diff --git a/py/desisim/scripts/gen_qso_catalog.py b/py/desisim/scripts/gen_qso_catalog.py index 5e57a902..5cba093d 100644 --- a/py/desisim/scripts/gen_qso_catalog.py +++ b/py/desisim/scripts/gen_qso_catalog.py @@ -24,6 +24,12 @@ def main(): parser.add_argument("--exptime", type=float, default=None, required=False, help='Exposure time to assign to all targets in the mock catalog') + + parser.add_argument("--zmin", type=float, default=1.7, required=False, + help='Minimum redshift') + + parser.add_argument("--zmax", type=float, default=10.0, required=False, + help='Maximum redshift') parser.add_argument("--release", type=str, default='jura', choices=['iron','jura','Y5'], required=False, help='DESI survey release to reproduce') @@ -47,7 +53,7 @@ def main(): # Note: For Y1 and Y3 mocks (and probably Y5 too) the target selection redshift distribution # from Chaussidon et al. 2022 works better to match QSO targets Iron catalog. # The option distribution='from_data' should be a better option once I finish implementing it. - survey.apply_redshift_dist(distribution='target_selection', zmin=1.8) + survey.apply_redshift_dist(distribution='target_selection', zmin=args.zmin, zmax=args.zmax) # Apply NPASS geometry either from a release or a custom tiles file. survey.apply_data_geometry(release=args.release, tilefile=args.tiles_file) diff --git a/py/desisim/survey_release.py b/py/desisim/survey_release.py index de3bf0dc..b3936c75 100644 --- a/py/desisim/survey_release.py +++ b/py/desisim/survey_release.py @@ -296,7 +296,6 @@ def assign_exposures(self,exptime=None): log.warning('Effective exposure time TSNR2_LRG column not found in observed data catalog.') log.warning('Will compute effective exposure time from alternative templates.') if 'TSNR2_LYA' in self.data.colnames: - log.warning('TSNR2_LRG column not found in observed data catalog.') log.info('Getting effective exposure time in data catalog by 11.8*TSNR2_LYA.') exptime_data = 11.8*self.data['TSNR2_LYA'] elif 'TSNR2_QSO' in self.data.colnames: