Flexible one-zone open-box chemical evolution modeling. Abundance fitting and stellar feedback calculation. Parameter optimization for simulations and yield table scoring. This is the code described in Philcox, Rybizki & Gutke (ApJ, arXiv)
pip install git+https://github.com/oliverphilcox/ChempyScoring.git
Chempy should run with the latest python 2 and python 3 version. Its dependencies are: Numpy, SciPy, matplotlib, multiprocessing, emcee (for the MCMC), corner (for the MCMC plots), PyTorch (for Neural Networks), scikit-monaco (for Monte Carlo integration), and tqdm (for timing multiprocessing). They are all pip installable and you can also get part of it with Anaconda.
You can install ChempyScoring into a folder where you have write access:
pip install --install-option='--prefix=~/extra_package/' git+https://github.com/oliverphilcox/ChempyScoring.git
Then you have to add the site-packages/ folder which will be one of the newly created subfolders in extra_package/ into the PYTHONPATH variable, e.g.:
export PYTHONPATH=~/extra_package/lib/python3.6/site-packages/:$PYTHONPATH
If you want this to be permanent, you can add the last line to your .bashrc.
- Jan Rybizki (MPIA, rybizki@mpia.de) - Original Chempy
- Oliver Philcox (Harvard, ohep2@alumni.cam.ac.uk) - Yield table scoring
- Hans-Walter Rix (MPIA)
- Andreas Just (ZAH)
- Morgan Fouesneau (MPIA)
- Philcox, Rybizki & Gutcke (ApJ, arXiv)
- Rybizki, Just & Rix (arXiv, ASCL)
- An early version of Chempy is presented in chapter 4 of Jan's phd thesis.
The jupyter tutorial shows the usage of the software for computing yield table scores and best posterior parameters. The original Chempy tutorial illustrate the basic usage of Chempy and basic concepts of galactic chemical evolution modeling. Both can be inspected in the github repository or you can run them interactively on your local machine.
To run them interactively first clone the repository with
git clone https://github.com/oliverphilcox/ChempyScoring.git
Then you can jupyter notebook from within the tutorial folder (it will run if you have installed ChempyScoring).
If you did not install ChempyScoring you can still run the tutorial but need to point to the files in the Chempy folder. Basically you have to cd ../ChempyScoring/ and then replace each from Chempy import ... with from . import ....
You can also have a look at the preliminary Chempy documentation which gives an overview over the Chempy classes and functions, although this does not yet provide support for the Scoring or Neural Network implementations.
Please cite the initial Chempy paper and scoring table code when using the code in your research (so far only arXiv link, will be updated).