diff options
Diffstat (limited to 'fr.py')
| -rwxr-xr-x | fr.py | 250 |
1 files changed, 0 insertions, 250 deletions
@@ -1,250 +0,0 @@ -#! /usr/bin/env python -# author : S. Mandalia -# s.p.mandalia@qmul.ac.uk -# -# date : March 17, 2018 - -""" -HESE BSM flavour ratio MCMC analysis script -""" - -from __future__ import absolute_import, division - -import os -import argparse -from functools import partial - -import numpy as np - -from utils import fr as fr_utils -from utils import gf as gf_utils -from utils import llh as llh_utils -from utils import mcmc as mcmc_utils -from utils import misc as misc_utils -from utils import plot as plot_utils -from utils.enums import DataType, Likelihood, MCMCSeedType -from utils.enums import ParamTag, PriorsCateg, Texture -from utils.param import Param, ParamSet - - -def define_nuisance(): - """Define the nuisance parameters.""" - tag = ParamTag.SM_ANGLES - nuisance = [] - g_prior = PriorsCateg.GAUSSIAN - lg_prior = PriorsCateg.LIMITEDGAUSS - e = 1e-9 - nuisance.extend([ - Param(name='s_12_2', value=0.307, seed=[0.26, 0.35], ranges=[0., 1.], std=0.013, tex=r's_{12}^2', prior=lg_prior, tag=tag), - Param(name='c_13_4', value=(1-(0.02206))**2, seed=[0.950, 0.961], ranges=[0., 1.], std=0.00147, tex=r'c_{13}^4', prior=lg_prior, tag=tag), - Param(name='s_23_2', value=0.538, seed=[0.31, 0.75], ranges=[0., 1.], std=0.069, tex=r's_{23}^2', prior=lg_prior, tag=tag), - Param(name='dcp', value=4.08404, seed=[0+e, 2*np.pi-e], ranges=[0., 2*np.pi], std=2.0, tex=r'\delta_{CP}', tag=tag), - Param( - name='m21_2', value=7.40E-23, seed=[7.2E-23, 7.6E-23], ranges=[6.80E-23, 8.02E-23], - std=2.1E-24, tex=r'\Delta m_{21}^2{\rm GeV}^{-2}', prior=g_prior, tag=tag - ), - Param( - name='m3x_2', value=2.494E-21, seed=[2.46E-21, 2.53E-21], ranges=[2.399E-21, 2.593E-21], - std=3.3E-23, tex=r'\Delta m_{3x}^2{\rm GeV}^{-2}', prior=g_prior, tag=tag - ) - ]) - tag = ParamTag.NUISANCE - nuisance.extend([ - Param(name='convNorm', value=1., seed=[0.5, 2. ], ranges=[0.1, 10.], std=0.4, prior=lg_prior, tag=tag), - Param(name='promptNorm', value=0., seed=[0. , 6. ], ranges=[0. , 20.], std=2.4, prior=lg_prior, tag=tag), - Param(name='muonNorm', value=1., seed=[0.1, 2. ], ranges=[0. , 10.], std=0.1, tag=tag), - Param(name='astroNorm', value=6.9, seed=[0., 5. ], ranges=[0. , 20.], std=1.5, tag=tag), - Param(name='astroDeltaGamma', value=2.5, seed=[2.4, 3. ], ranges=[-5., 5. ], std=0.1, tag=tag) - ]) - return ParamSet(nuisance) - - -def get_paramsets(args, nuisance_paramset): - """Make the paramsets for generating the Asmimov MC sample and also running - the MCMC. - """ - asimov_paramset = [] - llh_paramset = [] - - gf_nuisance = [x for x in nuisance_paramset.from_tag(ParamTag.NUISANCE)] - - llh_paramset.extend( - [x for x in nuisance_paramset.from_tag(ParamTag.SM_ANGLES)] - ) - llh_paramset.extend(gf_nuisance) - - for parm in llh_paramset: - parm.value = args.__getattribute__(parm.name) - - boundaries = fr_utils.SCALE_BOUNDARIES[args.dimension] - tag = ParamTag.SCALE - llh_paramset.append( - Param( - name='logLam', value=np.mean(boundaries), ranges=boundaries, std=3, - tex=r'{\rm log}_{10}\left (\Lambda^{-1}' + \ - misc_utils.get_units(args.dimension)+r'\right )', - tag=tag - ) - ) - llh_paramset = ParamSet(llh_paramset) - - tag = ParamTag.BESTFIT - if args.data is not DataType.REAL: - flavour_angles = fr_utils.fr_to_angles(args.injected_ratio) - else: - flavour_angles = fr_utils.fr_to_angles([1, 1, 1]) - - asimov_paramset.extend(gf_nuisance) - asimov_paramset.extend([ - Param(name='astroFlavorAngle1', value=flavour_angles[0], ranges=[ 0., 1.], std=0.2, tag=tag), - Param(name='astroFlavorAngle2', value=flavour_angles[1], ranges=[-1., 1.], std=0.2, tag=tag), - ]) - asimov_paramset = ParamSet(asimov_paramset) - - return asimov_paramset, llh_paramset - - -def nuisance_argparse(parser): - nuisance = define_nuisance() - for parm in nuisance: - parser.add_argument( - '--'+parm.name, type=float, default=parm.value, - help=parm.name+' to inject' - ) - - -def process_args(args): - """Process the input args.""" - args.source_ratio = fr_utils.normalise_fr(args.source_ratio) - if args.data is not DataType.REAL: - args.injected_ratio = fr_utils.normalise_fr(args.injected_ratio) - - args.binning = np.logspace( - np.log10(args.binning[0]), np.log10(args.binning[1]), args.binning[2]+1 - ) - - args.likelihood = Likelihood.GOLEMFIT - - args.mcmc_threads = misc_utils.thread_factors(args.threads)[1] - args.threads = misc_utils.thread_factors(args.threads)[0] - - if args.texture is Texture.NONE: - raise ValueError('Must assume a BSM texture') - - -def parse_args(args=None): - """Parse command line arguments""" - parser = argparse.ArgumentParser( - description="BSM flavour ratio analysis", - formatter_class=misc_utils.SortingHelpFormatter, - ) - parser.add_argument( - '--seed', type=misc_utils.seed_parse, default='25', - help='Set the random seed value' - ) - parser.add_argument( - '--threads', type=misc_utils.thread_type, default='1', - help='Set the number of threads to use (int or "max")' - ) - parser.add_argument( - '--datadir', type=str, default='./untitled', - help='Path to store chains' - ) - fr_utils.fr_argparse(parser) - gf_utils.gf_argparse(parser) - llh_utils.llh_argparse(parser) - mcmc_utils.mcmc_argparse(parser) - nuisance_argparse(parser) - if args is None: return parser.parse_args() - else: return parser.parse_args(args.split()) - - -def main(): - args = parse_args() - process_args(args) - misc_utils.print_args(args) - - if args.seed is not None: - np.random.seed(args.seed) - - asimov_paramset, llh_paramset = get_paramsets(args, define_nuisance()) - outfile = args.datadir + '/{0}/{1}/chains_'.format( - *map(misc_utils.parse_enum, [args.stat_method, args.data]) - ) + misc_utils.gen_identifier(args) - print '== {0:<25} = {1}'.format('outfile', outfile) - - if args.run_mcmc: - gf_utils.setup_fitter(args, asimov_paramset) - - print 'asimov_paramset', asimov_paramset - print 'llh_paramset', llh_paramset - - ln_prob = partial( - llh_utils.ln_prob, - args=args, - asimov_paramset=asimov_paramset, - llh_paramset=llh_paramset - ) - - if args.mcmc_seed_type == MCMCSeedType.UNIFORM: - p0 = mcmc_utils.flat_seed( - llh_paramset, nwalkers=args.nwalkers - ) - elif args.mcmc_seed_type == MCMCSeedType.GAUSSIAN: - p0 = mcmc_utils.gaussian_seed( - llh_paramset, nwalkers=args.nwalkers - ) - - samples = mcmc_utils.mcmc( - p0 = p0, - ln_prob = ln_prob, - ndim = len(llh_paramset), - nwalkers = args.nwalkers, - burnin = args.burnin, - nsteps = args.nsteps, - args = args, - threads = args.mcmc_threads - ) - mcmc_utils.save_chains(samples, outfile) - - raw = np.load(outfile+'.npy') - raw[:,4] *= 1E23 - raw[:,5] *= 1E21 - ranges = list(llh_paramset.ranges) - ranges[4] = [x*1E23 for x in ranges[4]] - ranges[5] = [x*1E21 for x in ranges[5]] - - labels = [ - r'${\rm sin}^2\theta_{12}$', - r'${\rm cos}^4\theta_{13}$', - r'${\rm sin}^2\theta_{23}$', - r'$\delta$', - r'$\Delta m_{21}^2\left[10^{-5}\,{\rm eV}^2\right]$', - r'$\Delta m_{31}^2\left[10^{-3}\,{\rm eV}^2\right]$', - r'$N_{\rm conv}$', - r'$N_{\rm prompt}$', - r'$N_{\rm muon}$', - r'$N_{\rm astro}$', - r'$\gamma_{\rm astro}$', - r'${\rm log}_{10}\left[\Lambda^{-1}_{'+ \ - r'{0}'.format(args.dimension)+r'}'+ \ - misc_utils.get_units(args.dimension)+r'\right]$' - ] - - plot_utils.chainer_plot( - infile = raw, - outfile = outfile[:5]+outfile[5:].replace('data', 'plots'), - outformat = ['pdf'], - args = args, - llh_paramset = llh_paramset, - labels = labels, - ranges = ranges - ) - print "DONE!" - - -main.__doc__ = __doc__ - - -if __name__ == '__main__': - main() |