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',