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PyFluent-Visualization

PyAnsys PyPI GH-CI MIT Black pre-commit.ci status

Overview

PyFluent-Visualization provides postprocessing and visualization capabilities for PyFluent using PyVista and Matplotlib.

Documentation and issues

For comprehensive information on PyFluent-Visualization, see the latest release documentation.

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.

On the PyFluent Visualization Issues page, you can create issues to submit questions, reports burgs, and request new features. To reach the project support team, email pyansys.core@ansys.com.

Installation

The ansys-fluent-visualization package supports Python 3.10 through Python 3.13 on Windows and Linux.

If you are using Python 3.10, download and install the wheel file for the vtk package from here for Windows or from here for Linux.

Install the latest release from PyPI with:

pip install ansys-fluent-visualization

Alternatively, install the latest release from GitHub with:

pip install git+https://github.com/ansys/pyfluent-visualization.git

If you plan on doing local development of PyFluent-Visualization with Git, install with:

git clone https://github.com/ansys/pyfluent-visualization.git
cd pyfluent-visualization
pip install pip -U
pip install -e .

Dependencies

You must have a licensed copy of Ansys Fluent installed locally. PyFluent-Visualization supports Ansys Fluent 2022 R2 and later.

Getting started

Basic usage

The following code assumes that a PyFluent session has already been created and a Fluent case with input parameters has been set up. For a complete example, see Analyzing your results in the PyFluent-Visualization documentation.

from ansys.fluent.visualization import Graphics
graphics = Graphics(session=session)
temperature_contour = graphics.Contours["contour-temperature"]
temperature_contour.field = "temperature"
temperature_contour.surfaces = ["in1", "in2", "out1"]
temperature_contour.display("window-1")

Usage in a JupyterLab environment

PyFluent-Visualization uses PyVista, which has the ability to display fully featured plots within a JupyterLab environment using ipyvtklink. Find out about using ipyvtklink with PyVista here <https://docs.pyvista.org/user-guide/jupyter/ipyvtk_plotting.html>

License and acknowledgments

PyFluent-Visualization is licensed under the MIT license.

PyFluent-Visualization makes no commercial claim over Ansys whatsoever. This tool extends the functionality of Ansys Fluent by adding a Python interface to Fluent without changing the core behavior or license of the original software. The use of the interactive Fluent control of PyFluent-Visualization requires a legally licensed local copy of Fluent.

For more information on Fluent, visit the Fluent page on the Ansys website.