diff options
| -rwxr-xr-x | fr.py | 2 | ||||
| -rw-r--r-- | submitter/make_dag.py | 2 | ||||
| -rw-r--r-- | utils/likelihood.py | 4 | ||||
| -rw-r--r-- | utils/plot.py | 18 |
4 files changed, 13 insertions, 13 deletions
@@ -157,7 +157,7 @@ def parse_args(): help='Spectral index for spectral energy dependance' ) parser.add_argument( - '--binning', default=[4, 7, 50], type=int, nargs=3, + '--binning', default=[1e4, 1e7, 10], type=int, nargs=3, help='Binning for spectral energy dependance' ) parser.add_argument( diff --git a/submitter/make_dag.py b/submitter/make_dag.py index 216ca72..80bd751 100644 --- a/submitter/make_dag.py +++ b/submitter/make_dag.py @@ -48,7 +48,7 @@ scale = "1E-20 1E-30" scale_region = "1E10" energy_dependance = 'spectral' spectral_index = -2 -binning = [4, 7, 51] +binning = [1e4, 1e7, 10] # Likelihood likelihood = 'golemfit' diff --git a/utils/likelihood.py b/utils/likelihood.py index f590200..8057896 100644 --- a/utils/likelihood.py +++ b/utils/likelihood.py @@ -19,7 +19,7 @@ import GolemFitPy as gf from utils import fr as fr_utils from utils import gf as gf_utils -from utils.enums import Likelihood, ParamTag +from utils.enums import EnergyDependance, Likelihood, ParamTag from utils.misc import enum_parse @@ -68,7 +68,7 @@ def triangle_llh(theta, args, asimov_paramset, mcmc_paramset, fitter): source_flux = args.source_ratio elif args.energy_dependance is EnergyDependance.SPECTRAL: source_flux = np.array( - [fr * np.power(bin_centers, SPECTRAL_INDEX) + [fr * np.power(bin_centers, args.spectral_index) for fr in args.source_ratio] ).T else: diff --git a/utils/plot.py b/utils/plot.py index 87a6f5c..af713eb 100644 --- a/utils/plot.py +++ b/utils/plot.py @@ -21,7 +21,7 @@ from getdist import plots from getdist import mcsamples from utils import misc as misc_utils -from utils.enums import Likelihood, ParamTag +from utils.enums import EnergyDependance, Likelihood, ParamTag from utils.fr import angles_to_u, angles_to_fr rc('text', usetex=False) @@ -112,38 +112,38 @@ def gen_figtext(args): if args.fix_scale: t += 'Source flavour ratio = [{0:.2f}, {1:.2f}, {2:.2f}]\nIC ' \ 'observed flavour ratio = [{3:.2f}, {4:.2f}, ' \ - '{5:.2f}]\nDimension = {7}\nScale = {9}'.format( + '{5:.2f}]\nDimension = {6}\nScale = {7}'.format( sr1, sr2, sr3, mr1, mr2, mr3, args.dimension, int(args.energy), args.scale ) else: t += 'Source flavour ratio = [{0:.2f}, {1:.2f}, {2:.2f}]\nIC ' \ 'observed flavour ratio = [{3:.2f}, {4:.2f}, ' \ - '{5:.2f}]\nDimension = {7}'.format( + '{5:.2f}]\nDimension = {6}'.format( sr1, sr2, sr3, mr1, mr2, mr3, args.dimension, int(args.energy) ) else: if args.fix_scale: t += 'IC observed flavour ratio = [{0:.2f}, {1:.2f}, ' \ - '{2:.2f}]\nDimension = {4}\nScale = {6}'.format( + '{2:.2f}]\nDimension = {3}\nScale = {4}'.format( mr1, mr2, mr3, args.dimension, int(args.energy), args.scale ) else: t += 'IC observed flavour ratio = [{0:.2f}, {1:.2f}, ' \ - '{2:.2f}]\nDimension = {4}'.format( + '{2:.2f}]\nDimension = {3}'.format( mr1, mr2, mr3, args.dimension, int(args.energy) ) if args.likelihood is Likelihood.GAUSSIAN: t += '\nSigma = {0:.3f}'.format(args.sigma_ratio) if args.energy_dependance is EnergyDependance.SPECTRAL: - t += '\nSpectral Index = {0}\nBinning = [{7}, {8}] GeV - {9} bins'.format( - int(args.spectral_index), int(10**args.binning[0]), - int(10**args.binning[1]), int(args.binning[2]) + t += '\nSpectral Index = {0}\nBinning = [{1}, {2}] TeV - {3} bins'.format( + int(args.spectral_index), int(args.binning[0]/1e3), + int(args.binning[-1]/1e3), len(args.binning)-1 ) elif args.energy_dependance is EnergyDependance.MONO: - t += '\nEnergy = {0} GeV'.format(args.energy) + t += '\nEnergy = {0} TeV'.format(int(args.energy/1e3)) return t |