'''Given a folder with an OccurrenceRateclass object, get all the planet

candidates from orion and with human dispositions, so that they can be

added to the list of planet candidates.'''

# get the results object

#self = loadpickle('%s/TIC_results_0_10000_det'%folder)

assert hasattr(self, 'tics')

assert hasattr(self, 'disposition_human')

# isolate planet candidates, putative PCs, and single transits

g01 = np.in1d(self.disposition_human, [0,1]) # PCs and pPCs

g2 = np.in1d(self.disposition_human , [2,2.5]) # STs and pSTs

g = (g01 + g2).astype(bool)

assert g.sum() == g01.sum() + g2.sum()

# get each TIC's sectors

sector_dict = get_sectors(self.tics[g])

# get columns of interest

# TIC,sectors,ra,dec,Tmag,Jmag,Hmag,Kmag,dist,Ms,Rs,Teff,P,T0,rp/Rs,rp,disp

outstr = '#TIC,sectors,ra,dec,Tmag,Jmag,Hmag,Kmag,dist,Ms,Rs,Teff,P,T0,rp/Rs,rp,disposition\n'

for i in np.where(g)[0]:

outstr += '%i;%s;%.5f;%.5f;'%(self.tics[i], sector_dict[self.tics[i]],

self.ras[i], self.decs[i])

outstr += '%.3f;%.3f;%.3f;%.3f;'%(self.TESSmags[i], self.Jmags[i],

self.Hmags[i], self.Kmags[i])

outstr += '%.3f;%.3f;%.3f;%i;'%(self.dists[i], self.Mss[i],

self.Rss[i], self.Teffs[i])

if self.disposition_human[i] < 2:

p, rpRs, rp = self.Ps[i], self.rpRss[i], self.rps[i]

elif self.disposition_human[i] >= 2:

p = self.Ps_singletransit[i]

rpRs = self.rpRs_singletransit[i]

rp = self.rps_singletransit[i]

else:

raise ValueError('disposition %.1f is not valid.'%self.disposition_human[i])

outstr += '%.6f;%.6f;%.5f;%.2f;%s\n'%(p, self.T0s[i], rpRs, rp,

get_disposition(self.disposition_human[i]))

'''Given a folder with an OccurrenceRateclass object, get all the planet

candidates from orion with human dispositions and create a list of CTOIs using the

CTOI format from ExoFOP

(https://exofop.ipac.caltech.edu/tess/templates/params_planet_YYYYMMDD_001.txt)'''

assert hasattr(self, 'tics')

assert hasattr(self, 'disposition_human')

assert np.all(np.in1d(fname_index, np.arange(1,1e3,dtype=int)))

# isolate planet candidates, putative PCs, and single transits

g1 = np.in1d(self.disposition_human, [1]) # PCs and pPCs

g2 = np.in1d(self.disposition_human , [2]) # STs and pSTs

g = (g1 + g2).astype(bool)

assert g.sum() == g1.sum() + g2.sum()

# get string

date = datetime.datetime.now()

date_str = '%.4d%.2d%.2d'%(date.year, date.month, date.day)

print '\nBe sure to update the list of TOIs and CTOIs from https://exofop.ipac.caltech.edu/tess/\n'

# get columns of interest including uncertainties (NaNs where appropriate)

# TIC,flag,disp,P,T0,Z,D,inc,b,rp/Rs,a/Rs,rp,mp,Teq,S,rho_star,sma,ecc,omega,tau_peri,K_RV,tag,group,prop_P,notes

# for definitions see ORION_PCs/ctoi_header.txt

f = open('ORION_PCs/ctoi_header.txt', 'r')

outstr = f.read()

f.close()

for i in np.where(g)[0]:

# check if potential CTOIs are already a TOI or a CTOI

if (not is_TOI(self.tics[i])) and (not is_CTOI(self.tics[i])):

print 'TIC %i: possible new CTOI'%self.tics[i]

# get multiple transit parameters

if self.disposition_human[i] < 2:

P, eP = self.Ps[i], self.e_Ps[i]

inc, einc = self.incs[i], np.mean([self.ehi_incs[i],self.elo_incs[i]])

rpRs, erpRs = self.rpRss[i], np.mean([self.ehi_rpRss[i],self.elo_rpRss[i]])

aRs, eaRs = self.aRss[i], np.mean([self.ehi_aRss[i],self.elo_aRss[i]])

rp, erp = self.rps[i], np.mean([self.ehi_rps[i],self.elo_rps[i]])

sma, esma = self.smas[i], np.mean([self.ehi_smas[i],self.elo_smas[i]])

notes = 'new CTOI from ORION (https://arxiv.org/abs/1812.08145)'

# get single transit parameters

elif self.disposition_human[i] >= 2:

P, eP = np.nan, np.nan#self.Ps_singletransit[i], np.mean([self.ehi_Ps_singletransit[i],self.elo_Ps_singletransit[i]])

inc, einc = self.inc_singletransit[i], np.mean([self.ehi_inc_singletransit[i],self.elo_inc_singletransit[i]])

rpRs, erpRs = self.rpRs_singletransit[i], np.mean([self.ehi_rpRs_singletransit[i],self.elo_rpRs_singletransit[i]])

aRs, eaRs = self.aRs_singletransit[i], np.mean([self.ehi_aRs_singletransit[i],self.elo_aRs_singletransit[i]])

rp, erp = self.rps_singletransit[i], np.mean([self.ehi_rps_singletransit[i],self.elo_rps_singletransit[i]])

#sampMs = np.random.randn(1000)*self.ehi_Mss[i] + self.Mss[i]

#_,_,sampP = get_samples_from_percentiles(P, self.ehi_Ps_singletransit[i], self.elo_Ps_singletransit[i])

#sampsma = rvs.semimajoraxis(sampP, sampMs, 0)

#v = np.percentile(sampsma, (16,50,84))

sma, esma = np.nan, np.nan#rvs.semimajoraxis(P, self.Mss[i], 0), np.mean([v[2]-v[1], v[1]-v[0]])

notes = 'new single transit CTOI from ORION (https://arxiv.org/abs/1812.08145)'

else:

raise ValueError('disposition %.1f is not valid.'%self.disposition_human[i])

# get other planet params

T0, eT0 = self.T0s[i], self.e_T0s[i]

Z, eZ = self.depths[i], unp.std_devs(unp.uarray(rpRs,erpRs)**2)

ub = rvs.impactparam_inc_aRs(unp.uarray(aRs,eaRs), unp.uarray(inc,einc))

uD = rvs.transit_width_aRs(unp.uarray(P,eP), unp.uarray(aRs,eaRs), unp.uarray(Z,eZ), ub)

uTeq = unp.uarray(self.Teffs[i],self.ehi_Teffs[i]) * unp.sqrt(rvs.Rsun2m(unp.uarray(self.Rss[i],self.ehi_Rss[i])) \

/ rvs.AU2m(2*unp.uarray(sma,esma)))

uS = unp.uarray(self.Rss[i],self.ehi_Rss[i])**2 * (unp.uarray(self.Teffs[i],self.ehi_Teffs[i])/5777)**4 * (1./unp.uarray(sma,esma))**2

D, eD = unp.nominal_values(uD), unp.std_devs(uD)

b, eb = unp.nominal_values(ub), unp.std_devs(ub)

Teq, eTeq = unp.nominal_values(uTeq), unp.std_devs(uTeq)

S, eS = unp.nominal_values(uS), unp.std_devs(uS)

# add ancillary stuff

flag, disp = 'newctoi', 'PC'

tag = '%s_cloutier_orion_%.5d'%(date_str, fname_index)

group, prop_P = '', 0

# add planet parameters

outstr += 'TIC%i.01|%s|%s|'%(self.tics[i], flag, disp)

outstr += '%.6f|%.6f|%.5f|%.5f|'%(P, eP, T0, eT0)

outstr += '%.1f|%.1f|%.3f|%.3f|%.2f|%.2f|'%(Z, eZ, D, eD, inc, einc)

outstr += '%.3f|%.3f|%.4f|%.4f|%.1f|%.1f|'%(b, eb, rpRs, erpRs, aRs, eaRs)

outstr += '%.2f|%.2f|%.2f|%.2f|%.1f|%.1f|'%(rp, erp, np.nan, np.nan, Teq, eTeq)

outstr += '%.1f|%.1f|%.2f|%.2f|%.4f|%.4f|'%(S, eS, np.nan, np.nan, sma, esma)

outstr += '%.2f|%.2f|%.2f|%.2f|%.2f|%.2f|'%(0, 0, np.nan, np.nan, np.nan, np.nan)

outstr += '%.2f|%.2f|'%(np.nan, np.nan)

outstr += '%s|%s|%i|%s\n'%(tag, group, prop_P, notes)

else:

if is_TOI(self.tics[i]): print 'TIC %i: already a TOI'%self.tics[i]

if is_CTOI(self.tics[i]): print 'TIC %i: already a CTOI'%self.tics[i]

# replace NaNs

outstr = outstr.replace('nan','')

# remind me to check stuff:

# TIC name is not a duplicate

# TO is correct for single transit events

warnings.warn('\nThe parameters here (e.g. T0 for single transits) should be confirmed by-eye.')

# save file

fname_out = 'ORION_PCs/params_planet_%s_%.3d.txt'%(date_str, fname_index)

f = open(fname_out, 'w')

f.write(outstr)

f.close()

'''check if the input TIC is already a TOI. The up-to-date list of TOIs can be downloaded from

list https://exofop.ipac.caltech.edu/tess/index.php'''

# get published list of all TOIs

toi_tics = np.loadtxt('ORION_PCs/exofop_tess_tois.csv', delimiter=',', skiprows=3, usecols=(0),

dtype='|S50')

# check if the input tic is in the list of tois

'''check if the input TIC is already a CTOI. The up-to-date list of CTOIs can be downloaded from

list https://exofop.ipac.caltech.edu/tess/index.php'''

# get published list of all CTOIs

ctoi_tics, users = np.loadtxt('ORION_PCs/exofop_tess_ctois.csv', delimiter=',', skiprows=3,

usecols=(0,41), dtype='|S50').T

# check if the input tic is in the list of ctois and is not one of my own CTOIs

if '"%s"'%tic in ctoi_tics:

return users[ctoi_tics == '"%s"'%tic] != '"cloutier"'

else:

'''Given a list of TICs, read-in the individual TESS sector targets lists

and identify which sector the TIC was observed in.'''

# get mapping between tics and sectors

fs = np.array(glob.glob('input_data/TESStargets/all_targets_S*'))

tics_tot, sectors_tot = np.zeros(0), np.zeros(0)

for f in fs:

if '.txt' in f:

tics_thissector = np.loadtxt(f)[:,0]

elif '.csv' in f:

tics_thissector = np.loadtxt(f, delimiter=',', skiprows=6)[:,0]

else:

raise ValueError('Cannot read this file: %s'%f)

# map tics to their sector

tics_tot = np.append(tics_tot, tics_thissector)

sect = int(f.split('_')[-2].split('S')[1])

sectors_tot = np.append(sectors_tot,

np.repeat(sect, tics_thissector.size))

# save each tic's sector(s)

assert tics_tot.size == sectors_tot.size

sector_dict = {}

for tic in tics:

sector_dict[tic] = str(list(np.unique(sectors_tot[np.in1d(tics_tot,tic)]).astype(int))).replace(' ','')

'''Map the disposition to a str'''

if disposition_num == 0:

return 'pPC'

elif disposition_num == 1:

return 'PC'

elif disposition_num == 2:

return 'ST'

elif disposition_num == 2.5:

return 'pST'

else:

'''Append the PCs in the input planet string to the master list of planet

candidates from all sectors.'''

# get file to append to

fname = 'orion_PCs.txt'

f = open(fname, 'r')

g = f.read()

f.close()

# append

f = open(fname, 'w')

f.write(g + ''.join(planet_str.split('disposition\n')[1:])) # removes the hdr