diff options
Diffstat (limited to 'utils/gf.py')
| -rw-r--r-- | utils/gf.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/utils/gf.py b/utils/gf.py index 766c161..99b1f24 100644 --- a/utils/gf.py +++ b/utils/gf.py @@ -15,7 +15,7 @@ from functools import partial import GolemFitPy as gf from utils.enums import * -from utils.misc import enum_keys, enum_parse +from utils.misc import enum_parse def data_distributions(fitter): @@ -81,25 +81,25 @@ def gen_steering_params(steering_categ, quiet=False): def gf_argparse(parser): parser.add_argument( '--data', default='real', type=partial(enum_parse, c=DataType), - choices=enum_keys(DataType), help='select datatype' + choices=DataType, help='select datatype' ) parser.add_argument( '--ast', default='baseline', type=partial(enum_parse, c=SteeringCateg), - choices=enum_keys(SteeringCateg), + choices=SteeringCateg, help='use asimov/fake dataset with specific steering' ) parser.add_argument( '--aft', default='hesespl', type=partial(enum_parse, c=FitCateg), - choices=enum_keys(FitCateg), + choices=FitCateg, help='use asimov/fake dataset with specific Fit' ) parser.add_argument( '--axs', default='nom', type=partial(enum_parse, c=XSCateg), - choices=enum_keys(XSCateg), + choices=XSCateg, help='use asimov/fake dataset with xs scaling' ) parser.add_argument( '--priors', default='uniform', type=partial(enum_parse, c=Priors), - choices=enum_keys(Priors), help='Bayesian priors' + choices=Priors, help='Bayesian priors' ) |