diff options
Diffstat (limited to 'utils/plot.py')
| -rw-r--r-- | utils/plot.py | 113 |
1 files changed, 112 insertions, 1 deletions
diff --git a/utils/plot.py b/utils/plot.py index 4c5ff1c..4180eb3 100644 --- a/utils/plot.py +++ b/utils/plot.py @@ -15,6 +15,8 @@ import numpy as np import matplotlib as mpl mpl.use('Agg') from matplotlib import rc +from matplotlib import pyplot as plt +from matplotlib.offsetbox import AnchoredText import getdist from getdist import plots @@ -32,6 +34,15 @@ def centers(x): return (x[:-1]+x[1:])*0.5 +def get_units(dimension): + if dimension == 3: return r' / GeV' + if dimension == 4: return r'' + if dimension == 5: return r' / GeV^{-1}' + if dimension == 6: return r' / GeV^{-2}' + if dimension == 7: return r' / GeV^{-3}' + if dimension == 8: return r' / GeV^{-4}' + + def calc_nbins(x): n = (np.max(x) - np.min(x)) / (2 * len(x)**(-1./3) * (np.percentile(x, 75) - np.percentile(x, 25))) return np.floor(n) @@ -84,6 +95,10 @@ def plot_argparse(parser): '--plot-elements', type=misc_utils.parse_bool, default='False', help='Plot MCMC triangle in the mixing elements space' ) + parser.add_argument( + '--plot-bayes', type=misc_utils.parse_bool, default='False', + help='Plot Bayes factor' + ) def flat_angles_to_u(x): @@ -139,7 +154,7 @@ def gen_figtext(args): mr1, mr2, mr3, args.dimension, int(args.energy), args.scale ) - else: + else: t += 'IC observed flavour ratio = [{0:.2f}, {1:.2f}, ' \ '{2:.2f}]\nDimension = {3}'.format( mr1, mr2, mr3, args.dimension, int(args.energy) @@ -242,3 +257,99 @@ def chainer_plot(infile, outfile, outformat, args, mcmc_paramset): mpl.pyplot.figtext(0.5, 0.7, fig_text, fontsize=15) for of in outformat: g.export(outfile+'_elements.'+of) + + +def bayes_factor_plot(infile, outfile, outformat, args): + """Make Bayes factor plot.""" + if not args.plot_bayes: return + print "Making Bayes Factor plot" + fig_text = gen_figtext(args) + + raw = np.load(infile) + scales, evidences = raw.T + null = evidences[0] + + reduced_ev = -(evidences - null) + + fig = plt.figure(figsize=(7, 5)) + ax = fig.add_subplot(111) + + ax.set_xlabel(r'{\rm log}_{10} \Lambda ' + get_units(args.dimension)) + ax.set_ylabel(r'Bayes Factor') + + ax.plot(scales, reduced_ev) + + for ymaj in ax.yaxis.get_majorticklocs(): + ax.axhline(y=ymaj, ls=':', color='gray', alpha=0.7, linewidth=1) + for xmaj in ax.xaxis.get_majorticklocs(): + ax.axvline(x=xmaj, ls=':', color='gray', alpha=0.7, linewidth=1) + + at = AnchoredText( + fig_text, prop=dict(size=7), frameon=True, loc=2 + ) + at.patch.set_boxstyle("round,pad=0.,rounding_size=0.5") + ax.add_artist(at) + for of in outformat: + fig.savefig(outfile+'.'+of, bbox_inches='tight', dpi=150) + + +def myround(x, base=5, 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)) + else: int(base * np.round(float(x)/base)) + + +def plot_BSM_angles_limit(infile, outfile, xticks, outformat, args): + """Make BSM angles vs scale limit plot.""" + print "Making BSM angles limit plot.""" + fig_text = gen_figtext(args) + + raw = np.load(infile) + sc_ranges = ( + myround(np.min(raw[0][:,0]), down=True), + myround(np.max(raw[0][:,0]), up=True) + ) + + proc = [] + for idx, theta in enumerate(raw): + scale, llh = theta.T + delta_llh = -2 * (llh - np.max(llh)) + # 90% CL for 1 dof + al = scale[delta_llh > 2.71] + proc.append((idx+1, al[0])) + + limits = np.array(proc) + + fig = plt.figure(figsize=(7, 5)) + ax = fig.add_subplot(111) + + ax.set_xticklabels(['']+xticks+['']) + ax.set_xlim(0, len(xticks)+1) + ax.set_ylim(sc_ranges[0], sc_ranges[-1]) + ax.set_xlabel(r'BSM angle') + ylabel = r'${\rm log}_{10} \Lambda' + get_units(args.dimension) + r'$' + ax.set_ylabel(ylabel) + + for l in limits: + line = plt.Line2D( + (l[0]-0.1, l[0]+0.1), (l[1], l[1]), lw=3, color='r' + ) + ax.add_line(line) + # ax.arrow( + # l[0], l[1], 0, -1.5, head_width=0.05, head_length=0.2, fc='r', + # ec='r', lw=2 + # ) + ax.annotate( + s='', xy=l, xytext=(l[0], l[1]-1.5), + arrowprops={'arrowstyle': '<-', 'lw': 1.5, 'color':'r'} + ) + + for ymaj in ax.yaxis.get_majorticklocs(): + ax.axhline(y=ymaj, ls=':', color='gray', alpha=0.4, linewidth=1) + for xmaj in ax.xaxis.get_majorticklocs(): + ax.axvline(x=xmaj, ls=':', color='gray', alpha=0.4, linewidth=1) + + for of in outformat: + fig.savefig(outfile+'.'+of, bbox_inches='tight', dpi=150) + |