Skip to main content

Numerical Test Rig for Cascades. A workflows-library for CFD analysis of cascade-flows

Project description

Numerical Test Rig for Cascades.

Features

Easy geometry and post-processing visualization and manipulation with pyvista. Tested methods and functions for math, time-series, and mesh quality analysis.

Dependencies

  • libgl1-mesa-glx (graphics driver)

  • xvfb (virtual Display)

  • libglu1-mesa (gmsh dependency)

  • libxcursor1 (gmsh dependency)

  • libxinerama1 (gmsh dependency)

Python requirement is Python>=3.10. Current NTRfC versions are based on Python 3.11. Only versions <v0.1.0 can be used with older versions of Python. Library requirements will be installed with the package itself. Installation

NTRfC is utilizing powerful and complex dependencies like pyvista,open3d and gmsh. We strongly recommend using virtual or conda environments for installation.

For more information, see:

virtualenv: https://pypi.org/project/virtualenv/ miniconda: https://docs.conda.io/en/latest/miniconda.html anaconda: https://docs.anaconda.com/anaconda/install/index.html mamba: https://mamba.readthedocs.io/en/latest/installation.html

Installation

Installation from pypi

pip install ntrfc

Installation from gitlab with pip

pip install git+https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC.git

Installation from source

After cloning the repository, go to the project root dir and type

python setup.py install

Editable installation from source with pip

After cloning the repository, go to the project root dir and type

pip install -e .

This way you have NTRfC installed but the code is not installed, but linked to the source-code. You don’t have to reinstall the package after your edits. This speeds up testing and will lead to less debugging time.

Singularity releases

Use a singularity container from ntrfc singularity releases: https://cloud.sylabs.io/library/nyhuma/ntrflows/ntr.sif]. The containers will come with a virtual graphics card and a xvfb display-server, enabling you to render on hpc-systems and any other unprepared system with limited graphics capability.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template. It uses the following libraries:

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

ntrfc-0.2.3.tar.gz (3.8 MB view details)

Uploaded Source

Built Distribution

ntrfc-0.2.3-py2.py3-none-any.whl (3.8 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file ntrfc-0.2.3.tar.gz.

File metadata

  • Download URL: ntrfc-0.2.3.tar.gz
  • Upload date:
  • Size: 3.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for ntrfc-0.2.3.tar.gz
Algorithm Hash digest
SHA256 a37fc0b3dbd9b86f9a5caa860bda40405ecd4b62eaf0abe6ba390e1a4a9b516d
MD5 4192a80cc2b65977399e9cba2b2f9ea4
BLAKE2b-256 40d4ca99f7875054112f0f1ea0b385b16d85df260a921ead512b388f711ac30f

See more details on using hashes here.

File details

Details for the file ntrfc-0.2.3-py2.py3-none-any.whl.

File metadata

  • Download URL: ntrfc-0.2.3-py2.py3-none-any.whl
  • Upload date:
  • Size: 3.8 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for ntrfc-0.2.3-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 35f481b3b4ee6f1c90bb78a5920decb59ed6d94b72983045a707d5e6ab44962a
MD5 82b423776db9c0e61304d2c61079aa79
BLAKE2b-256 da9109e0607570a4b493e16ea63a7dd5255d120de0cd77948ba835643e4c9fd9

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