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Matching NEID Spectra

Project description

NEIDspecmatch (Beta)

NEIDSpecMatch: Spectral matching of NEID data. Based on: HPFSpecMatch.

Dependencies

  • pyde, either (pip install pyde) or install from here. This package needs numba (try conda install numba if problems).

  • emcee (pip install emcee)

  • astroquery (pip install astroquery)

  • crosscorr (git clone https://github.com/TeHanHunter/crosscorr.git) pip3 install . NEED fortran installation. For Mac: brew install gcc (GNU fortran). For Ubuntu: sudo apt install gfortran

  • NEIDspec (git clone https://github.com/TeHanHunter/neidspec.git) pip3 install .

  • lmfit (pip install lmfit)

  • barycorrpy (pip install barycorrpy)

    Known Issue: The latest version of barycorrpy deprecated some syntax used in the NEIDSpecMatch. Please use earlier versions (0.4.4 tested to work) while we update the syntax.

Installation

create a new conda env with conda create -n neidspecmatch python==3.10 conda activate neidspecmatch

conda install numba
git clone https://github.com/hpparvi/PyDE.git
cd PyDE
pip3 install .
cd ..
pip3 install emcee
pip3 install astroquery
git clone https://github.com/TeHanHunter/crosscorr.git
cd crosscorr
brew install gcc
pip3 install .
cd ..
git clone https://github.com/TeHanHunter/neidspec.git
cd neidspec
pip3 install .
cd ..
pip3 install lmfit
pip3 install barycorrpy
pip3 install celerite
git clone https://github.com/TeHanHunter/neidspecmatch.git
cd neidspecmatch
pip3 install .

Library download

The current library include 78 library stars. You may download them here. The full directory (yyyymmdd_specmatch_nir/) need to be saved under the library/ folder. Make sure the path in config.py agrees with the name of the library.

Cross-validation and result uncertainty

The cross-validation is a necessary step to estimate the uncertainty of the recovered stellar parameters. To run the cross-validation on the current library, one can run run_crossval.py for the desired order(s). The output include a file in the format of crossvalidation_results_o102.csv. One can take the standard deviation of the column d_teff, d_feh, and d_logg on all/certain rows (depending on the star type you want to estimate the uncertainty).

The alternative is to use the cross-validation result saved in the same link as the library, although we recommend running the cross-validation locally to check the completeness of the installation.

Fit a spectrum

Once the library is in place, one can run NEIDSpecMatch using run_neidspecmatch.py. You need to specify the file path, target name (as in the fits header), orders, and more.

Reference

TODO

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