF supports Ansys solver results files for:

- Mechanical APDL (`.rst`, `.mode`, `.rfrq`, `.rdsp`)
- LS-DYNA (`.d3plot`, `.binout`)
- Fluent (`.cas/dat.h5`, `.flprj`)
- CFX (`.cad/dat.cff`, `.flprj`)

For more information on file support, see the `main page <https://dpf.docs.pyansys.com/version/stable/index.html>`_
in the PDF-Core documentation.

PyDPF-Post leverages the PyDPF-Core project's ``ansys-dpf-core`` package, which is
available at `PyDPF-Core GitHub <https://github.com/ansys/pydpf-core>`_.
Use the ``ansys-dpf-core`` package for building more advanced and customized
workflows using DPF.

Brief demo
~~~~~~~~~~

Provided you have Ansys 2023 R1 or later installed, a DPF server automatically starts
once you start using PyDPF-Post.

To load a simulation for a MAPDL result file to extract and
postprocess results, use this code:

.. code:: python

    >>> from ansys.dpf import post
    >>> from ansys.dpf.post import examples
    >>> simulation = post.load_simulation(examples.download_crankshaft())
    >>> displacement = simulation.displacement()
    >>> print(displacement)


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

             results         U
              set_id         3
      node      comp
      4872         X -3.41e-05
                   Y  1.54e-03
                   Z -2.64e-06
      9005         X -5.56e-05
                   Y  1.44e-03
                   Z  5.31e-06
       ...

.. code:: python

    >>> displacement.plot()


.. figure:: ./images/crankshaft_disp.png
    :width: 300pt

.. code:: python

    >>> stress_eqv = simulation.stress_eqv_von_mises_nodal()
    >>> stress_eqv.plot()

.. figure:: ./images/crankshaft_stress.png
    :width: 300pt

To run PyDPF-Post with Ansys 2021 R1 through 2022 R2, use this code to
start the legacy PyDPF-Post tools:

.. code:: python

    >>> from ansys.dpf import post
    >>> from ansys.dpf.post import examples
    >>> solution = post.load_solution(examples.download_crankshaft())
    >>> stress = solution.stress()
    >>> stress.eqv.plot_contour(show_edges=False)

.. figure:: ./images/crankshaft_stress.png
    :width: 300pt


For comprehensive examples of how you use PyDPF-Post, see :ref:`gallery`.


Key features
~~~~~~~~~~~~

**Computational efficiency**

PyDPF-Post is based on DPF, whose data framework localizes loading and
postprocessing on the DPF server, enabling rapid postprocessing workflows
because they are written in C and FORTRAN. Because PyDPF-Post presents results
in a Pythonic manner, you can rapidly develop simple or complex postprocessing
scripts.

**Easy to use**

The PyDPF-Post API automates the use of chained DPF operators to make
postprocessing easier. The PyDPF-Post documentation describes how you can
use operators to compute results. This allows you to build your own custom,
low-level scripts to enable fast postprocessing of potentially multi-gigabyte models
using `PyDPF-Core <https://github.com/ansys/pydpf-core>`_.

Documentation and issues
------------------------
Documentation for the latest stable release of PyDPF-Post is hosted at `PyDPF-Post documentation
<https://post.docs.pyansys.com/version/stable/>`_.

In the upper right corner of the documentation's title bar, there is an option for switching from
viewing the documentation for the latest stable release to viewing the documentation for the
development version or previously released versions.

You can also `view <https://cheatsheets.docs.pyansys.com/pydpf-post_cheat_sheet.png>`_ or
`download <https://cheatsheets.docs.pyansys.com/pydpf-post_cheat_sheet.pdf>`_ the
PyDPF-Post cheat sheet. This one-page reference provides syntax rules and commands
for using PyDPF-Post. 

On the `PyDPF-Post Issues <https://github.com/ansys/pydpf-post/issues>`_ page,
you can create issues to report bugs and request new features. On the `PyDPF-Post Discussions
<https://github.com/ansys/pydpf-post/discussions>`_ page or the `Discussions <https://discuss.ansys.com/>`_
page on the Ansys Developer portal, you can post questions, share ideas, and get community feedback. 

To reach the project support team, email `pyansys.core@ansys.com <pyansys.core@ansys.com>`_.


.. toctree::
   :maxdepth: 2
   :caption: Getting Started
   :hidden:

   getting_started/index
   user_guide/index
   api/index
   examples/index
   contributing