diff options
Diffstat (limited to 'sens.py')
| -rwxr-xr-x | sens.py | 48 |
1 files changed, 30 insertions, 18 deletions
@@ -14,6 +14,8 @@ import os import argparse from functools import partial +import glob + import numpy as np import numpy.ma as ma from scipy.optimize import minimize @@ -216,35 +218,45 @@ def main(): print '|||| SCALE = {0:.0E}'.format(np.power(10, scale)) # Lower scale boundary for first (NULL) point and set the scale param. + reset_range = None if scale < scale_prm.ranges[0]: + reset_range = scale_prm.ranges scale_prm.ranges = (scale, scale_prm.ranges[1]) scale_prm.value = scale - if args.stat_method is StatCateg.BAYESIAN: - identifier = 'b{0}_{1}_{2}_sca{3}'.format( - args.eval_segment, args.segments, str_enum(args.texture), scale + identifier = 'b{0}_{1}_{2}_sca{3}'.format( + args.eval_segment, args.segments, str_enum(args.texture), scale + ) + llh = '{0}'.format(args.likelihood).split('.')[1] + data = '{0}'.format(args.data).split('.')[1] + src_string = solve_ratio(args.source_ratio) + prefix = args.mn_output + '/DIM{0}/{1}/{2}/s{3}/{4}'.format( + args.dimension, data, llh, src_string, identifier + ) + try: + stat = mn_utils.mn_evidence( + mn_paramset = base_mn_pset, + llh_paramset = llh_paramset, + asimov_paramset = asimov_paramset, + args = args, + prefix = prefix ) - try: - stat = mn_utils.mn_evidence( - mn_paramset = base_mn_pset, - llh_paramset = llh_paramset, - asimov_paramset = asimov_paramset, - args = args, - identifier = identifier - ) - except: - print 'Failed run' - raise - # continue - print '## Evidence = {0}'.format(stat) - elif args.stat_method is StatCateg.FREQUENTIST: - raise NotImplementedError('Still needs testing') + except: + print 'Failed run' + raise + print '## Evidence = {0}'.format(stat) if args.eval_segment is not None: stat_arr[0] = np.array([scale, stat]) else: stat_arr[idx_sc] = np.array([scale, stat]) + # Cleanup. + for f in glob.glob(prefix + '*'): + os.remove(f) + if reset_range is not None: + scale_prm.ranges = reset_range + misc_utils.make_dir(outfile) print 'Saving to {0}'.format(outfile+'.npy') np.save(outfile+'.npy', stat_arr) |