<jupyter_start><jupyter_text>Looking at the giant neaby star<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 astropy.modeling import models, fitting
import lightkurve as lk
from astropy.timeseries import LombScargle
import scipy.signal as signal

#matplotlib set up
%matplotlib inline
from matplotlib import rcParams
rcParams["figure.figsize"] = (14, 5)
rcParams["font.size"] = 20
from lightkurve import search_targetpixelfile
pixelfile = search_targetpixelfile('GD394', sector=15).download(quality_bitmask='hardest')
pixelfile.plot(frame=1,aperture_mask=pixelfile.pipeline_mask);
pixelfile.interact()
lc = lk.lightcurvefile.LightCurveFile(path='tess2019226182529-s0015-0000000259773610-0151-s_tp-custom-lc.fits') 
lc1 = fits.open('tess2019226182529-s0015-0000000259773610-0151-s_tp-custom-lc.fits')
data = lc1[1].data
lc2 = lk.LightCurve(time=data['TIME'], flux= data['FLUX'])
#lc2.scatter()

pg = lc2.to_periodogram(oversample_factor=10,minimum_period=0.8*u.day, maximum_period=1.5*u.day)
#plt.plot(pg.period, pg.power)

pg.plot()
print(pg.period_at_max_power)


pf16 = search_targetpixelfile('GD394', sector=16).download(quality_bitmask='hardest')
pf16.plot(frame=1,aperture_mask=pixelfile.pipeline_mask);
pf16.interact()
lc12 = fits.open('tess2019253231442-s0016-0000000259773610-0152-s_tp-custom-lc.fits')
data = lc12[1].data
lc22 = lk.LightCurve(time=data['TIME'], flux= data['FLUX'])
#lc2.scatter()

pg2 = lc22.to_periodogram(oversample_factor=10,minimum_period=0.8*u.day, maximum_period=1.2*u.day)
plt.plot(pg2.period, pg2.power)
pixelfile.interact_sky()<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '10683', 'license': 'MIT', 'n_tokens_mistral': 787, 'n_tokens_neox': 685, 'n_words': 115, 'path': 'closest.ipynb', 'repo_name': 'davidjwilson/GD394-Tess', 'size': '1787'}