Skip to main content

A python wrapper for ansys Fluent visualization

Project description

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 3.12 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.pyvista import Graphics
graphics = Graphics(session=session)
temperature_contour = graphics.Contours["contour-temperature"]
temperature_contour.field = "temperature"
temperature_contour.surfaces_list = ["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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ansys_fluent_visualization-0.14.dev0.tar.gz (21.3 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file ansys_fluent_visualization-0.14.dev0.tar.gz.

File metadata

File hashes

Hashes for ansys_fluent_visualization-0.14.dev0.tar.gz
Algorithm Hash digest
SHA256 2d9c483de242e3ab0e01d29368681a34c13513c1c512055d916063802f81b24b
MD5 60df640cf30fbd6181d132bd34ffa93f
BLAKE2b-256 c648ac9b7fae0b23fa6ca41342601981e95219e06267e98fd1e6c2be76af1337

See more details on using hashes here.

File details

Details for the file ansys_fluent_visualization-0.14.dev0-py3-none-any.whl.

File metadata

File hashes

Hashes for ansys_fluent_visualization-0.14.dev0-py3-none-any.whl
Algorithm Hash digest
SHA256 1af686934f6fad522595afaa1540e5927197112cab29941a9659dbd83b254984
MD5 1608f04a1b6211b7adabc01586693335
BLAKE2b-256 62387ec48e8919431764847772b103259c316ad603a340fe158a914981a2fdd3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page