#!/usr/bin/env python # Copyright (c) 2019, Anthony Latorre # # This program is free software: you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) # any later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or # FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for # more details. # # You should have received a copy of the GNU General Public License along with # this program. If not, see . from __future__ import print_function, division import numpy as np # Taken from https://raw.githubusercontent.com/mwaskom/seaborn/c73055b2a9d9830c6fbbace07127c370389d04dd/seaborn/utils.py def despine(fig=None, ax=None, top=True, right=True, left=False, bottom=False, offset=None, trim=False): """Remove the top and right spines from plot(s). fig : matplotlib figure, optional Figure to despine all axes of, default uses current figure. ax : matplotlib axes, optional Specific axes object to despine. top, right, left, bottom : boolean, optional If True, remove that spine. offset : int or dict, optional Absolute distance, in points, spines should be moved away from the axes (negative values move spines inward). A single value applies to all spines; a dict can be used to set offset values per side. trim : bool, optional If True, limit spines to the smallest and largest major tick on each non-despined axis. Returns ------- None """ # Get references to the axes we want if fig is None and ax is None: axes = plt.gcf().axes elif fig is not None: axes = fig.axes elif ax is not None: axes = [ax] for ax_i in axes: for side in ["top", "right", "left", "bottom"]: # Toggle the spine objects is_visible = not locals()[side] ax_i.spines[side].set_visible(is_visible) if offset is not None and is_visible: try: val = offset.get(side, 0) except AttributeError: val = offset _set_spine_position(ax_i.spines[side], ('outward', val)) # Potentially move the ticks if left and not right: maj_on = any( t.tick1line.get_visible() for t in ax_i.yaxis.majorTicks ) min_on = any( t.tick1line.get_visible() for t in ax_i.yaxis.minorTicks ) ax_i.yaxis.set_ticks_position("right") for t in ax_i.yaxis.majorTicks: t.tick2line.set_visible(maj_on) for t in ax_i.yaxis.minorTicks: t.tick2line.set_visible(min_on) if bottom and not top: maj_on = any( t.tick1line.get_visible() for t in ax_i.xaxis.majorTicks ) min_on = any( t.tick1line.get_visible() for t in ax_i.xaxis.minorTicks ) ax_i.xaxis.set_ticks_position("top") for t in ax_i.xaxis.majorTicks: t.tick2line.set_visible(maj_on) for t in ax_i.xaxis.minorTicks: t.tick2line.set_visible(min_on) if trim: # clip off the parts of the spines that extend past major ticks xticks = ax_i.get_xticks() if xticks.size: firsttick = np.compress(xticks >= min(ax_i.get_xlim()), xticks)[0] lasttick = np.compress(xticks <= max(ax_i.get_xlim()), xticks)[-1] ax_i.spines['bottom'].set_bounds(firsttick, lasttick) ax_i.spines['top'].set_bounds(firsttick, lasttick) newticks = xticks.compress(xticks <= lasttick) newticks = newticks.compress(newticks >= firsttick) ax_i.set_xticks(newticks) yticks = ax_i.get_yticks() if yticks.size: firsttick = np.compress(yticks >= min(ax_i.get_ylim()), yticks)[0] lasttick = np.compress(yticks <= max(ax_i.get_ylim()), yticks)[-1] ax_i.spines['left'].set_bounds(firsttick, lasttick) ax_i.spines['right'].set_bounds(firsttick, lasttick) newticks = yticks.compress(yticks <= lasttick) newticks = newticks.compress(newticks >= firsttick) ax_i.set_yticks(newticks) if __name__ == '__main__': import ROOT import argparse from os.path import split from matplotlib.ticker import FuncFormatter parser = argparse.ArgumentParser("plot ROOT fit results") parser.add_argument("filename", help="input file") parser.add_argument("--save", action="store_true", default=False, help="save plots") args = parser.parse_args() if args.save: # default \textwidth for a fullpage article in Latex is 16.50764 cm. # You can figure this out by compiling the following TeX document: # # \documentclass{article} # \usepackage{fullpage} # \usepackage{layouts} # \begin{document} # textwidth in cm: \printinunitsof{cm}\prntlen{\textwidth} # \end{document} width = 16.50764 width /= 2.54 # cm -> inches # According to this page: # http://www-personal.umich.edu/~jpboyd/eng403_chap2_tuftegospel.pdf, # Tufte suggests an aspect ratio of 1.5 - 1.6. height = width/1.5 FIGSIZE = (width,height) import matplotlib.pyplot as plt font = {'family':'serif', 'serif': ['computer modern roman']} plt.rc('font',**font) plt.rc('text', usetex=True) else: # on retina screens, the default plots are way too small # by using Qt5 and setting QT_AUTO_SCREEN_SCALE_FACTOR=1 # Qt5 will scale everything using the dpi in ~/.Xresources import matplotlib matplotlib.use("Qt5Agg") import matplotlib.pyplot as plt # Default figure size. Currently set to my monitor width and height so that # things are properly formatted FIGSIZE = (13.78,7.48) # Make the defalt font bigger plt.rc('font', size=22) root_file = ROOT.TFile(args.filename) head, tail = split(args.filename) if tail.startswith("e_") or tail.startswith("electron"): prefix = "electron" elif tail.startswith("mu_") or tail.startswith("muon"): prefix = "muon" else: prefix = "" try: if root_file.Get("h1"): for hist_number, tf1_number in zip([1,2,4,5],[1,2,3,None]): h = root_file.Get("h%i" % hist_number) if tf1_number: f = root_file.Get("f%i" % tf1_number) bins = [h.GetXaxis().GetBinLowEdge(i) for i in range(1,h.GetNbinsX()+1)] + [h.GetXaxis().GetBinUpEdge(h.GetNbinsX())] hist = [h.GetBinContent(i) for i in range(1,h.GetNbinsX()+1)] bins = np.array(bins) hist = np.array(hist) bincenters = (bins[1:] + bins[:-1])/2 norm = np.trapz(hist,bincenters) hist /= norm fig = plt.figure(figsize=FIGSIZE) plt.hist(bincenters,weights=hist,bins=bins,histtype='step') x = np.linspace(bins[0],bins[-1],10000) if tf1_number: plt.plot(x,[f(xval)/norm for xval in x],color='red') despine(fig,trim=True) if hist_number == 1: plt.gca().set_xlim(-1,1) plt.ylabel("Arbitrary Units") plt.xlabel(r"$\cos\theta$") if args.save: plt.savefig("%s_shower_angular_distribution.pdf" % prefix) plt.savefig("%s_shower_angular_distribution.eps" % prefix) else: plt.title("%s Shower Angular Distribution" % prefix.capitalize()) elif hist_number == 2: plt.ylabel("Arbitrary Units") plt.xlabel(r"Distance along Track (cm)") if args.save: plt.savefig("%s_shower_position_distribution.pdf" % prefix) plt.savefig("%s_shower_position_distribution.eps" % prefix) else: plt.title("%s Shower Position Distribution" % prefix.capitalize()) elif hist_number == 4: plt.ylabel("Arbitrary Units") plt.xlabel(r"$\cos\theta$") if args.save: plt.savefig("%s_delta_ray_angular_distribution.pdf" % prefix) plt.savefig("%s_delta_ray_angular_distribution.eps" % prefix) else: plt.title("%s Delta Ray Angular Distribution" % prefix.capitalize()) elif hist_number == 5: plt.ylabel("Arbitrary Units") plt.xlabel(r"Distance along Track (cm)") if args.save: plt.savefig("%s_delta_ray_position_distribution.pdf" % prefix) plt.savefig("%s_delta_ray_position_distribution.eps" % prefix) else: plt.title("%s Delta Ray Position Distribution" % prefix.capitalize()) else: for graph_name, tf1_number, ylabel in zip(["g_dir_alpha","g_dir_beta","g_pos_alpha","g_pos_beta","g_dir_alpha_delta","g_dir_beta_delta"], [1,2,None,None,3,4], [r"$\alpha$",r"$\beta$",r"$k$",r"$\theta$",r"$\alpha$",r"$\beta$"]): g = root_file.Get(graph_name) if tf1_number: f = g.GetFunction("f%i" % tf1_number) x = [g.GetX()[i] for i in range(g.GetN())] y = [g.GetY()[i] for i in range(g.GetN())] yerr = [g.GetEY()[i] for i in range(g.GetN())] x = np.array(x) y = np.array(y) yerr = np.array(yerr) fig = plt.figure(figsize=FIGSIZE) plt.errorbar(x,y,yerr=yerr,fmt='o') x = np.linspace(x[0],x[-1],10000) if tf1_number: plt.plot(x,[f(xval) for xval in x],color='red') despine(fig,trim=True) plt.xlabel("Kinetic Energy (MeV)") plt.ylabel(ylabel) if graph_name == "g_dir_alpha": if args.save: plt.savefig("%s_shower_angular_distribution_alpha.pdf" % prefix) plt.savefig("%s_shower_angular_distribution_alpha.eps" % prefix) else: plt.title("%s Shower Angular Distribution" % prefix.capitalize()) elif graph_name == "g_dir_beta": if args.save: plt.savefig("%s_shower_angular_distribution_beta.pdf" % prefix) plt.savefig("%s_shower_angular_distribution_beta.eps" % prefix) else: plt.title("%s Shower Position Distribution" % prefix.capitalize()) elif graph_name == "g_pos_alpha": if args.save: plt.savefig("%s_shower_position_distribution_alpha.pdf" % prefix) plt.savefig("%s_shower_position_distribution_alpha.eps" % prefix) else: plt.title("%s Shower Position Distribution" % prefix.capitalize()) elif graph_name == "g_pos_beta": if args.save: plt.savefig("%s_shower_position_distribution_beta.pdf" % prefix) plt.savefig("%s_shower_position_distribution_beta.eps" % prefix) else: plt.title("%s Shower Position Distribution" % prefix.capitalize()) elif graph_name == "g_dir_alpha_delta": if args.save: plt.savefig("%s_delta_ray_angular_distribution_alpha.pdf" % prefix) plt.savefig("%s_delta_ray_angular_distribution_alpha.eps" % prefix) else: plt.title("%s Delta Ray Angular Distribution" % prefix.capitalize()) elif graph_name == "g_dir_beta_delta": if args.save: plt.savefig("%s_delta_ray_angular_distribution_beta.pdf" % prefix) plt.savefig("%s_delta_ray_angular_distribution_beta.eps" % prefix) else: plt.title("%s Delta Ray Position Distribution" % prefix.capitalize()) plt.show() finally: root_file.Close()