ATMOSPHERIX_DATA_RED

We provide a sample tool to read SPIRou "t.fits" files, process the data (remove telluric/stella contributions) and make the correlation analysis for a given planet atmosphere template.

Requirements: Python 3 modules

• scipy
• pickle
• sklearn: https://scikit-learn.org/
• batman: https://lweb.cfa.harvard.edu/~lkreidberg/batman/
• astropy

import numpy as np import sys import os import matplotlib.pyplot as plt import pickle from sklearn.preprocessing import StandardScaler from sklearn.decomposition import PCA from sklearn.decomposition import FastICA import time

To run the code:

1. Going from a list of "t.fits" files to the format compatible with our data reduction code:

   • Read fits files

   • Correct for Blaze and remove NaNs from the observations

   • Compute orbital phase and transit window

   • Store pre-processed data in ".pkl" files To apply the code, change the paramters in the file "read_data.py" and type the following command line:

     $ python read_data.py

2. Data reduction process: change parameters in "reduce_data.py" and run

   $ python reduce_data.py

   Test case: You can download observations of Gl 15 A (in the .pkl format) and the associated models via the following repository: https://drive.google.com/drive/folders/1eWhGpNrjLUSoyWKbWYVv15o0UZ0Ucn6D?usp=sharing

3. Compute the correlation between the data and model for a grid of planet velocimetric semi-amplitude and systemic velocity:

Change parameters in "get_correl.py" and run

$ python get_correl.py