Emily Boudreaux
a5905e5fed
Two major changes in this version. First stroid now embeds a vacuum coordinate as part of its StroidMesh file (this is a packed set of mfem meshes and GridFunction). This is a logical coordinate from 0 at the stellar surface to 1 at the mesh surface / compactified infinity which can be used by consumers to much more stablly infer position in the vacuum region. Second, there is a new topology backend, multi_block, which has been made the default. See the readme for more information but the basic jist is that multi_block addes 6 transition blocks onto the edge of the core domain. This allows for a much more well conditioned transition from the internal cartesien region to the external spherical region. The mesh conditioning improves by roughly a factor of 1000 for the same refinement level when compared to the legacy topology. The legacy topology is maintained as a option if core_mapping is set to spherified in the config.
Wheel Generation
This directory contains scripts to generate precompiled python wheels for GridFire
Notes
- MacOS wheels can only be generated on macos
- aarch64 wheels can only be generated on aarch64 machines
- x86_64 wheels can only be generated on x86_64 machines
- linux wheels can be generated on any linux machine, but the target architecture must match the machine architecture
- Running each script will take a very long time (could be upwards of half of a day depending on your system) and will require roughly 2GB of disk space
- When generating MacOS wheels, you must have all the correct versions of python installed with
pyenv. Run the scriptutils/wheels/installPyEnvVersions.shto install the correct versions of python.
Usage
Once you know you are on the correct machine, run the script for your desired architecture and operating system. For example, to generate a macos x86_64 wheel, run:
./build-wheels-macos-aarch64.sh https://github.com/4D-STAR/GridFire
Once you have all the wheels generated (which will likely require multiple systems), copy all the wheels into a single
directory (lets assume its called wheels and in the root of the directory) and then run (from the root of the repository):
python -m pip install --upgrade build
python -m build --sdist --outdir wheels
twine upload wheels/*
Thie will also take a while (it needs to upload all the wheels to PyPI) but will result in all the wheels being uploaded to PyPI.