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-#! /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 copy import deepcopy
-from functools import partial
-
-import numpy as np
-
-from utils import fr as fr_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 MCMCSeedType, ParamTag, PriorsCateg
-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', 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', 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', 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),
- ])
- 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 = []
- hypo_paramset = []
-
- hypo_paramset.extend(
- [x for x in nuisance_paramset.from_tag(ParamTag.SM_ANGLES)]
- )
-
- for parm in hypo_paramset:
- parm.value = args.__getattribute__(parm.name)
-
- hypo_paramset = ParamSet(hypo_paramset)
-
- tag = ParamTag.BESTFIT
- flavour_angles = fr_utils.fr_to_angles(args.injected_ratio)
-
- 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, hypo_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.injected_ratio = fr_utils.normalise_fr(args.injected_ratio)
-
-
-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(
- '--injected-ratio', type=float, nargs=3, default=[1, 2, 0],
- help='Set the central value for the injected flavour ratio at source'
- )
- parser.add_argument(
- '--seed', type=misc_utils.seed_parse, default='26',
- 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'
- )
- mcmc_utils.mcmc_argparse(parser)
- nuisance_argparse(parser)
- if args is None: return parser.parse_args()
- else: return parser.parse_args(args.split())
-
-
-def gen_identifier(args):
- f = '_INJ_{0}'.format(misc_utils.solve_ratio(args.injected_ratio))
- return f
-
-
-def gen_figtext(args, asimov_paramset):
- f = ''
- f += 'Injected ratio = {0}'.format(
- misc_utils.solve_ratio(args.injected_ratio)
- )
- for param in asimov_paramset:
- f += '\nInjected {0:20s} = {1:.3f}'.format(
- param.name, param.nominal_value
- )
- return f
-
-
-def triangle_llh(theta, args, hypo_paramset):
- """Log likelihood function for a given theta."""
- if len(theta) != len(hypo_paramset):
- raise AssertionError(
- 'Dimensions of scan is not the same as the input '
- 'params\ntheta={0}\nparamset]{1}'.format(theta, hypo_paramset)
- )
- for idx, param in enumerate(hypo_paramset):
- param.value = theta[idx]
-
- return 1. # Flat LLH
-
-
-def ln_prob(theta, args, hypo_paramset):
- dc_hypo_paramset = deepcopy(hypo_paramset)
- lp = llh_utils.lnprior(theta, paramset=dc_hypo_paramset)
- if not np.isfinite(lp):
- return -np.inf
- return lp + triangle_llh(
- theta,
- args = args,
- hypo_paramset = dc_hypo_paramset,
- )
-
-
-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, hypo_paramset = get_paramsets(args, define_nuisance())
-
- prefix = ''
- outfile = args.datadir + '/fr' + prefix + gen_identifier(args)
- print '== {0:<25} = {1}'.format('outfile', outfile)
-
- print 'asimov_paramset', asimov_paramset
- print 'hypo_paramset', hypo_paramset
-
- if args.run_mcmc:
- ln_prob_eval = partial(
- ln_prob,
- hypo_paramset = hypo_paramset,
- args = args,
- )
-
- if args.mcmc_seed_type == MCMCSeedType.UNIFORM:
- p0 = mcmc_utils.flat_seed(
- hypo_paramset, nwalkers=args.nwalkers
- )
- elif args.mcmc_seed_type == MCMCSeedType.GAUSSIAN:
- p0 = mcmc_utils.gaussian_seed(
- hypo_paramset, nwalkers=args.nwalkers
- )
-
- samples = mcmc_utils.mcmc(
- p0 = p0,
- ln_prob = ln_prob_eval,
- ndim = len(hypo_paramset),
- nwalkers = args.nwalkers,
- burnin = args.burnin,
- nsteps = args.nsteps,
- args = args,
- threads = args.threads
- )
-
- mmxs = map(fr_utils.angles_to_u, samples)
- frs = np.array(
- [fr_utils.u_to_fr(args.injected_ratio, x) for x in mmxs]
- )
- mcmc_utils.save_chains(frs, outfile)
-
- of = outfile[:5]+outfile[5:].replace('data', 'plots')+'_posterior'
- plot_utils.chainer_plot(
- infile = outfile+'.npy',
- outfile = of,
- outformat = ['png'],
- args = args,
- llh_paramset = hypo_paramset,
- fig_text = gen_figtext(args, hypo_paramset)
- )
-
- print "DONE!"
-
-
-main.__doc__ = __doc__
-
-
-if __name__ == '__main__':
- main()