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#!/usr/bin/env python
# Copyright (c) 2019, Anthony Latorre <tlatorre at uchicago>
#
# 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 <https://www.gnu.org/licenses/>.
"""
Script to plot the energy and time difference distribution for neutrons. To run
it just run:
$ ./plot-neutrons [list of fit results]
"""
from __future__ import print_function, division
import numpy as np
from scipy.stats import iqr, poisson
from scipy.stats import iqr, norm, beta
from sddm.stats import *
import emcee
from sddm.dc import estimate_errors, EPSILON
import nlopt
from sddm import printoptions
particle_id = {20: 'e', 22: 'u'}
if __name__ == '__main__':
import argparse
import numpy as np
import pandas as pd
import sys
import h5py
from sddm.plot_energy import *
from sddm.plot import *
from sddm import setup_matplotlib
from sddm.utils import correct_energy_bias
parser = argparse.ArgumentParser("plot fit results")
parser.add_argument("filenames", nargs='+', help="input files")
parser.add_argument("--save", action='store_true', default=False, help="save corner plots for backgrounds")
parser.add_argument("--mc", nargs='+', required=True, help="atmospheric MC files")
args = parser.parse_args()
setup_matplotlib(args.save)
import matplotlib.pyplot as plt
# Loop over runs to prevent using too much memory
evs = []
rhdr = pd.concat([read_hdf(filename, "rhdr").assign(filename=filename) for filename in args.filenames],ignore_index=True)
for run, df in rhdr.groupby('run'):
evs.append(get_events(df.filename.values, merge_fits=True))
ev = pd.concat(evs)
ev = correct_energy_bias(ev)
# Note: We loop over the MC filenames here instead of just passing the
# whole list to get_events() because I had to rerun some of the MC events
# using SNOMAN and so most of the runs actually have two different files
# and otherwise the GTIDs will clash
ev_mcs = []
for filename in args.mc:
ev_mcs.append(get_events([filename], merge_fits=True, mc=True))
ev_mc = pd.concat(ev_mcs)
ev_mc = correct_energy_bias(ev_mc)
ev = ev.reset_index()
ev_mc = ev_mc.reset_index()
# remove events 200 microseconds after a muon
ev = ev.groupby('run',group_keys=False).apply(muon_follower_cut)
# 00-orphan cut
ev = ev[(ev.gtid & 0xff) != 0]
ev_mc = ev_mc[(ev_mc.gtid & 0xff) != 0]
neutrons = ev[ev.neutron]
neutrons_mc = ev_mc[ev_mc.neutron]
atm = ev[ev.signal & ev.prompt & ev.atm]
atm_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ev_mc.atm]
# Drop events without fits
atm = atm[~np.isnan(atm.fmin)]
atm_mc = atm_mc[~np.isnan(atm_mc.fmin)]
atm = atm[atm.psi < 6]
atm_mc = atm_mc[atm_mc.psi < 6]
atm = pd.merge(atm,neutrons,left_on=['run','gtid'],right_on=['run','atm_gtid'],suffixes=('','_neutron'))
atm_mc = pd.merge(atm_mc,neutrons_mc,left_on=['run','gtid'],right_on=['run','atm_gtid'],suffixes=('','_neutron'))
print("neutrons with nhit > 100")
print(atm[atm.nhit_neutron >= 100][['run','gtid_neutron','nhit_neutron','nhit_cal_neutron']])
fig = plt.figure(1)
plt.hist(atm.nhit_cal_neutron.values,bins=np.linspace(0,100,101),histtype='step',color='C0',label="Data")
weights = np.tile(len(atm)/len(atm_mc),len(atm_mc))
plt.hist(atm_mc.nhit_cal_neutron.values,bins=np.linspace(0,100,101),weights=weights,histtype='step',color='C1',label="Monte Carlo")
plt.xlabel("Nhit")
despine(fig,trim=True)
plt.tight_layout()
plot_legend(1)
if args.save:
plt.savefig("neutron_nhit_cal.pdf")
plt.savefig("neutron_nhit_cal.eps")
else:
plt.title("Neutron Nhit Distribution")
fig = plt.figure(2)
dt = (atm.gtr_neutron - atm.gtr)/1e6;
bins = np.linspace(20e-3,250,101)
plt.hist(dt,bins=bins,histtype='step',color='C0',label="Data")
dt = (atm_mc.gtr_neutron - atm_mc.gtr)/1e6;
plt.hist(dt,bins=bins,weights=weights,histtype='step',color='C1',label="Monte Carlo")
plt.xlabel(r"$\Delta$ t (ms)")
despine(fig,trim=True)
plt.tight_layout()
plot_legend(1)
if args.save:
plt.savefig("neutron_delta_t.pdf")
plt.savefig("neutron_delta_t.eps")
else:
plt.title(r"Neutron $\Delta t$ Distribution")
plt.show()
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