| Name | ntrfc JSON |
| Version |
0.2.4
JSON |
| download |
| home_page | None |
| Summary | Numerical Test Rig for Cascades. A workflows-library for CFD analysis of cascade-flows |
| upload_time | 2024-11-15 14:10:43 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT License |
| keywords |
ntrfc
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
============
NTRfC README
============
**Numerical Test Rig for Cascades.**
* Free software: MIT license
* Documentation: https://ntrfc.readthedocs.io.
* NTRfC is the base of the (NTRFlows)[https://gitlab.uni-hannover.de/tfd_public/tools/NTRFlows] repository, a workflow for cfd parameter studies
**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:
- [pyvista](https://github.com/pyvista)
- [gmsh](http://gmsh.info/)
- [Cookiecutter](https://github.com/audreyr/cookiecutter)
- [audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage)
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