from numpy import *
import numpy as np
from matplotlib.pyplot import *
import matplotlib as mpl
mpl.rcParams['xtick.major.size'] = 8
mpl.rcParams['xtick.minor.size'] = 4
mpl.rcParams['xtick.major.width'] = 1.5
mpl.rcParams['xtick.minor.width'] = 1.5
mpl.rcParams['ytick.major.size'] = 8
mpl.rcParams['ytick.minor.size'] = 4
mpl.rcParams['ytick.major.width'] = 1.5
mpl.rcParams['ytick.minor.width'] = 1.5
ticksize=20
labelsize=22
data=loadtxt('stof_1998_quiet_times.dat')
tof=data[:,0]
epqst=data[:,1]
energy=data[:,2]
mask_low=epqst<84
mask_high=epqst>=84



counts,binx=histogram(tof[mask_low],bins=arange(0.5,400.5,1))
counts_h,binx_h=histogram(tof[mask_high],bins=arange(0.5,400.5,1))
figure()
plot(binx_h[:-1]+0.5,counts_h,'r',label='gain=H',drawstyle='steps-pre',lw=1.5)
plot(binx[:-1]+0.5,counts,'b',label='gain=L',drawstyle='steps-pre',lw=1.5)
xlabel(r'$\tau_{\#}$',fontsize=labelsize)
ylabel('$Counts$',fontsize=labelsize)
xticks(fontsize=ticksize)
yticks(fontsize=ticksize)
legend(fontsize=ticksize)
yscale('log')
show()
tight_layout(pad=0.4,h_pad=0.01,w_pad=0.001)


counts,binx=histogram(energy[mask_low],bins=arange(0.5,1000.5,1))
counts_h,binx_h=histogram(energy[mask_high],bins=arange(0.5,1000.5,1))
figure()
plot(binx_h[:-1]+0.5,counts_h,'r',label='gain=H',drawstyle='steps-pre',lw=1.5)
plot(binx[:-1]+0.5,counts,'b',label='gain=L',drawstyle='steps-pre',lw=1.5)
xlabel(r'$E_{SSD\#}$',fontsize=labelsize)
ylabel('$Counts$',fontsize=labelsize)
xticks(fontsize=ticksize)
yticks(fontsize=ticksize)
legend(fontsize=ticksize)
xscale('log')
yscale('log')
xlim(10,1000)
show()
tight_layout(pad=0.4,h_pad=0.01,w_pad=0.001)



mask_energy=energy>37
counts,binx=histogram(epqst[mask_energy],bins=arange(0.5,120.5,1))
figure()
plot(binx[:-1]+0.5,counts,'b',drawstyle='steps-pre',lw=1.5,label=r'$E_{SSD\#}>37$')
xlabel(r'$E/q{\#}$',fontsize=labelsize)
ylabel('$Counts$',fontsize=labelsize)
xticks(fontsize=ticksize)
yticks(fontsize=ticksize)
legend(loc=3,fontsize=ticksize)
show()
tight_layout(pad=0.4,h_pad=0.01,w_pad=0.001)