Interpolate lithium spectra and predict lithium abundance for most main sequence stars
Reason this release was yanked:
pyproject.toml is user friendly, it's just picky about who its friends are
Project description
Breidablik
An interpolation routine and abundance predictor wrapper around stellar spectra for lithium generated from Balder (Amarsi et al. 2016) and the Stagger-grid (Magic et al. 2013). The raw synthetic spectra and models can be found at https://zenodo.org/records/10428804. We use radial basis functions (Bertran de Lis et al. 2022) to interpolate between stellar parameters and lithium abundance inputs to generate interpolated 3D NLTE stellar line profiles; and feedforward neural networks to interpolate between stellar parameters and stellar line strengths, these interpolation models are provided as part of the package. Using the interpolation routine, we can predict the lithium profile given any stellar parameters and lithium abundance input, we can also predict the lithium abundance given an observed spectrum and stellar parameters.
Installation
Install with pip
Automatic
If you are using linux/macOS, you can install using:
wget https://raw.githubusercontent.com/ellawang44/Breidablik/master/install_pip
./install_pip
Once the installation is done, you can delete the installation script.
Manual
If the above automatic installation did not work for you, then to install with pip
, there are 3 steps:
- Install Breidablik through
pip
. This will install Breidablik without the raw synthetic spectra. - Optional, download the raw data. Whilst Breidablik will happily interpolate and predict lithium abundances without the raw synthetic spectra, the raw spectra can be found in
balder.zip
on https://zenodo.org/records/10428804. There are functions underbreidablik.analysis
which interact with the raw synthetic spectra. - Optional, put the raw data in the breidablik folder. The functions in
breidablik.analysis.read
have adata_path
parameter which is the path to the folder containing the raw spectra. By default, this path is set to a folder namedBalder
inside thebreidablik
package. Therefore, I recommend putting the data inside theBalder
folder inside thebreidablik
package; however, this is not a requirement.
Install without pip
Automatic
If you are using linux/macOS, you can navigate to where you want this repository and run:
git clone https://github.com/ellawang44/Breidablik
cd Breidablik
./install
Manual
If the above automatic installation did not work for you, then to install without using pip
, there are 5 steps:
- Navigate to where you want this repository and clone this git repository.
- Navigate into
Breidablik/breidablik
. - Download the models from
models_vX.X.X.zip
on https://zenodo.org/records/10428804 and unzip it. Pick the latest model, i.e. the model with the highest version number. If you are running an older version of Breidablik, pick the model based on the version of Breidablik you want to run. The model version number will be just lower than your Breidablik version number. e.g. running Breidablik v1.1.0 will require models v1.0.0. - Optional, download the raw data from
balder.zip
on https://zenodo.org/records/10428804 and unzip it. - Optional, add this directory to the python path. This makes the directory findable by python no matter where it is launched.
Check that your installation is correct
Optional, to check that the installation was successful, in the Breidablik
folder, you can run:
python -m pytest
If all tests pass with no warnings, then the installation was successful. If you have installed this package through pip
, you can still run the tests, but instead this will need to be done in the breidablik
folder installed by pip
.
Updating the code
The easiest way to update the code is by doing a clean install.
There are 3 components to Breidablik: synthetic spectra from Balder, trained models for interpolation, the code itself.
The synthetic spectra from Balder is downloaded once upon install, if there were updates to this, reinstall is recommended. Note that old versions of Breidablik installed spectra as separate files (~2000 files), new versions of Breidablik have one numpy file per grid. This change was made because pip takes a while to delete a lot of small files. If you are uninstalling an old version of Breidablik, be aware that it might take a while.
The trained models for interpolation is downloaded upon manual install, but comes with the package if installed through pip. If you've installed the code manually, you will need to update the trained models manually.
The code itself can be updated both through pip and git if you installed manually.
Getting Started
See the examples at https://breidablik.readthedocs.io/en/latest/Getting%20Started.html#examples
License and Citation
If you use this package for any academic purpose, please cite Wang et al. 2020 (arXiv:2010.15248) and Wang et al. 2024 (arXiv:2402.02669).
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file breidablik-1.5.0.tar.gz
.
File metadata
- Download URL: breidablik-1.5.0.tar.gz
- Upload date:
- Size: 39.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1f027c0c36927c31b918af0cdebaf4efc9db1d72435ae1fe4b6f5da4448b1cc1 |
|
MD5 | f527687d4483a7dcf61551a3648ade73 |
|
BLAKE2b-256 | fc5a12aaccb4754b9c8d3d083f2115de88017af6489d108f0be47b5c820f1393 |
File details
Details for the file breidablik-1.5.0-py3-none-any.whl
.
File metadata
- Download URL: breidablik-1.5.0-py3-none-any.whl
- Upload date:
- Size: 40.1 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 78a56e29ffd2155132789a7c18be190a8d3f6e06c4aa904e6af3e10e0195c604 |
|
MD5 | 2b22c3af8b225fcf42b0a9283bb102a1 |
|
BLAKE2b-256 | 627991da63e1b854de5f158cd09d37b47fa293ef1a4f1f2325bbf303d915effa |