/
bhm_spiders_clusters.py
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bhm_spiders_clusters.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# @Author: Tom Dwelly
# @Date: 2020-06-17
# @Filename: bhm_spiders_clusters.py
# @License: BSD 3-clause (http://www.opensource.org/licenses/BSD-3-Clause)
# isort: skip_file
import peewee
from peewee import JOIN
from peewee import fn
from target_selection.cartons.base import BaseCarton
from target_selection.mag_flux import AB2nMgy, AB2Jy
# general catalogdb imports
from sdssdb.peewee.sdss5db.catalogdb import (
Catalog,
EROSITASupersetClusters,
)
# imports of existing spectro catalogues
from sdssdb.peewee.sdss5db.catalogdb import (
CatalogToSDSS_DR16_SpecObj,
SDSS_DR16_SpecObj,
CatalogToBHM_eFEDS_Veto,
BHM_eFEDS_Veto,
SDSSV_BOSS_SPALL,
SDSSV_BOSS_Conflist,
SDSSV_Plateholes,
SDSSV_Plateholes_Meta,
)
# additional imports required by bhm_spiders_clusters_lsdr8
from sdssdb.peewee.sdss5db.catalogdb import (
CatalogToLegacy_Survey_DR8,
Legacy_Survey_DR8,
)
# additional imports required by bhm_spiders_clusters_ps1dr2
from sdssdb.peewee.sdss5db.catalogdb import (
Panstarrs1,
CatalogToPanstarrs1, # only exists after v0.5 cross-match
)
# Details: Start here
# https://wiki.sdss.org/display/OPS/Defining+target+selection+and+cadence+algorithms
# ############################################
# ############################################
# ############################################
# ############################################
# # This file provides the following BHM cartons in v0.5:
#
# bhm_spiders_clusters_efeds_stragglers
# bhm_spiders_clusters_lsdr8
# bhm_spiders_clusters_ps1dr2
#
# ############################################
# ############################################
# ############################################
# ############################################
# Notes on how many targets to expect:
# => SELECT ero_version,xmatch_method,xmatch_version,opt_cat,count(*)
# FROM erosita_superset_clusters GROUP BY ero_version,xmatch_method,xmatch_version,opt_cat;
# ero_version | xmatch_method | xmatch_version | opt_cat | count
# --------------------------+--------------------+--------------------------+--------------+--------
# eFEDS_c001_V18C_legacy_d | EROMAPPER_LS_DR8 | grzw1_v0.3_2020-12-04 | lsdr8 | 73768
# em01_c946_201008_poscorr | EROMAPPER_LS_DR8 | grzw1_v0.3_2020-12-04 | lsdr8 | 160465
# em01_c946_201008_poscorr | EROMAPPER_PS1_DR2 | eromapper_2020-10-23 | ps1dr2 | 140808
#
#
# END PREAMBLE
# ##################################################################################
class BhmSpidersClustersLsdr8Carton(BaseCarton):
name = 'bhm_spiders_clusters_lsdr8'
category = 'science'
mapper = 'BHM'
program = 'bhm_spiders'
tile = False
instrument = 'BOSS'
inertial = True
def build_query(self, version_id, query_region=None):
c = Catalog.alias()
ls = Legacy_Survey_DR8.alias()
c2ls = CatalogToLegacy_Survey_DR8.alias()
s2020 = BHM_eFEDS_Veto.alias()
sV = SDSSV_BOSS_SPALL.alias()
xx = EROSITASupersetClusters.alias()
x = (
xx
.select(
fn.rank().over(partition_by=[xx.ero_detuid],
order_by=[xx.xmatch_metric.desc()]).alias('x_rank'),
xx.ero_detuid.alias('ero_detuid'),
xx.ls_id.alias('ls_id'),
xx.target_has_spec.alias('target_has_spec'),
)
.where(
(xx.ero_version == self.parameters['ero_version']),
(xx.xmatch_method == self.parameters['xmatch_method']),
(xx.xmatch_version == self.parameters['xmatch_version']),
(xx.opt_cat == self.parameters['opt_cat']),
(xx.xmatch_metric > self.parameters['xmatch_metric_min']),
(xx.ero_det_like > self.parameters['det_like_min']),
)
.alias('x')
)
instrument = peewee.Value(self.instrument)
inertial = peewee.Value(self.inertial).cast('bool')
fibertotflux_r_max = AB2nMgy(self.parameters['fibertotmag_r_min'])
fibertotflux_r_min = AB2nMgy(self.parameters['fibertotmag_r_max'])
fibertotflux_z_max = AB2nMgy(self.parameters['fibertotmag_z_min'])
fibertotflux_z_min = AB2nMgy(self.parameters['fibertotmag_z_max'])
fibertotflux_r_min_for_cadence1 = AB2nMgy(self.parameters['fibertotmag_r_for_cadence1'])
fibertotflux_z_min_for_cadence1 = AB2nMgy(self.parameters['fibertotmag_z_for_cadence1'])
fibertotflux_r_min_for_cadence2 = AB2nMgy(self.parameters['fibertotmag_r_for_cadence2'])
gaia_g_max_for_cadence1 = self.parameters['gaia_g_max_for_cadence1']
gaia_rp_max_for_cadence1 = self.parameters['gaia_rp_max_for_cadence1']
# flux30 = AB2nMgy(30.00)
# match_radius_spectro = self.parameters['spec_join_radius'] / 3600.0
# #########################################################################
# prepare the spectroscopy catalogues
match_radius_spectro = self.parameters['spec_join_radius'] / 3600.0
spec_sn_thresh = self.parameters['spec_sn_thresh']
spec_z_err_thresh = self.parameters['spec_z_err_thresh']
# SDSS DR16
c2s16 = CatalogToSDSS_DR16_SpecObj.alias()
ss16 = SDSS_DR16_SpecObj.alias()
s16 = (
ss16.select(
ss16.specobjid.alias('specobjid'),
)
.where(
ss16.snmedian >= spec_sn_thresh,
ss16.zwarning == 0,
ss16.zerr <= spec_z_err_thresh,
ss16.zerr > 0.0,
ss16.scienceprimary > 0,
)
.alias('s16')
)
# SDSS-IV/eFEDS March2020
c2s2020 = CatalogToBHM_eFEDS_Veto.alias()
ss2020 = BHM_eFEDS_Veto.alias()
s2020 = (
ss2020.select(
ss2020.pk.alias('pk'),
)
.where(
ss2020.sn_median_all >= spec_sn_thresh,
ss2020.zwarning == 0,
ss2020.z_err <= spec_z_err_thresh,
ss2020.z_err > 0.0,
)
.alias('s2020')
)
# SDSS-V spAll
ssV = SDSSV_BOSS_SPALL.alias()
sV = (
ssV.select(
ssV.specobjid.alias('specobjid'),
ssV.plug_ra.alias('plug_ra'),
ssV.plug_dec.alias('plug_dec'),
)
.where(
ssV.sn_median_all >= spec_sn_thresh,
ssV.zwarning == 0,
ssV.z_err <= spec_z_err_thresh,
ssV.z_err > 0.0,
ssV.specprimary > 0,
)
.alias('sV')
)
# SDSS-V plateholes - only consider plateholes that
# were drilled+shipped but that were not yet observed
ssph = SDSSV_Plateholes.alias()
ssphm = SDSSV_Plateholes_Meta.alias()
ssconf = SDSSV_BOSS_Conflist.alias()
sph = (
ssph.select(
ssph.pkey.alias('pkey'),
ssph.target_ra.alias('target_ra'),
ssph.target_dec.alias('target_dec'),
)
.join(
ssphm,
on=(ssph.yanny_uid == ssphm.yanny_uid)
)
.join(
ssconf, JOIN.LEFT_OUTER,
on=(ssphm.plateid == ssconf.plate)
)
.where(
(ssph.holetype == 'BOSS_SHARED'),
(ssph.sourcetype == 'SCI') | (ssph.sourcetype == 'STA'),
ssphm.isvalid > 0,
ssconf.plate.is_null(),
)
.alias('sph')
)
# priority is determined by target rank within cluster
# start with a priority floor value (per carton)
# then increment if any conditions are met:
priority = peewee.Case(
None,
(
(
x.c.x_rank == 1,
self.parameters['priority_floor_bcg']
),
(
x.c.x_rank > 1,
self.parameters['priority_floor_member'] +
fn.least(self.parameters['priority_levels'] - 2,
x.c.x_rank - 2)
),
),
None)
value = peewee.Case(
None,
(
(x.c.x_rank == 1, self.parameters['value_bcg']),
(x.c.x_rank > 1, self.parameters['value_member']),
),
None).cast('float')
# choose cadence based on fiber magnitude in r-band
cadence1 = self.parameters['cadence1']
cadence2 = self.parameters['cadence2']
cadence3 = self.parameters['cadence3']
cadence4 = 'unknown_cadence' # catch failures
cadence = peewee.Case(
None,
(
(
((ls.fibertotflux_r > fibertotflux_r_min_for_cadence1) |
(ls.fibertotflux_z > fibertotflux_z_min_for_cadence1) |
(ls.gaia_phot_g_mean_mag.between(0.1, gaia_g_max_for_cadence1)) |
(ls.gaia_phot_rp_mean_mag.between(0.1, gaia_rp_max_for_cadence1))),
cadence1),
(ls.fibertotflux_r > fibertotflux_r_min_for_cadence2, cadence2),
(ls.fibertotflux_r <= fibertotflux_r_min_for_cadence2, cadence3),
),
cadence4)
# compute transformed SDSS mags for pointlike and extended sources uniformly
# transform the legacysurvey grz into sdss psfmag griz
# extract coeffs from fit logs via:
# awk 'BEGIN {print("coeffs = {")} /POLYFIT/{ if($3~/sdss_psfmag/){pe="p"} else if ($3~/sdss_fiber2mag/){pe="e"} else{pe="error"}; printf("\"%s%d_%s\": %s,\n", substr($3,length($3)), $8, pe, $10)} END {print("}")}' bhm_spiders_clusters_lsdr8/lsdr8_fibermag_to_sdss_fiber2mag_?_results.log # noqa
coeffs = {
"g2_e": -0.897719,
"g1_e": 2.298300,
"g0_e": -1.019299,
"i2_e": -0.950114,
"i1_e": 0.981972,
"i0_e": -0.261645,
"r2_e": -0.201741,
"r1_e": 0.697128,
"r0_e": -0.120926,
"z2_e": -1.424312,
"z1_e": 2.415301,
"z0_e": -0.677163,
}
nMgy_min = 1e-3 # equiv to AB=30
# extended - start from ls8 fiberfluxes
g0_e = (22.5 - 2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_g)))
r0_e = (22.5 - 2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_r)))
z0_e = (22.5 - 2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_z)))
g_r_e = (-2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_g) /
peewee.fn.greatest(nMgy_min, ls.fiberflux_r)))
r_z_e = (-2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_r) /
peewee.fn.greatest(nMgy_min, ls.fiberflux_z)))
g_e = (g0_e + coeffs['g0_e'] + coeffs['g1_e'] * g_r_e + coeffs['g2_e'] * g_r_e * g_r_e)
r_e = (r0_e + coeffs['r0_e'] + coeffs['r1_e'] * g_r_e + coeffs['r2_e'] * g_r_e * g_r_e)
i_e = (r0_e + coeffs['i0_e'] + coeffs['i1_e'] * r_z_e + coeffs['i2_e'] * r_z_e * r_z_e)
z_e = (z0_e + coeffs['z0_e'] + coeffs['z1_e'] * r_z_e + coeffs['z2_e'] * r_z_e * r_z_e)
# validity checks
valid = (g0_e.between(0.1, 29.9) &
r0_e.between(0.1, 29.9) &
z0_e.between(0.1, 29.9))
opt_prov = peewee.Case(None, ((valid, 'sdss_fiber2mag_from_lsdr8'),), 'undefined')
magnitude_g = peewee.Case(None, ((valid, g_e),), 'NaN')
magnitude_r = peewee.Case(None, ((valid, r_e),), 'NaN')
magnitude_i = peewee.Case(None, ((valid, i_e),), 'NaN')
magnitude_z = peewee.Case(None, ((valid, z_e),), 'NaN')
magnitude_gaia_g = peewee.Case(
None,
((ls.gaia_phot_g_mean_mag.between(0.1, 29.9), ls.gaia_phot_g_mean_mag),),
'NaN')
magnitude_gaia_bp = peewee.Case(
None,
((ls.gaia_phot_bp_mean_mag.between(0.1, 29.9), ls.gaia_phot_bp_mean_mag),),
'NaN')
magnitude_gaia_rp = peewee.Case(
None,
((ls.gaia_phot_rp_mean_mag.between(0.1, 29.9), ls.gaia_phot_rp_mean_mag),),
'NaN')
# # We want to switch between psfmags and fibertotmags depending on
# # ls.type parameter (PSF or extended)
# # For 'PSF' targets, we use psfmags, but for extended sources use fiber2mags
# opt_prov = peewee.Case(
# ls.type,
# (('PSF', 'ls_psfmag'),),
# 'ls_fibertotmag')
#
# magnitude_g = peewee.Case(
# ls.type,
# (('PSF', (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.flux_g))).cast('float')),),
# (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.fibertotflux_g))).cast('float'))
#
# magnitude_r = peewee.Case(
# ls.type,
# (('PSF', (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.flux_r))).cast('float')),),
# (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.fibertotflux_r))).cast('float'))
#
# magnitude_z = peewee.Case(
# ls.type,
# (('PSF', (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.flux_z))).cast('float')),),
# (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.fibertotflux_z))).cast('float'))
#
# magnitude_i = peewee.Case(
# ls.type,
# (('PSF',
# (22.5 - 2.5 * fn.log10(
# fn.greatest(flux30, 0.5 * (ls.flux_r + ls.flux_z)))).cast('float')),),
# (22.5 - 2.5 * fn.log10(
# fn.greatest(flux30, 0.5 * (ls.fibertotflux_r +
# ls.fibertotflux_z)))).cast('float'))
spec_sn_thresh = self.parameters['spec_sn_thresh']
spec_z_err_thresh = self.parameters['spec_z_err_thresh']
query = (
c.select(
c.catalogid.alias('catalogid'),
ls.ls_id.alias('ls_id'), # extra
x.c.ero_detuid.cast('text').alias('ero_detuid'), # extra
c.ra.alias('ra'), # extra
c.dec.alias('dec'), # extra
priority.alias('priority'),
value.alias('value'),
cadence.alias('cadence'),
instrument.alias('instrument'),
opt_prov.alias('optical_prov'),
magnitude_g.alias('g'),
magnitude_r.alias('r'),
magnitude_i.alias('i'),
magnitude_z.alias('z'),
magnitude_gaia_g.alias('gaia_g'),
magnitude_gaia_bp.alias('bp'),
magnitude_gaia_rp.alias('rp'),
inertial.alias('inertial'),
g0_e.alias('ls8_fibermag_g'), # extra
r0_e.alias('ls8_fibermag_r'), # extra
z0_e.alias('ls8_fibermag_z'), # extra
)
.join(c2ls)
.join(ls)
.join(x, on=(ls.ls_id == x.c.ls_id))
# start joining the spectroscopy
.switch(c)
.join(c2s16, JOIN.LEFT_OUTER)
.join(
s16, JOIN.LEFT_OUTER,
on=(
(c2s16.target_id == s16.c.specobjid) &
(c2s16.version_id == version_id)
)
)
.switch(c)
.join(c2s2020, JOIN.LEFT_OUTER)
.join(
s2020, JOIN.LEFT_OUTER,
on=(
(c2s2020.target_id == s2020.c.pk) &
(c2s2020.version_id == version_id)
)
)
.join(
sV, JOIN.LEFT_OUTER,
on=(
fn.q3c_join(sV.c.plug_ra, sV.c.plug_dec,
c.ra, c.dec,
match_radius_spectro)
)
)
.join(
sph, JOIN.LEFT_OUTER,
on=(
fn.q3c_join(sph.c.target_ra, sph.c.target_dec,
c.ra, c.dec,
match_radius_spectro)
)
)
# finished joining the spectroscopy
.where(
c.version_id == version_id,
c2ls.version_id == version_id,
c2ls.best >> True
)
.where(
s16.c.specobjid.is_null(True), # all of these must be satisfied
s2020.c.pk.is_null(True),
sV.c.specobjid.is_null(True),
sph.c.pkey.is_null(True),
)
.where(
(
(ls.fibertotflux_r.between(fibertotflux_r_min, fibertotflux_r_max)) |
(ls.fibertotflux_z.between(fibertotflux_z_min, fibertotflux_z_max))
),
(x.c.target_has_spec == 0),
# gaia safety checks to avoid bad ls photometry
~(ls.gaia_phot_g_mean_mag.between(0.1, self.parameters['gaia_g_mag_limit'])),
~(ls.gaia_phot_rp_mean_mag.between(0.1, self.parameters['gaia_rp_mag_limit'])),
)
)
if query_region:
query = query.where(peewee.fn.q3c_radial_query(c.ra, c.dec,
query_region[0],
query_region[1],
query_region[2]))
return query
#
# END BhmSpidersClustersLsdr8Carton
# ##################################################################################
class BhmSpidersClustersEfedsStragglersCarton(BaseCarton):
name = 'bhm_spiders_clusters_efeds_stragglers'
category = 'science'
mapper = 'BHM'
program = 'bhm_spiders'
tile = False
instrument = 'BOSS'
inertial = True
def build_query(self, version_id, query_region=None):
c = Catalog.alias()
ls = Legacy_Survey_DR8.alias()
c2ls = CatalogToLegacy_Survey_DR8.alias()
# s2020 = BHM_eFEDS_Veto.alias()
# sV = SDSSV_BOSS_SPALL.alias()
# ph = SDSSV_Plateholes.alias()
# phm = SDSSV_Plateholes_Meta.alias()
xx = EROSITASupersetClusters.alias()
x = (
xx
.select(
fn.rank().over(partition_by=[xx.ero_detuid],
order_by=[xx.xmatch_metric.desc()]).alias('x_rank'),
xx.ero_detuid.alias('ero_detuid'),
xx.ls_id.alias('ls_id'),
xx.target_has_spec.alias('target_has_spec'),
)
.where(
(xx.ero_version == self.parameters['ero_version']),
(xx.xmatch_method == self.parameters['xmatch_method']),
(xx.xmatch_version == self.parameters['xmatch_version']),
(xx.opt_cat == self.parameters['opt_cat']),
(xx.xmatch_metric > self.parameters['xmatch_metric_min']),
(xx.ero_det_like > self.parameters['det_like_min']),
)
.alias('x')
)
instrument = peewee.Value(self.instrument)
inertial = peewee.Value(self.inertial).cast('bool')
fibertotflux_r_max = AB2nMgy(self.parameters['fibertotmag_r_min'])
fibertotflux_r_min = AB2nMgy(self.parameters['fibertotmag_r_max'])
fibertotflux_z_max = AB2nMgy(self.parameters['fibertotmag_z_min'])
fibertotflux_z_min = AB2nMgy(self.parameters['fibertotmag_z_max'])
fibertotflux_r_min_for_cadence1 = AB2nMgy(self.parameters['fibertotmag_r_for_cadence1'])
fibertotflux_z_min_for_cadence1 = AB2nMgy(self.parameters['fibertotmag_z_for_cadence1'])
fibertotflux_r_min_for_cadence2 = AB2nMgy(self.parameters['fibertotmag_r_for_cadence2'])
gaia_g_max_for_cadence1 = self.parameters['gaia_g_max_for_cadence1']
gaia_rp_max_for_cadence1 = self.parameters['gaia_rp_max_for_cadence1']
# flux30 = AB2nMgy(30.00)
# #########################################################################
# prepare the spectroscopy catalogues
match_radius_spectro = self.parameters['spec_join_radius'] / 3600.0
spec_sn_thresh = self.parameters['spec_sn_thresh']
spec_z_err_thresh = self.parameters['spec_z_err_thresh']
# SDSS DR16
c2s16 = CatalogToSDSS_DR16_SpecObj.alias()
ss16 = SDSS_DR16_SpecObj.alias()
s16 = (
ss16.select(
ss16.specobjid.alias('specobjid'),
)
.where(
ss16.snmedian >= spec_sn_thresh,
ss16.zwarning == 0,
ss16.zerr <= spec_z_err_thresh,
ss16.zerr > 0.0,
ss16.scienceprimary > 0,
)
.alias('s16')
)
# SDSS-IV/eFEDS March2020
c2s2020 = CatalogToBHM_eFEDS_Veto.alias()
ss2020 = BHM_eFEDS_Veto.alias()
s2020 = (
ss2020.select(
ss2020.pk.alias('pk'),
)
.where(
ss2020.sn_median_all >= spec_sn_thresh,
ss2020.zwarning == 0,
ss2020.z_err <= spec_z_err_thresh,
ss2020.z_err > 0.0,
)
.alias('s2020')
)
# SDSS-V spAll
ssV = SDSSV_BOSS_SPALL.alias()
sV = (
ssV.select(
ssV.specobjid.alias('specobjid'),
ssV.plug_ra.alias('plug_ra'),
ssV.plug_dec.alias('plug_dec'),
)
.where(
ssV.sn_median_all >= spec_sn_thresh,
ssV.zwarning == 0,
ssV.z_err <= spec_z_err_thresh,
ssV.z_err > 0.0,
ssV.specprimary > 0,
)
.alias('sV')
)
# All eFEDS plates have been observed so ignore plateholes now
# # SDSS-V plateholes - only consider plateholes that
# # were drilled+shipped but that were not yet observed
# ssph = SDSSV_Plateholes.alias()
# ssphm = SDSSV_Plateholes_Meta.alias()
# ssconf = SDSSV_BOSS_Conflist.alias()
# sph = (
# ssph.select(
# ssph.pkey.alias('pkey'),
# ssph.target_ra.alias('target_ra'),
# ssph.target_dec.alias('target_dec'),
# )
# .join(
# ssphm,
# on=(ssph.yanny_uid == ssphm.yanny_uid)
# )
# .join(
# ssconf, JOIN.LEFT_OUTER,
# on=(ssphm.plateid == ssconf.plate)
# )
# .where(
# (ssph.holetype == 'BOSS_SHARED'),
# (ssph.sourcetype == 'SCI') | (ssph.sourcetype == 'STA'),
# ssphm.isvalid > 0,
# ssconf.plate.is_null(),
# )
# .alias('sph')
# )
# priority is determined by target rank within cluster
# start with a priority floor value (per carton)
# then increment if any conditions are met:
priority = peewee.Case(
None,
(
(
x.c.x_rank == 1,
self.parameters['priority_floor_bcg']
),
(
x.c.x_rank > 1,
self.parameters['priority_floor_member'] +
fn.least(self.parameters['priority_levels'] - 2,
x.c.x_rank - 2)
),
),
None)
value = peewee.Case(
None,
(
(x.c.x_rank == 1, self.parameters['value_bcg']),
(x.c.x_rank > 1, self.parameters['value_member']),
),
None).cast('float')
# choose cadence based on fiber magnitude in r-band
cadence1 = self.parameters['cadence1']
cadence2 = self.parameters['cadence2']
cadence3 = self.parameters['cadence3']
cadence4 = 'unknown_cadence' # catch failures
cadence = peewee.Case(
None,
(
(
((ls.fibertotflux_r > fibertotflux_r_min_for_cadence1) |
(ls.fibertotflux_z > fibertotflux_z_min_for_cadence1) |
(ls.gaia_phot_g_mean_mag.between(0.1, gaia_g_max_for_cadence1)) |
(ls.gaia_phot_rp_mean_mag.between(0.1, gaia_rp_max_for_cadence1))),
cadence1),
(ls.fibertotflux_r > fibertotflux_r_min_for_cadence2, cadence2),
(ls.fibertotflux_r <= fibertotflux_r_min_for_cadence2, cadence3),
),
cadence4)
# compute transformed SDSS mags for pointlike and extended sources separately
# transform the legacysurvey grz into sdss psfmag griz
# copy of routine for bhm_spiders_clusters_lsdr8
coeffs = {
"g2_e": -0.897719,
"g1_e": 2.298300,
"g0_e": -1.019299,
"i2_e": -0.950114,
"i1_e": 0.981972,
"i0_e": -0.261645,
"r2_e": -0.201741,
"r1_e": 0.697128,
"r0_e": -0.120926,
"z2_e": -1.424312,
"z1_e": 2.415301,
"z0_e": -0.677163,
}
nMgy_min = 1e-3 # equiv to AB=30
# extended - start from ls8 fiberfluxes
g0_e = (22.5 - 2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_g)))
r0_e = (22.5 - 2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_r)))
z0_e = (22.5 - 2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_z)))
g_r_e = (-2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_g) /
peewee.fn.greatest(nMgy_min, ls.fiberflux_r)))
r_z_e = (-2.5 * peewee.fn.log(peewee.fn.greatest(nMgy_min, ls.fiberflux_r) /
peewee.fn.greatest(nMgy_min, ls.fiberflux_z)))
g_e = (g0_e + coeffs['g0_e'] + coeffs['g1_e'] * g_r_e + coeffs['g2_e'] * g_r_e * g_r_e)
r_e = (r0_e + coeffs['r0_e'] + coeffs['r1_e'] * g_r_e + coeffs['r2_e'] * g_r_e * g_r_e)
i_e = (r0_e + coeffs['i0_e'] + coeffs['i1_e'] * r_z_e + coeffs['i2_e'] * r_z_e * r_z_e)
z_e = (z0_e + coeffs['z0_e'] + coeffs['z1_e'] * r_z_e + coeffs['z2_e'] * r_z_e * r_z_e)
# validity checks
valid = (g0_e.between(0.1, 29.9) &
r0_e.between(0.1, 29.9) &
z0_e.between(0.1, 29.9))
opt_prov = peewee.Case(None, ((valid, 'sdss_fiber2mag_from_lsdr8'),), 'undefined')
magnitude_g = peewee.Case(None, ((valid, g_e),), 'NaN')
magnitude_r = peewee.Case(None, ((valid, r_e),), 'NaN')
magnitude_i = peewee.Case(None, ((valid, i_e),), 'NaN')
magnitude_z = peewee.Case(None, ((valid, z_e),), 'NaN')
# # We want to switch between psfmags and fibertotmags depending on
# # ls.type parameter (PSF or extended)
# # For 'PSF' targets, we use psfmags, but for extended sources use fiber2mags
# opt_prov = peewee.Case(
# ls.type,
# (('PSF', 'ls_psfmag'),),
# 'ls_fibertotmag')
#
# magnitude_g = peewee.Case(
# ls.type,
# (('PSF', (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.flux_g))).cast('float')),),
# (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.fibertotflux_g))).cast('float'))
#
# magnitude_r = peewee.Case(
# ls.type,
# (('PSF', (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.flux_r))).cast('float')),),
# (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.fibertotflux_r))).cast('float'))
#
# magnitude_z = peewee.Case(
# ls.type,
# (('PSF', (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.flux_z))).cast('float')),),
# (22.5 - 2.5 * fn.log10(fn.greatest(flux30, ls.fibertotflux_z))).cast('float'))
#
# magnitude_i = peewee.Case(
# ls.type,
# (('PSF',
# (22.5 - 2.5 * fn.log10(
# fn.greatest(flux30, 0.5 * (ls.flux_r + ls.flux_z)))).cast('float')),),
# (22.5 - 2.5 * fn.log10(
# fn.greatest(flux30, 0.5 * (ls.fibertotflux_r +
# ls.fibertotflux_z)))).cast('float'))
spec_sn_thresh = self.parameters['spec_sn_thresh']
spec_z_err_thresh = self.parameters['spec_z_err_thresh']
query = (
c.select(
c.catalogid.alias('catalogid'),
ls.ls_id.alias('ls_id'), # extra
x.c.ero_detuid.cast('text').alias('ero_detuid'), # extra
c.ra.alias('ra'), # extra
c.dec.alias('dec'), # extra
priority.alias('priority'),
value.alias('value'),
cadence.alias('cadence'),
instrument.alias('instrument'),
opt_prov.alias('optical_prov'),
magnitude_g.alias('g'),
magnitude_r.alias('r'),
magnitude_i.alias('i'),
magnitude_z.alias('z'),
ls.gaia_phot_g_mean_mag.alias('gaia_g'),
ls.gaia_phot_bp_mean_mag.alias('bp'),
ls.gaia_phot_rp_mean_mag.alias('rp'),
inertial.alias('inertial'),
g0_e.alias('ls8_fibermag_g'), # extra
r0_e.alias('ls8_fibermag_r'), # extra
z0_e.alias('ls8_fibermag_z'), # extra
)
.join(c2ls)
.join(ls)
.join(x, on=(ls.ls_id == x.c.ls_id))
# start joining the spectroscopy
.switch(c)
.join(c2s16, JOIN.LEFT_OUTER)
.join(
s16, JOIN.LEFT_OUTER,
on=(
(c2s16.target_id == s16.c.specobjid) &
(c2s16.version_id == version_id)
)
)
.switch(c)
.join(c2s2020, JOIN.LEFT_OUTER)
.join(
s2020, JOIN.LEFT_OUTER,
on=(
(c2s2020.target_id == s2020.c.pk) &
(c2s2020.version_id == version_id)
)
)
.join(
sV, JOIN.LEFT_OUTER,
on=(
fn.q3c_join(sV.c.plug_ra, sV.c.plug_dec,
c.ra, c.dec,
match_radius_spectro)
)
)
# .join(
# sph, JOIN.LEFT_OUTER,
# on=(
# fn.q3c_join(sph.c.target_ra, sph.c.target_dec,
# c.ra, c.dec,
# match_radius_spectro)
# )
# )
# finished joining the spectroscopy
.where(
c.version_id == version_id,
c2ls.version_id == version_id,
c2ls.best >> True
)
.where(
s16.c.specobjid.is_null(True), # all of these must be satisfied
s2020.c.pk.is_null(True),
sV.c.specobjid.is_null(True),
# sph.c.pkey.is_null(True),
)
.where(
(
(ls.fibertotflux_r.between(fibertotflux_r_min, fibertotflux_r_max)) |
(ls.fibertotflux_z.between(fibertotflux_z_min, fibertotflux_z_max))
),
(x.c.target_has_spec == 0),
# gaia safety checks to avoid bad ls photometry
~(ls.gaia_phot_g_mean_mag.between(0.1, self.parameters['gaia_g_mag_limit'])),
~(ls.gaia_phot_rp_mean_mag.between(0.1, self.parameters['gaia_rp_mag_limit'])),
)
)
if query_region:
query = query.where(peewee.fn.q3c_radial_query(c.ra, c.dec,
query_region[0],
query_region[1],
query_region[2]))
return query
#
# END BhmSpidersClustersEfedsStragglersCarton
# ##################################################################################
class BhmSpidersClustersPs1dr2Carton(BaseCarton):
name = 'bhm_spiders_clusters_ps1dr2'
category = 'science'
mapper = 'BHM'
program = 'bhm_spiders'
tile = False
instrument = 'BOSS'
inertial = True
def build_query(self, version_id, query_region=None):
c = Catalog.alias()
ps = Panstarrs1.alias()
c2ps = CatalogToPanstarrs1.alias() # only exists after v0.5 cross-match
# s2020 = BHM_eFEDS_Veto.alias()
# sV = SDSSV_BOSS_SPALL.alias()
xx = EROSITASupersetClusters.alias()
x = (
xx
.select(
fn.rank().over(partition_by=[xx.ero_detuid],
order_by=[xx.xmatch_metric.desc()]).alias('x_rank'),
xx.ero_detuid.alias('ero_detuid'),
xx.ps1_dr2_id.alias('ps1_dr2_id'),
xx.target_has_spec.alias('target_has_spec'),
)
.where(
(xx.ero_version == self.parameters['ero_version']),
(xx.xmatch_method == self.parameters['xmatch_method']),
(xx.xmatch_version == self.parameters['xmatch_version']),
(xx.opt_cat == self.parameters['opt_cat']),
(xx.xmatch_metric > self.parameters['xmatch_metric_min']),
(xx.ero_det_like > self.parameters['det_like_min']),
)
.alias('x')
)
instrument = peewee.Value(self.instrument)
inertial = peewee.Value(self.inertial).cast('bool')
r_psf_flux_max = AB2Jy(self.parameters['r_psf_mag_min'])
i_psf_flux_max = AB2Jy(self.parameters['i_psf_mag_min'])
z_psf_flux_max = AB2Jy(self.parameters['z_psf_mag_min'])
r_psf_flux_min_for_cadence1 = AB2Jy(self.parameters['r_psf_mag_max_for_cadence1'])
i_psf_flux_min_for_cadence1 = AB2Jy(self.parameters['i_psf_mag_max_for_cadence1'])
z_psf_flux_min_for_cadence1 = AB2Jy(self.parameters['z_psf_mag_max_for_cadence1'])
r_psf_flux_min_for_cadence2 = AB2Jy(self.parameters['r_psf_mag_max_for_cadence2'])
i_psf_flux_min_for_cadence2 = AB2Jy(self.parameters['i_psf_mag_max_for_cadence2'])
z_psf_flux_min_for_cadence2 = AB2Jy(self.parameters['z_psf_mag_max_for_cadence2'])
# match_radius_spectro = self.parameters['spec_join_radius'] / 3600.0
# #########################################################################
# prepare the spectroscopy catalogues
match_radius_spectro = self.parameters['spec_join_radius'] / 3600.0
spec_sn_thresh = self.parameters['spec_sn_thresh']
spec_z_err_thresh = self.parameters['spec_z_err_thresh']
# SDSS DR16
c2s16 = CatalogToSDSS_DR16_SpecObj.alias()
ss16 = SDSS_DR16_SpecObj.alias()
s16 = (
ss16.select(
ss16.specobjid.alias('specobjid'),
)
.where(
ss16.snmedian >= spec_sn_thresh,
ss16.zwarning == 0,
ss16.zerr <= spec_z_err_thresh,
ss16.zerr > 0.0,
ss16.scienceprimary > 0,
)
.alias('s16')
)
# SDSS-IV/eFEDS March2020
c2s2020 = CatalogToBHM_eFEDS_Veto.alias()
ss2020 = BHM_eFEDS_Veto.alias()
s2020 = (
ss2020.select(
ss2020.pk.alias('pk'),
)
.where(
ss2020.sn_median_all >= spec_sn_thresh,
ss2020.zwarning == 0,
ss2020.z_err <= spec_z_err_thresh,
ss2020.z_err > 0.0,
)
.alias('s2020')
)
# SDSS-V spAll
ssV = SDSSV_BOSS_SPALL.alias()
sV = (
ssV.select(
ssV.specobjid.alias('specobjid'),
ssV.plug_ra.alias('plug_ra'),
ssV.plug_dec.alias('plug_dec'),
)
.where(
ssV.sn_median_all >= spec_sn_thresh,
ssV.zwarning == 0,
ssV.z_err <= spec_z_err_thresh,
ssV.z_err > 0.0,
ssV.specprimary > 0,
)
.alias('sV')
)
# SDSS-V plateholes - only consider plateholes that
# were drilled+shipped but that were not yet observed
ssph = SDSSV_Plateholes.alias()
ssphm = SDSSV_Plateholes_Meta.alias()
ssconf = SDSSV_BOSS_Conflist.alias()
sph = (
ssph.select(
ssph.pkey.alias('pkey'),
ssph.target_ra.alias('target_ra'),
ssph.target_dec.alias('target_dec'),
)
.join(
ssphm,
on=(ssph.yanny_uid == ssphm.yanny_uid)
)
.join(
ssconf, JOIN.LEFT_OUTER,
on=(ssphm.plateid == ssconf.plate)
)
.where(
(ssph.holetype == 'BOSS_SHARED'),
(ssph.sourcetype == 'SCI') | (ssph.sourcetype == 'STA'),
ssphm.isvalid > 0,
ssconf.plate.is_null(),
)
.alias('sph')
)
# priority is determined by target rank within cluster
# start with a priority floor value (per carton)
# then increment if any conditions are met:
priority = peewee.Case(
None,
(
(
x.c.x_rank == 1,
self.parameters['priority_floor_bcg']
),
(
x.c.x_rank > 1,
self.parameters['priority_floor_member'] +
fn.least(self.parameters['priority_levels'] - 2,
x.c.x_rank - 2)
),
),
None)
value = peewee.Case(
None,
(
(x.c.x_rank == 1, self.parameters['value_bcg']),
(x.c.x_rank > 1, self.parameters['value_member']),
),
None)