bug fixes

3 files changed, 11 insertions, 14 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'
     )
 
diff --git a/utils/mcmc.py b/utils/mcmc.py
index aebe12f..995a338 100644
--- a/utils/mcmc.py
+++ b/utils/mcmc.py
@@ -18,9 +18,11 @@ import tqdm
 import numpy as np
 from scipy.stats import multivariate_normal
 
+import GolemFitPy as gf
+
 from utils import fr as fr_utils
 from utils.enums import Likelihood
-from utils.misc import enum_keys, enum_parse, make_dir, parse_bool
+from utils.misc import enum_parse, make_dir, parse_bool
 
 
 def lnprior(theta, paramset):
@@ -65,7 +67,7 @@ def mcmc(p0, triangle_llh, lnprior, ndim, nwalkers, burnin, nsteps, ntemps=1, th
 def mcmc_argparse(parser):
     parser.add_argument(
         '--likelihood', default='gaussian', type=partial(enum_parse, c=Likelihood),
-        choices=enum_keys(Likelihood), help='likelihood contour'
+        choices=Likelihood, help='likelihood contour'
     )
     parser.add_argument(
         '--run-mcmc', type=parse_bool, default='True',
@@ -137,14 +139,13 @@ def triangle_llh(theta, args):
     )
 
     fr = fr_utils.u_to_fr((fr1, fr2, fr3), u)
-    fr_bf = args.measured_ratio
     if args.likelihood is Likelihood.FLAT:
         return 1.
     elif args.likelihood is Likelihood.GAUSSIAN:
+        fr_bf = args.measured_ratio
         return gaussian_llh(fr, fr_bf, args.sigma_ratio)
     elif args.likelihood is Likelihood.GOLEMFIT:
         raise NotImplementedError('TODO')
-        import GolemFitPy as gf
         from collections import namedtuple
         datapaths = gf.DataPaths()
         IceModels = namedtuple('IceModels', 'std_half2')
diff --git a/utils/misc.py b/utils/misc.py
index 2ff0664..108a458 100644
--- a/utils/misc.py
+++ b/utils/misc.py
@@ -252,10 +252,6 @@ def print_args(args):
         print '== {0:<25} = {1}'.format(key, arg_vars[key])
 
 
-def enum_keys(e):
-    return e.__members__.keys()
-
-
 def enum_parse(s, c):
     return c[s.upper()]