How to Install

For managing python and packages, we recommend using Anaconda (https://anaconda.org) and the channel conda-forge. Although it is not essential, you can create a separate environment for running the PLP.

You have to download the current version of pipeline. You may download the most recent tarball of the pipeline package from the releases page. If you are familiar with "git", you can use "git clone" to download the source from the master branch.

git clone https://github.com/igrins/plp.git

The IGRINS pipeline version v3.0.0 runs in Python 3.11 (note it is currently incompatible with python 3.12). It is usually run in Linux or MacOS, but might be installable in Windows (let us know if you get it running). Install python 3.11 and the latest version of the python dependencies below.

The PLP has the following python dependencies:

• numpy
• scipy
• astropy
• matplotlib
• pandas
• simplejson
• astroscrappy (recommended if you want to use cosmic ray rejection https://astroscrappy.readthedocs.io/en/latest/)

After installing Anaconda, below is an example of the commands you want to type into the terminal to create the a python environment (here called igrins-plp-env), install the various python dependencies, and install the PLP by cloning it from the git repo. You can copy and paste what is below into your terminal and it should work:

conda create --name igrins-plp-env --channel=conda-forge python=3.11
conda activate igrins-plp-env
conda install numpy
conda install scipy
conda install astropy
conda install matplotlib
conda install pandas
conda install simplejson
conda install astroscrappy
git clone https://github.com/igrins/plp.git

Now go into the PLP directory

cd PLP

Now you need to give the PLP access to your IGRINS raw data. The "indata" directory should contain or point to the directory where the rawdata is organized by its UT date. For example, "indata/20140525" should contain data taken in 2014-05-25.

> ls indata/20140525
IGRINS_DT_Log_20140525-1_H.txt  SDCH_20140525_0083.fits
IGRINS_DT_Log_20140525-1_K.txt   SDCK_20140525_0001.fits
IGRINS_DT_Log_20140526-1_H.txt   SDCK_20140525_0002.fits
IGRINS_DT_Log_20140526-1_K.txt   SDCK_20140525_0003.fits
SDCH_20140525_0001.fits          SDCK_20140525_0004.fits
SDCH_20140525_0002.fits          SDCK_20140525_0005.fits
SDCH_20140525_0003.fits          SDCK_20140525_0006.fits
...

You can do this by either copying the raw data directly into the "indata" directory, or by creating a symbolic link for each night, or creating a symbolic link for the whole "indata" directory itself. See https://kb.iu.edu/d/abbe for how to create symbolic links.