def get_eleanor(sectors='all',
tic=None,
coords=None,
out_sec=False,
height=15,
width=15,
bkg_size=31,
do_psf=False,
do_pca=False,
out_flux='corr_flux',
norm=True,
errorcalc=True,
qual_flag=True):
#!!Add more docstrings for all keywords!!
#!!Add common name processing instead of just tic!!
"""
Function to get a light curve from the TESS full frame images (FFIs) using
the Python package eleanor.
Parameters
----------
sectors : str or array or list
The sectors that eleanor will use to produce the light curve. If set to
'all', then all available sectors will be used in the light curve
production.
tic : int or None
TIC ID for the object that a light curve is desired for. If set to None,
coords must have a valid input.
coords : tuple of floats
The RA and Dec of the object that a light curve is desired for. Must be
of the form (RA, Dec) in decimal degrees. If set to None, the tic
argument cannot be None.
out_sec : bool
Flag controlling whether an array containing the sectors used to extract
the light curve will be output. If True, an additional output will be
expected.
height : int
Height in pixels of the postage stamp with which to extract the light
curve.
width : int
Height in pixels of the postage stamp with which to extract the light
curve.
bkg_size : int
Background size to be considered for the background subtraction from the
light curve.
do_psf : bool
Flag to determine whether a PSF-corrected light curve will be generated
as an additional option to the corrected light curve.
do_pca : bool
Flag to deteremine whether a PCA-corrected light curve will be generated
as an additional option to the corrected light curve.
out_flux : str
Which of the light curves to output. Options are 'corr_flux', 'psf_flux',
and 'pca_flux'. Only one may be selected. If either 'psf_flux' or
'pca_flux' are selected, the do_psf and do_pca flags must be set to True,
respectively.
norm : bool
Flag determining whether the light curve will be normalized prior to
output.
errorcalc : bool
Flag determining whether the RMS errors will be calculated for the light
curve.
qual_flag : bool
Flag determining whether the timestamps with bad quality flags will be
excluded automatically.
Returns
-------
lc : 'LightCurve' object
The combined light curve from each sector for the coordinates or TIC ID
requested.
sectors : array
Optional output array containing the sectors that the combined light
curve was extracted from.
"""
import eleanor
if tic is None and coords is None:
raise ValueError('Please make sure either tic or coords have valid ' +
'input')
if tic:
star = eleanor.multi_sectors(tic=tic, sectors=sectors)
else:
star = eleanor.multi_sectors(coords=coords, sectors=sectors)
secs = []
data = []
for s in star:
datum = eleanor.TargetData(s,
height=height,
width=width,
bkg_size=bkg_size,
do_psf=do_psf,
do_pca=do_pca)
data.append(datum)
sec = s.sector
secs.append(sec)
for i in range(len(data)):
q = data[i].quality == 0
time = data[i].time
if out_flux == 'corr_flux':
flux = data[i].corr_flux
elif out_flux == 'pca_flux':
flux = data[i].pca_flux
elif out_flux == 'psf_flux':
flux = data[i].psf_flux
if qual_flag:
time = time[q]
flux = flux[q]
if norm:
flux = flux / np.median(flux)
flux_err = None
if errorcalc:
flux_err = np.ones(len(flux)) * rms(flux)
if i == 0:
lc = LightCurve(time, flux, flux_err=flux_err)
else:
sec_lc = LightCurve(time, flux, flux_err=flux_err)
lc = lc.append(lc)
if out_sec:
return lc, secs
else:
return lc
def get_mlffi(tic=None,
ra=None,
dec=None,
sectors='all',
flux_type='corr',
out_sec=False):
"""
For use on tesseract only. Fetches FFI light curves made by Brian Powell.
Parameters
----------
tic : int or None
TIC ID of target. If None, both ra and dec must not be None.
ra : float or None
RA of target. If None, tic must not be None. If not None, dec must also
not be None.
dec : float or None
Dec of target. If None, tic must not be None. If not None, ra must also
not be None.
sectors : str or list or array
The desired sectors to make the light curve from. May be set to 'all' to
use all available light curves.
flux_type : str
The type of correction applied to the light curve. Options are 'raw',
'corr', and 'pca'.
out_sec : bool
Flag determining whether or not the sectors that the light curve was
generated from are output. If True, an additional output will be
expected.
Returns
-------
lc : 'LightCurve' object
The combined light curve.
sectors : array
The sectors from which the output light curve was generated.
"""
if not tic and not ra and not dec:
raise ValueError('Please provide valid input for either tic or ra/dec')
if sectors == 'all':
if not ra and not dec:
info = tessobs_info(tic=tic)
else:
info = tessobs_info(ra=ra, dec=dec)
sectors = list(set(info['sector']))
if not isinstance(sectors, list):
raise ValueError('Sectors must be a list!')
if not tic:
tic = coord_to_tic(ra, dec)
camera_arr = []
chip_arr = []
Tmag_arr = []
sects = sectors
if not os.path.isdir('/data/tessraid/bppowel1/'):
raise ValueError('Not on tesseract')
for i in range(len(sects)):
path = '/data/tessraid/bppowel1/tesslcs_sector_' + str(
sects[i]) + '_104'
lc_files = []
for (dirpath, dirnames, filenames) in os.walk(path):
for name in filenames:
lc_files.append(os.path.join(dirpath, name))
lc_files = [t for t in lc_files if 'tesslc_' in t]
tics = [int(t.split('.')[0].split('_')[-1]) for t in lc_files]
path = [s for s in lc_files if str(tic) in s]
try:
fp = open(str(path[0]), 'rb')
except:
print('Target not found in Sector %s' % sects[i])
sects.remove(sects[i]) #trouble line, may cause silent error
continue
data = pickle.load(fp)
fp.close()
Tmag_arr.append(data[2])
camera_arr.append(data[4])
chip_arr.append(data[5])
time = data[6]
flux_err = data[10]
if flux_type == 'corr':
flux = data[8]
elif flux_type == 'raw':
flux = data[7]
elif flux_type == 'pca':
flux = data[9]
if i == 0:
lc = LightCurve(time, flux, flux_err=flux_err)
else:
sec_lc = LightCurve(time, flux, flux_err=flux_err)
lc.append(sec_lc)
lc = lc.normalize()
lc.Tmag = Tmag_arr
lc.camera = camera_arr
lc.chip = chip_arr
if out_sec:
return lc, sects
else:
return lc