diff options
Diffstat (limited to 'utils/plot.py')
| -rw-r--r-- | utils/plot.py | 82 |
1 files changed, 56 insertions, 26 deletions
diff --git a/utils/plot.py b/utils/plot.py index b63126b..4dd8cc4 100644 --- a/utils/plot.py +++ b/utils/plot.py @@ -13,6 +13,8 @@ import os from copy import deepcopy import numpy as np +from scipy import interpolate + import matplotlib as mpl mpl.use('Agg') from matplotlib import rc @@ -27,7 +29,7 @@ from utils.enums import Likelihood, ParamTag, StatCateg from utils.fr import angles_to_u, angles_to_fr rc('text', usetex=False) -rc('font', **{'family':'serif', 'serif':['Computer Modern'], 'size':18}) +rc('font', **{'family':'serif', 'serif':['DejaVu Sans'], 'size':18}) def centers(x): @@ -117,17 +119,18 @@ def gen_figtext(args): mr1, mr2, mr3 = misc_utils.solve_ratio(args.measured_ratio) if args.fix_source_ratio: sr1, sr2, sr3 = misc_utils.solve_ratio(args.source_ratio) - t += 'Source flavour ratio = [{0}, {1}, {2}]\nIC ' \ - 'observed flavour ratio = [{3}, {4}, ' \ - '{5}]\nDimension = {6}'.format( - sr1, sr2, sr3, mr1, mr2, mr3, args.dimension, - int(args.energy) - ) + t += 'Source flavour ratio = [{0}, {1}, {2}]'.format(sr1, sr2, sr3) + if args.data is DataType.ASIMOV: + t += '\nIC observed flavour ratio = [{0}, {1}, {2}]'.format( + mr1, mr2, mr3 + ) + t += '\nDimension = {0}'.format(args.dimension) else: - t += 'IC observed flavour ratio = [{0}, {1}, ' \ - '{2}]\nDimension = {3}'.format( - mr1, mr2, mr3, args.dimension, int(args.energy) - ) + if args.data is DataType.ASIMOV: + t += 'IC observed flavour ratio = [{0}, {1}, ' \ + '{2}]\nDimension = {3}'.format( + mr1, mr2, mr3, args.dimension, int(args.energy) + ) if args.fix_scale: t += 'Scale = {0}'.format(args.scale) if args.likelihood is Likelihood.GAUSSIAN: @@ -231,7 +234,7 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset): g.export(outfile+'_elements.'+of) -def myround(x, base=1, up=False, down=False): +def myround(x, base=2, up=False, down=False): if up == down and up is True: assert 0 if up: return int(base * np.round(float(x)/base-0.5)) elif down: return int(base * np.round(float(x)/base+0.5)) @@ -241,12 +244,17 @@ def myround(x, base=1, up=False, down=False): def plot_statistic(data, outfile, outformat, args, scale_param, label=None): """Make MultiNest factor or LLH value plot.""" print 'Making Statistic plot' - fig_text = gen_figtext(args) + fig_text = '\n' + gen_figtext(args) if label is not None: fig_text += '\n' + label print 'data', data print 'data.shape', data.shape scales, statistic = data.T + tck, u = interpolate.splprep([scales, statistic], s=0) + scales, statistic = interpolate.splev(np.linspace(0, 1, 1000), tck) + print 'scales', scales + print 'statistic', statistic + min_idx = np.argmin(scales) null = statistic[min_idx] if args.stat_method is StatCateg.BAYESIAN: @@ -258,21 +266,31 @@ def plot_statistic(data, outfile, outformat, args, scale_param, label=None): ax = fig.add_subplot(111) ax.set_xlim(np.log10(args.scale_region)) - ax.set_xlabel('$'+scale_param.tex+'$') + ax.set_xlabel(r'${\mathrm {log}}_{10} \left (\Lambda^{-1}' + \ + get_units(args.dimension) +r'\right )$', fontsize=16) if args.stat_method is StatCateg.BAYESIAN: - ax.set_ylabel(r'Bayes Factor') + ax.set_ylabel(r'log(Bayes Factor)') elif args.stat_method is StatCateg.FREQUENTIST: ax.set_ylabel(r'$-2\Delta {\rm LLH}$') ax.plot(scales, reduced_ev) + ax.axhline(y=np.log(10**(3/2.)), color='red', alpha=1., linewidth=1.3) + for ymaj in ax.yaxis.get_majorticklocs(): ax.axhline(y=ymaj, ls=':', color='gray', alpha=0.3, linewidth=1) for xmaj in ax.xaxis.get_majorticklocs(): ax.axvline(x=xmaj, ls=':', color='gray', alpha=0.3, linewidth=1) + if args.data is DataType.REAL: + fig.text(0.8, 0.14, 'IceCube Preliminary', color='red', fontsize=9, + ha='center', va='center') + elif args.data is DataType.ASIMOV: + fig.text(0.8, 0.14, 'IceCube Simulation', color='red', fontsize=9, + ha='center', va='center') + at = AnchoredText( - fig_text, prop=dict(size=10), frameon=True, loc=2 + fig_text, prop=dict(size=10), frameon=True, loc=4 ) at.patch.set_boxstyle("round,pad=0.1,rounding_size=0.5") ax.add_artist(at) @@ -374,9 +392,13 @@ def plot_sens_fixed_angle(data, outfile, outformat, args): fig = plt.figure(figsize=(7, 5)) ax = fig.add_subplot(111) ax.set_xlim(0, len(xticks)+1) - ax.set_xticklabels([''] + xticks + ['']) - ax.set_xlabel(r'BSM operator angle') - ax.set_ylabel(r'${\rm log}_{10} \left (\Lambda^{-1}' + get_units(dim) +r'\right )$') + ax.set_xticklabels([''] + xticks + [''], fontsize=14) + ax.set_xlabel(r'BSM operator angle', fontsize=16) + ax.set_ylabel(r'${\mathrm {log}}_{10} \left (\Lambda^{-1}' + \ + get_units(dim) +r'\right )$', fontsize=16) + + # ax.tick_params(axis='x', labelsize=11) + ax.tick_params(axis='y', labelsize=14) for isrc in xrange(len(data[idim])): src = args.source_ratios[isrc] @@ -386,6 +408,8 @@ def plot_sens_fixed_angle(data, outfile, outformat, args): for ian in xrange(len(data[idim][isrc])): print '=== an', ian scales, statistic = data[idim][isrc][ian].T + tck, u = interpolate.splprep([scales, statistic], s=0) + scales, statistic = interpolate.splev(np.linspace(0, 1, 1000), tck) min_idx = np.argmin(scales) null = statistic[min_idx] if args.stat_method is StatCateg.BAYESIAN: @@ -400,24 +424,30 @@ def plot_sens_fixed_angle(data, outfile, outformat, args): dim, src, reduced_ev ) continue + if reduced_ev[-1] < np.log(10**(3/2.)) - 0.1: + print 'Peaked contour does not exclude large scales! For ' \ + 'DIM {0} FRS{1} reduced_ev {2}!'.format( + dim, src, reduced_ev + ) + continue arr_len = dim-2 lim = al[0] print 'limit = {0}'.format(lim) label = '{0} : {1} : {2}'.format(*misc_utils.solve_ratio(src)) - if lim < yranges[0]: yranges[0] = lim + if lim < yranges[0]: yranges[0] = lim-arr_len if lim > yranges[1]: yranges[1] = lim+arr_len+2 # if lim > yranges[1]: yranges[1] = lim xoff = 0.15 line = plt.Line2D( - (ian+1-xoff, ian+1+xoff), (lim, lim), lw=2., color=colour[isrc], label=label + (ian+1-xoff, ian+1+xoff), (lim, lim), lw=2.5, color=colour[isrc], label=label ) ax.add_line(line) if len(legend_handles) < isrc+1: legend_handles.append(line) x_offset = isrc*xoff/2. - xoff/2. ax.annotate( - s='', xy=(ian+1+x_offset, lim-0.01), xytext=(ian+1+x_offset, lim+arr_len), - arrowprops={'arrowstyle': '<-', 'lw': 2., 'color':colour[isrc]} + s='', xy=(ian+1+x_offset, lim-0.02), xytext=(ian+1+x_offset, lim+arr_len), + arrowprops={'arrowstyle': '<-', 'lw': 1.5, 'color':colour[isrc]} ) try: @@ -438,14 +468,14 @@ def plot_sens_fixed_angle(data, outfile, outformat, args): at.patch.set_boxstyle("round,pad=0.1,rounding_size=0.5") ax.add_artist(at) - fig.text(0.42, 0.8, 'Excluded', color='red', fontsize=20, ha='center', + fig.text(0.42, 0.8, r'Excluded', color='red', fontsize=16, ha='center', va='center', fontweight='bold') if args.data is DataType.REAL: - fig.text(0.805, 0.14, 'IceCube Preliminary', color='red', fontsize=11, + fig.text(0.805, 0.14, 'IceCube Preliminary', color='red', fontsize=9, ha='center', va='center') elif args.data is DataType.ASIMOV: - fig.text(0.805, 0.14, 'IceCube Simulation', color='red', fontsize=11, + fig.text(0.805, 0.14, 'IceCube Simulation', color='red', fontsize=9, ha='center', va='center') for ymaj in ax.yaxis.get_majorticklocs(): |