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

data=loadtxt('hot_pixel_hstof.dat')
tof   =data[:,0]
energy=data[:,1]
epqst =data[:,2]

figure(figsize=(8,5))

mask1=epqst>83
mask2=epqst<84

subplot(121)
result=hist(energy[mask1],bins=arange(0.5,200.5,1),log=True,label='gain=L')
legend()
xlabel(r'$E_{SSD\#}$',fontsize=18)
ylabel('Counts',fontsize=18)
xticks([20,40,60,80,100,120,140,160,180],fontsize=14)
yticks(fontsize=14)
subplot(122)
hist(energy[mask2],bins=arange(0.5,200.5,1),log=True,label='gain=H')
ylim(1e0,1e5)
legend()
xlabel(r'$E_{SSD\#}$',fontsize=18)
xticks(fontsize=14)
yticks([1e0,1e1,1e2,1e3,1e4,1e5],['','','','','',''])
show()
tight_layout(pad=1,h_pad=-0.5,w_pad=-0.25)



#subplot(121)
#hist(energy[mask1],bins=arange(0.5,200.5,1),log=True,label='gain=L')
#legend()
#xlabel(r'$E_{SSD\#}$',fontsize=18)
#ylabel('Counts',fontsize=18)
#xticks([20,40,60,80,100,120,140,160,180],fontsize=14)
#yticks(fontsize=14)
#subplot(122)
#hist(energy[mask2],bins=arange(0.5,200.5,1),log=True,label='gain=H')
#ylim(1e0,1e5)
#legend()
#xlabel(r'$E_{SSD\#}$',fontsize=18)
#xticks(fontsize=14)
#yticks([1e0,1e1,1e2,1e3,1e4,1e5],['','','','','',''])
#show()
#tight_layout(pad=1,h_pad=-0.5,w_pad=-0.25)