Add cheat sheet links in PyDPF-Core doc

README.md

@@ -4,44 +4,61 @@
 [![pypi](https://badge.fury.io/py/ansys-dpf-post.svg?logo=python&logoColor=white)](https://pypi.org/project/ansys-dpf-post)
 [![MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
-The Ansys Data Processing Framework (DPF) is designed to provide numerical
-simulation users and engineers with a toolbox for accessing and
-transforming simulation data.
+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 result files) allows you to extract simulation metadata as well
-as results and then apply postprocessing operations on it.
+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 result files for:
+The latest version of DPF supports Ansys solver results files for:
 
-  - MAPDL (`.rst`, `.mode`, `.rfrq`, `.rdsp`)
-  - LS-DYNA (`.d3plot`, `.binout`)
-  - Fluent (`.cas/dat.h5`, `.flprj`)
-  - CFX (`.cad/dat.cff`, `.flprj`)
+- Mechanical APDL (`.rst`, `.mode`, `.rfrq`, `.rdsp`)
+- LS-DYNA (`.d3plot`, `.binout`)
+- Fluent (`.cas/dat.h5`, `.flprj`)
+- CFX (`.cad/dat.cff`, `.flprj`)
 
-See the `PyDPF-Core main page <https://dpf.docs.pyansys.com/version/stable/index.html>`_
-for more information on compatibility.
+For more information on file support, see the [main page](https://dpf.docs.pyansys.com/version/stable/index.html)
+in the PDF-Core documentation.
 
-This module leverages the PyDPF-Core project's ``ansys-dpf-core`` package, which is
+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 Ansys DPF.
 
-## Documentation
+## Documentation and issues
 
-For comprehensive information on this package, see the [PyDPF-Post Documentation](https://post.docs.pyansys.com),
-For detailed how-to information, see the [Examples](https://post.docs.pyansys.com/version/stable/examples/index.html)
-in the PyDPF-Post documentation.
+Documentation for the latest stable release of PyPDF-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-Core 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 [[email protected]](mailto:[email protected]).
 
 ## Installation
 
-To install this package, use this command:
+To install this package, run this command:
 
 ```
 pip install ansys-dpf-post
 ```
 
-You can also clone and install this package with this code:
+You can also clone and install this package with these commands:
 
 ```
 git clone https://github.com/ansys/pydpf-post
@@ -51,10 +68,11 @@ pip install . --user
 
 ## Brief demo
 
-Provided you have Ansys 2023 R1 or later installed, a DPF server starts
-automatically once you start using PyDPF-Post.
+Provided you have Ansys 2023 R1 or later installed, a DPF server automatically starts
+once you start using PyDPF-Post.
 
-To load a simulation to extract and post-process results, use this code:
+To load a simulation for a MAPDL result file to extract and
+postprocess results, use this code:
 
 ```pycon
 >>> from ansys.dpf import post
@@ -85,8 +103,8 @@ To load a simulation to extract and post-process results, use this code:
 ```
 ![Example Stress plot Crankshaft](https://github.com/ansys/pydpf-post/raw/master/docs/source/images/crankshaft_stress.png)
 
-To run PyDPF-Post with Ansys versions 2021 R1 and 2022 R2, use this code to
-start the legacy PyDPF-Post tools::
+To run PyDPF-Post with Ansys 2021 R1 through 2022 R2, use this code to
+start the legacy PyDPF-Post tools:
 
 ```pycon
 >>> from ansys.dpf import post
@@ -97,7 +115,12 @@ start the legacy PyDPF-Post tools::
 ```
 ![Example Stress plot Crankshaft](https://github.com/ansys/pydpf-post/raw/master/docs/source/images/crankshaft_stress.png)
 
-## License
+## License and acknowledgements
+
+PyDPF-Post is licensed under the MIT license. For more information, see the
+[LICENSE](https://github.com/ansys/pydpf-post/raw/master/LICENSE) file.
 
-``PyDPF-Post`` is licensed under the MIT license. For more information, see the
-[LICENSE](https://github.com/ansys/pydpf-post/raw/master/LICENSE).
+PyDPF-Post makes no commercial claim over Ansys whatsoever. This library
+extends the functionality of Ansys DPF by adding a Python interface
+to DPF without changing the core behavior or license of the original
+software.

docs/source/index.rst

@@ -2,36 +2,36 @@
 PyDPF-Post
 ==========
 
-The Ansys Data Processing Framework (DPF) is designed to provide
-numerical simulation users and engineers with a toolbox for accessing
-and transforming simulation data.
+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 result files) allows you
-to extract simulation metadata as well as results and then apply postprocessing
-operations on it.
+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 result files for:
+The latest version of DPF supports Ansys solver results files for:
 
-- MAPDL (``.rst``, ``.mode``, ``.rfrq``, ``.rdsp``)
-- LS-DYNA (``.d3plot``, ``.binout``)
-- Fluent (``.cas/dat.h5``, ``.flprj``)
-- CFX (``.cad/dat.cff``, ``.flprj``)
+- Mechanical APDL (`.rst`, `.mode`, `.rfrq`, `.rdsp`)
+- LS-DYNA (`.d3plot`, `.binout`)
+- Fluent (`.cas/dat.h5`, `.flprj`)
+- CFX (`.cad/dat.cff`, `.flprj`)
 
-See the `PyDPF-Core main page <https://dpf.docs.pyansys.com/version/stable/index.html>`_
-for more information on file support.
+For more information on file support, see the `main page <https://dpf.docs.pyansys.com/version/stable/index.html>`_
+in the PDF-Core documentation.
 
-This module leverages the PyDPF-Core project's ``ansys-dpf-core`` package, which is
+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 installed, a DPF server starts
-automatically once you start using PyDPF-Post.
+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:
@@ -76,7 +76,7 @@ postprocess results, use this code:
 .. figure:: ./images/crankshaft_stress.png
     :width: 300pt
 
-To run PyDPF-Post with Ansys versions 2021 R1 and 2022 R2, use this code to
+To run PyDPF-Post with Ansys 2021 R1 through 2022 R2, use this code to
 start the legacy PyDPF-Post tools:
 
 .. code:: python
@@ -91,7 +91,7 @@ start the legacy PyDPF-Post tools:
     :width: 300pt
 
 
-For comprehensive how-to information, see :ref:`gallery`.
+For comprehensive examples of how you use PyDPF-Post, see :ref:`gallery`.
 
 
 Key features
@@ -105,14 +105,34 @@ 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>`_.
+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 `[email protected] <[email protected]>`_.
 
 
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