#print((gaia_data1["dec"])[rv_index])
#ra_vals = (gaia_data1["ra"])[rv_index]
#dec_vals = (gaia_data1["dec"])[rv_index]
gaia_IDs = (gaia_data1b)[rv_index]
ticIDs = np.zeros(1265)
additive = 0
#print(ra_vals[[0]])
#ra_vals = np.array(ra_vals)
#dec_vals = np.array(dec_vals)
while additive < 1265:
mast_table = Catalogs.query_criteria(catalog="Tic", GAIA=str(gaia_IDs[additive]),objType="STAR")
print(additive)
ticIDs[additive] = int(mast_table["ID"][0])
additive += 1
print(ticIDs)
'''
for element in ra_vals:
print(element)
print(np.where(ra_vals == element)[0][0])
print(ra_vals[np.where(ra_vals == element)[0][0]])
additive += 1
if additive == 10:
break
def create_standard(self, trimmed):
'''
Create a standardized table, pulling at least the necessary columns
from the raw table and potentially including others too.
'''
t = trimmed
n = len(t)
s = Table()
# PICK UP FROM HERE!!!!!!!!!!!!!
# pull out the name as the CTOI
s['name'] = ['TOI{:.2f}'.format(c) for c in t['CTOI']]
s['hostname'] = ['TOI{:.0f}'.format(c) for c in t['CTOI']]
s['period'] = t['Period (days)']
s['transit_duration'] = t['Duration (hrs)'] / 24
s['stellar_teff'] = t['Stellar Eff Temp (K)']
s['stellar_radius'] = t['Stellar Radius (R_Sun)']
#t['TIC'].name = 'TIC ID'
# search for the table from MAST
print('downloading the TIC. this may take a minute? or restart?')
tic_table = Catalogs.query_criteria(catalog="Tic",
ID=np.unique(t['TIC ID']))
# preface all the columns with TIC so we can keep them straight
for k in tic_table.colnames:
tic_table[k].name = f'TIC {k}'
# make sure the indices are integers
tic_table['TIC ID'] = np.array(tic_table['TIC ID']).astype(np.int)
withtic = join(t, tic_table, 'TIC ID', join_type='left')
# pull out some magnitudes
s['Jmag'] = withtic['TIC Jmag'] # KLUDGE!!!!!t['koi_jmag']
s['Vmag'] = withtic['TIC Vmag']
s['G'] = withtic['TIC GAIAmag']
s['T'] = withtic['TIC Tmag']
# planet radius
s['radius'] = withtic['Radius (R_Earth)']
s['radius_uncertainty_upper'] = withtic['Radius (R_Earth) Error']
s['radius_uncertainty_lower'] = -withtic['Radius (R_Earth) Error']
#KLUDGE?
s['transit_ar'] = withtic['a/Rad_s']
#KLUDGE?
#s['rv_semiamplitude'] = t['pl_rvamp'] #t.MaskedColumn(t['K'], mask=t['K']==0.0)
s['mass'] = withtic['Mass (M_Earth)']
s['mass_uncertainty_upper'] = withtic['Mass (M_Earth) Error']
s['mass_uncertainty_lower'] = -withtic['Mass (M_Earth) Error']
s['radius_ratio'] = withtic['Radius (R_Earth)'] * u.Rearth / withtic[
'Stellar Radius (R_Sun)'] / u.Rsun
s['ra'] = withtic['RA']
s['dec'] = withtic['Dec']
s['transit_b'] = withtic['Impact Param']
# is this usually Gaia??
s['distance'] = withtic['Stellar Distance (pc)']
s['distance_uncertainty_upper'] = np.zeros(n) + np.nan
s['distance_uncertainty_lower'] = np.zeros(n) + np.nan
s['disposition'] = withtic['User Disposition']
# a little kludge
#s['stellar_teff'][s['name'] == 'GJ 436b'] = 3400.0
#s['stellar_teff'][s['name'] == 'Qatar-1b'] = 4860.0
#s['stellar_radius'][s['name'] == 'WASP-100b'] = 1.5#???
s.sort('name')
self.standard = s
def query_mast(self):
""" Fetch the data for this star in astroquery.mast using the TICID
"""
t = Catalogs.query_criteria(target_name=self.ticid)
return t
def TIC_byID(ID):
from astroquery.mast import Catalogs
catTable = Catalogs.query_criteria(ID=ID, catalog="Tic")
return catTable
def get_tess_stars_from_sector(sector_num,
datapath=utils.TESS_DATAPATH,
force_redownload=False,
verbose=True):
'''
Queries https://tess.mit.edu/observations/target-lists/ for the input catalog from TESS sector 'sector_num',
and for each target in that list, gets its data from astroquery and joins the two catalogs.
Arguments
---------
sector_num : int
The TESS sector number for which information is being requested.
datapath : str
The top-level path to which data should be stored.
verbose : bool
Whether to print statements on the script's progress.
Returns
-------
stars : pd.DataFrame
The joined TIC and target-list data.
'''
# sets up file paths and names
sector = str(sector_num).zfill(3)
if datapath is None:
datapath = os.getcwd()
subpath = "tesstargets" + os.path.sep + "TESS_targets_S{}.csv".format(
sector)
fullpath = os.path.join(datapath, subpath)
noises_path = os.path.join(
datapath, "tess_photometric_noise" + os.path.sep +
"TESS_noise_S{}.csv".format(sector))
if (not os.path.exists(fullpath)
) or force_redownload or utils.GLOBAL_FORCE_REDOWNLOAD:
# queries the target list
url = utils.get_sector_pointings(sector_num)
if verbose or utils.GLOBAL_VERBOSE:
print("Getting sector {0} observed targets from {1}.".format(
sector_num, url))
req = requests.get(url)
if not req.ok:
raise requests.exceptions.HTTPError(
"Data from sector {} is not available.".format(sector_num))
observations = pd.read_csv(BytesIO(req.content), comment='#')[[
'TICID', 'Camera', 'CCD'
]] # MAST has Tmag, RA, Dec at higher precision
observed_ticids = observations['TICID'].values
# queries MAST for stellar data
if verbose or utils.GLOBAL_VERBOSE:
print("Querying MAST for sector {0} observed targets.".format(
sector_num))
with warnings.catch_warnings():
warnings.simplefilter("ignore")
tic_data = Catalogs.query_criteria(catalog='Tic',
ID=observed_ticids).to_pandas()
tic_data = tic_data.astype({"ID": int})
merged_data = tic_data.merge(observations,
left_on='ID',
right_on='TICID')
if os.path.exists(noises_path):
merged_data = merged_data.merge(pd.read_csv(noises_path,
index_col=0,
comment='#'),
on="ID")
else:
print(
"Noise values not found on path: change file location or download using get_tess_photometric_noise.py."
)
merged_data = merged_data.rename({"ID": "ticid"})
merged_data.to_csv(fullpath)
if verbose or utils.GLOBAL_VERBOSE:
print("Saved TIC data from TESS sector {0} to path {1}.".format(
sector_num, fullpath))
return merged_data
else:
stellar_sector_data = pd.read_csv(fullpath, index_col=0)
if "noise" not in stellar_sector_data.index and os.path.exists(
noises_path):
stellar_sector_data = stellar_sector_data.merge(pd.read_csv(
noises_path, index_col=0, comment='#'),
on="ID")
stellar_sector_data.to_csv(fullpath)
if verbose or utils.GLOBAL_VERBOSE:
print(
"Added photometric noise values to TIC data from TESS sector {0} to path {1}."
.format(sector_num, fullpath))
return stellar_sector_data
def ticid2radec(entry):
if debug:
print(
"<p>DEBUGGING: trying to call astropy.mast.Catalogs.query_criteria()</p>"
)
#from .coordconvert import ra2decimal, dec2decimal
#from cgi import escape
import warnings, datetime
if "GATEWAY_INTERFACE" in os.environ:
import __main__
homedir = os.path.abspath(
os.path.join(os.path.dirname(__main__.__file__), '../tmp/'))
## # To make astropy work from w/in Apache? XDG variables don't work.
os.environ.update({'HOME': homedir})
if not (os.path.isdir(homedir) or os.path.islink(homedir)):
if debug: print("<p>Trying to make homedir {}</p>".format(homedir))
try:
os.mkdir(homedir)
except Exception as e:
print(
"<p><font color=red>ERROR: Failed to make homedir with exception {}</font></e>"
.format(e))
return None
homedir = os.environ["HOME"]
if debug:
print("<p>Homedir is {} with contents:".format(homedir))
print(os.listdir(homedir))
if os.path.isdir("{}/.astropy".format(homedir)):
print(os.listdir("{}/.astropy".format(homedir)))
print("</p>\n")
if debug: print("<p>DEBUGGING: environ is {}</p>".format(os.environ))
key = 'HTTP_HOST'
if key in os.environ:
if 'heasarcdev' not in os.environ[key]:
if debug:
print(
"<p>DEBUGGING: {} is {}; trying to reset the HTTP proxies to 128.183.17.248:443</p>"
.format(key, os.environ[key]))
os.environ.update({
"HTTPS_PROXY": "128.183.17.248:443",
"HTTP_PROXY": "128.183.17.248:443"
})
else:
if debug:
print(
"<p>DEBUGGING: {} is {}; NOT trying to reset the HTTP proxies</p>"
.format(key, os.environ[key]))
sys.stdout.flush()
if debug:
print("<p>DEBUG: trying to import astroquery.mast.Catalogs</p>")
print("<p>{} DEBUG: HOME dir is currently {}</p>".format(
datetime.datetime.now(), os.environ['HOME']))
print("<p>{} DEBUG: HTTP_HOST is currently {}</p>".format(
datetime.datetime.now(), os.environ['HTTP_HOST']))
sys.stdout.flush()
try:
from astroquery.mast import Catalogs
except Exception as e:
print(
"<p>{} ERROR: failed to import astroquery.mast.Catalogs(): {}</p>"
.format(datetime.datetime.now(), e))
sys.stdout.flush()
raise
if debug:
print(
"<p>{} DEBUG: Successfully imported astroquery.mast.Catalogs.</p>"
.format(datetime.datetime.now()))
if debug:
import inspect, astroquery
print("<p>DEBUG: my astroquery is version {} at {}</p>".format(
astroquery.__version__, inspect.getfile(astroquery)))
sys.stdout.flush()
if debug: print("<p>DEBUGGING: Calling query_criteria</p>")
sys.stdout.flush()
try:
catalogData = Catalogs.query_criteria(catalog="Tic", ID=entry)
except Exception as e:
#print("<p>ERROR: astroquery.mast.Catalogs() error {} for string {}</p>".format(e,escape(entry,quote=True)))
print(
"<p>ERROR: astroquery.mast.Catalogs() error {} for string {}</p>".
format(e, entry))
raise
if debug:
print("<p>DEBUGGING: this Tic ID gives ra,dec={},{}</p>".format(
catalogData['ra'][0], catalogData['dec'][0]))
sys.stdout.flush()
return entry, catalogData['ra'][0], catalogData['dec'][0]
from astropy.io import ascii
import matplotlib.pyplot as plt
import pdb
from astroquery.mast import Catalogs
# take the output of sample.py and collate information required to run isoclassify
spoc = ascii.read('tess_spoc_candidates.csv')
ids = [''] * len(spoc)
band = ['kmag'] * len(spoc)
dust = ['allsky'] * len(spoc)
for i in range(0, len(spoc)):
ids[i] = 'TOI' + str(spoc['Full TOI ID'][i]).split('.')[0]
catalogData = Catalogs.query_criteria(catalog="Tic", ID=spoc['TIC'])
spoc = spoc[np.argsort(spoc['TIC'])]
catalogData = catalogData[np.argsort(np.asarray(catalogData['ID'],
dtype='int'))]
ascii.write([
ids, catalogData['ra'], catalogData['dec'], catalogData['gaiabp'],
catalogData['e_gaiabp'], catalogData['gaiarp'], catalogData['e_gaiarp'],
1. / catalogData['d'], catalogData['e_d'] / catalogData['d']**2,
catalogData['Kmag'], catalogData['e_Kmag'], band, dust, spoc['TIC']
],
'tess_spoc_candidates_isocl.csv',
delimiter=',',
names=[
'id_starname', 'ra', 'dec', 'bpmag', 'bpmag_err', 'rpmag',
plt.subplot(5, 5, nplot)
prf = getPrfAtColRowFits(col + col_add, row + row_add, ccd, camera,
sector, path)
plt.imshow(prf, **kwargs)
plt.annotate("%.1f, %.1f" % (col_add, row_add), (8, 11), color='w')
_ = kwargs.pop('vmax') #unset vmax
from astroquery.mast import Tesscut
from astroquery.mast import Catalogs
ticid = 307214209
target = "TIC %u" % ticid
size = 13
catalogData = Catalogs.query_criteria(catalog="Tic", ID=ticid)
ra = catalogData['ra']
dec = catalogData['dec']
coord = "%f, %f" % (ra, dec)
hdulist = Tesscut.get_cutouts(coord, size=size)
n = 1 # There is more than one sector, we chose the second one
# Pull out the location of the middle of the CCD from the Physics WCS in the header.
image_head = hdulist[n][1].header
prime_head = hdulist[n][0].header
ap_head = hdulist[n][2].header
col_center = image_head['1CRV4P']
row_center = image_head['2CRV4P']
print("Header col,row: %f, %f" % (col_center, row_center))
