Numerical Test Rig for Cascades. A workflows-library for cfd-analysis of cascade-flows
Project description
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)
Current NTRfC versions are based on Python 3.10. 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 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)
History
0.1.6 (2023-10-13)
productive meshing algorithm
minor improvements
0.1.5 (2023-07-04)
bugfixes alphashape
initial gmsh intigration
jupyternotebook testing
improved codecov
0.1.4 (2023-06-25)
cleaner structure, more reliability
pypi deployment
sphynx docs
removed bugs
0.1.3 (2023-03-11)
bug fixes
implementation of a new timeseries stationarity analysis
yplus postprocessing
additional tests
0.1.2 (2022-20-12)
meshquality methods
example data sets
jupyter notebook examples
Project details
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