How to download NEID Solar data from the NEID Atrchives at NExScI

This tutorial was originally developed for the Sun-as-a-Star Splinter at the Extremely Precise Radial Velocities Sixth Workshop (EPRV6) in June 2024.
Main contrutors: Khaled Al Moulla and Ryan Rubenzhal.

This tutorial uses the NEID Archive Python API. To install it use:

                
                pip install git+https://github.com/Caltech-IPAC/pyNEID.git


Import packages and set up output directory

                from astropy.io import fits
from glob import glob
import matplotlib.pyplot as plt
import numpy as np
import os
from pyneid.neid import neid

output_directory = 'sun_neid_l2/'
os.makedirs(output_directory, exist_ok=True)


Define range of time and basic parameter, then query the NEID files and download them. For this tutorial we will be downloading the level 2 data (the RV level) as FITS files.

                date_min = '2021-01-14 00:00:00'
date_max = '2021-01-14 23:59:59'

param = dict()
param['datalevel'] = 'solarl2'
param['datetime' ] = date_min + '/' + date_max

# Query
Neid.query_criteria(param, format='csv', outpath=output_directory+'temp.tbl')
# Download L2 files
Neid.download(output_directory+'temp.tbl', 'solarl2', 'csv', output_directory, start_row=0, end_row=3)
# Delete temporary file
os.remove(output_directory+'temp.tbl')


To extract the relevant information, loop over the files and extract the needed data from the headers.

                files = glob(output_directory+'**/*.fits', recursive=True)
Nfile = len(files)

# Empty arrays for header variables
time_val = np.empty(Nfile)
vrad_val = np.empty(Nfile)
vrad_err = np.empty(Nfile)

# Loop files
for i in range(Nfile):
    # Open FITS file
    hdul = fits.open(files[i])

    # Extract header variables
    header = hdul[12].header
    time_val[i] = header['CCFJDMOD']
    vrad_val[i] = header['CCFRVMOD']
    vrad_err[i] = header['DVRMSMOD']

    # Close FITS file
    hdul.close()


Example plot of the extracted data.

                plt.figure()
plt.errorbar(time_val, vrad_val, vrad_err, fmt='.', color='k', ecolor='r')
plt.xlabel('BJD [d]')
plt.ylabel('RV [km/s]')
plt.show()
NEID Solar Plot