dustapprox -- A tool for computing approximative extinction coefficients
This is a set of tools to compute photometric extinction coefficients in a quick and dirty way.
full documentation at: http://mfouesneau.github.io/dustapprox/
Quick Start
import pandas as pd
from dustapprox import models
from dustapprox.literature import edr3
import pylab as plt
# get Gaia models
lib = models.PrecomputedModel()
r = lib.find(passband='Gaia')[0] # taking the first one
model = lib.load_model(r, passband='GAIA_GAIA3.G')
# get some data
data = pd.read_csv('models/precomputed/kurucs_gaiaedr3_small_a0_grid.csv')
df = data[(data['passband'] == 'GAIA_GAIA3.G') & (data['A0'] > 0)]
# values
kg_pred = model.predict(df)Installation
- Installation from PyPI
pip install git+https://github.com/mfouesneau/gdr3_extinction
- Manual installation
download the repository and run the setup
git clone https://github.com/mfouesneau/gdr3_extinction python setup.py install
Contributors
- Morgan Fouesneau (@mfouesneau)
- René Andrae
- Rosanna Sordo
- Thavisha Dharmawardena
Contributing
Please open a new issue or new pull request for bugs, feedback, or new features you would like to see. If there is an issue you would like to work on, please leave a comment, and we will be happy to assist. New contributions and contributors are very welcome!
