<jupyter_start><jupyter_text>Looking at the reprocessed light curves<jupyter_code>import numpy as np
import matplotlib.pyplot as plt
import astropy.io.fits as fits
import os
import glob
from astropy.table import Table
from astropy.io import ascii
import astropy.units as u
import astropy.constants as const
from scipy.interpolate import interpolate
from astropy.convolution import convolve, Box1DKernel
from astropy.modeling import models, fitting
import lightkurve as lk

#matplotlib set up
%matplotlib inline
from matplotlib import rcParams
rcParams["figure.figsize"] = (14, 5)
rcParams["font.size"] = 20<jupyter_output><empty_output><jupyter_text>First observation that was reprocessed, checking on 20201109<jupyter_code>path = '/media/david/5tb_storage1/gd394_chandra/21181/working/'
tbin = 100
fname = 'ob21181_{}slc.fits'.format(tbin)
lcpath = path+fname 
data = fits.getdata(lcpath, 1)
t, c, e = data['TIME'], data['COUNT_RATE'], data['COUNT_RATE_ERR']
plt.errorbar(t-t[0], c, yerr=e, marker='o', ls='none')
plt.ylim(91, 119)
#plt.show()
#plt.plot(t, data['EXPOSURE'])
plt.ylabel('Counts (s$^{-1}$)')
plt.xlabel('Time (s)')
plt.tight_layout()
plt.savefig('plots/ob21181_{}slc.pdf'.format(tbin))
data.names
fits.getheader(lcpath,1)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13101815311760062, 'fraction_numerical': 0.036306235201262825, 'mean_word_length': 7.076433121019108, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '114980', 'license': 'MIT', 'n_tokens_mistral': 513, 'n_tokens_neox': 462, 'n_words': 110, 'path': 'chandra_lcs.ipynb', 'repo_name': 'davidjwilson/gd394_chandra', 'size': '1267'}