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Diffstat (limited to 'scripts/fr.py')
| -rwxr-xr-x | scripts/fr.py | 250 |
1 files changed, 250 insertions, 0 deletions
diff --git a/scripts/fr.py b/scripts/fr.py new file mode 100755 index 0000000..9802b55 --- /dev/null +++ b/scripts/fr.py @@ -0,0 +1,250 @@ +#! /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() |