def single_site(site='keck'):
df = get_cdips_candidates()
df.source_id = df.source_id.astype(str)
df = canddf.merge(df, on='source_id', how='left')
assert len(df) == len(canddf)
for name, ra, dec in zip(nparr(df['targetid']), nparr(df['gaia_ra']),
nparr(df['gaia_dec'])):
outdir = '../results/followup_planning/{}'.format(name)
if not os.path.exists(outdir):
os.mkdir(outdir)
make_observability_chart_singlesite(name=name,
site=site,
ra=ra,
dec=dec,
outdir=outdir,
start_time=START_TIME,
end_time=END_TIME)
def multi_site(
sites=[
'keck', 'Las Campanas Observatory', 'Kitt Peak National Observatory'
]):
"""
Campanas: PFS, PISCO
Kitt Peak: TRES(?), NEID
Keck: HIRES, Subaru
La-Palma: HARPS-N
"""
df = get_cdips_candidates()
df.source_id = df.source_id.astype(str)
df = canddf.merge(df, on='source_id', how='left')
assert len(df) == len(canddf)
for source_id, name, ra, dec in zip(CANDIDATES, nparr(df['targetid']),
nparr(df['gaia_ra']),
nparr(df['gaia_dec'])):
outdir = '../results/followup_planning/{}'.format(RUN_NAME)
if not os.path.exists(outdir):
os.mkdir(outdir)
if ra == dec == -1:
ra, dec = given_sourceid_get_radec(source_id)
print(name, ra, dec)
make_observability_chart_multisite(name=name,
sites=sites,
ra=ra,
dec=dec,
outdir=outdir,
start_time=START_TIME,
end_time=END_TIME,
save_csv=True)
print('done with {}...'.format(name))
"""
##########
# config #
##########
import numpy as np, pandas as pd
from cdips_followup.manage_ephemerides import query_ephemeris
from cdips_followup.utils import (get_cdips_candidates,
given_sourceid_get_radec)
from astroquery.gaia import Gaia
from numpy import array as nparr
from astropy.coordinates import ICRS
from astropy import units as u
df = get_cdips_candidates()
# select * where K<2 and not L contains 'SP2' and not L contains '--'
sel = ((df.current_priority < 2)
& ~(df.pending_spectroscopic_observations.str.contains('SP2'))
& ~(df.pending_spectroscopic_observations.str.contains('--')))
df = df[sel]
scols = [
'source_id', 'ticid', 'targetid', 'rp', 'period', 'tic_Vmag', 'tic_teff',
'pending_spectroscopic_observations'
]
df = df[scols]
ras, decs = [], []
for ix, source_id in enumerate(nparr(df.source_id.astype(str))):
(df_ctoi.Notes.str.contains('CG') |
df_ctoi.Notes.str.contains('Zari') |
df_ctoi.Notes.str.contains('KC') |
df_ctoi.Notes.str.contains('Nice') |
df_ctoi.Notes.str.contains('IC2602') |
df_ctoi.Notes.str.contains('Collinder135')
)
)
sdf_ctoi = df_ctoi[sel_ctoi]
#
# Get updates on them from candidate database.
#
df_cand = get_cdips_candidates()
mdf = sdf_ctoi.merge(df_cand, how='left', left_on='TIC ID', right_on='ticid')
scols = [
'TIC ID', 'CTOI', 'Promoted to TOI', 'TESS Mag', 'TESS Mag err', 'RA',
'Dec', 'Depth ppm', 'Depth ppm Error', 'Duration (hrs)', 'Duration (hrs) Error',
'Radius (R_Earth)', 'Radius (R_Earth) Error', 'Stellar Distance (pc)',
'Stellar Radius (R_Sun)', 'Stellar Radius (R_Sun) err', 'CTOI lastmod',
'User', 'Group', 'Tag', 'Notes',
'source_id', 'ticid', 'toi', 'targetid', 'iscdipstarget', 'reference',
'name', 'age', 'nbhd_rating', 'init_priority', 'current_priority',
'pending_spectroscopic_observations',
'pending_photometry_observations', 'comment', 'rp', 'rp_unc', 'period',
'gaia_ra', 'gaia_dec', 'gaia_plx', 'gaia_Gmag', 'gaia_Bmag', 'gaia_Rmag',
'tic_Bmag', 'tic_Vmag', 'tic_Jmag', 'tic_Hmag', 'tic_Kmag', 'tic_Tmag',