"""
plot__sipm_pde 

python script to access the halld_sipm data base (created by Yi) and plot SiPM properties
The values are then histogramed.
"""
import os
import subprocess
import numpy
from matplotlib import pyplot as plt
from datetime import datetime, date, time, timedelta
from matplotlib.backends.backend_pdf import PdfPages

Vover = 1.2

# create list of file names
filenames = []
figs = []

# create text file with data from sipm_dpe table.

nfiles = 0
filenames.append("sipmfiles/sipm_V"+str(int(10*Vover))+".dat")
command =["mysql","-hhallddb.jlab.org","-uhalld","-pGlueX_00","halld_sipm","-e","select * from sipm_pde where voltage_offset="+str(Vover-0.9)+";"]
print "command=",command
fout = open(filenames[nfiles],"w")
subprocess.call(command,stdout=fout)
fout.close()


# create text file from data base first

fin = open(filenames[0],"r")
sn_in = []
temp_in = []
voltage_in = []
pde_in = []
DR_in = []
gain_in = []
xtalk_in = []

entries = 0
nplots = 0

for line in fin:
    entries += 1
    linew = line.split()
    if entries == 1:
        for token in linew:
            print "First line dump, num tokens=",len(linew)," token=",token
        continue   # discard first entry
    Iover = int(float(linew[2])*10)
    IVover = int((Vover-0.9 + 0.001)*10)
    if IVover < 0:
        IVover = IVover -1
    # print "Iover=",Iover," IVover=",IVover
    if Iover == IVover:    # make integer instead of floating comparison
        sn_in.append(float(linew[0]))
        temp_in.append(float(linew[1]))
        voltage_in.append(float(linew[5]))
        pde_in.append(float(linew[8]))
        DR_in.append(float(linew[6]))
        gain_in.append(float(linew[10]))
        xtalk_in.append(float(linew[12]))            

entries -= 1
print "\nNumber of entries=",entries," for ",fin
print "Number of entries for pde=",len(pde_in)
# print "pde=",pde_in
fin.close()
    

# convert to numpy arrays for plotting
sn = numpy.array(sn_in)
temp = numpy.array(temp_in)
voltage = numpy.array(voltage_in)
pde = numpy.array(pde_in)
DR = numpy.array(DR_in)
gain = numpy.array(gain_in)
xtalk = numpy.array(xtalk_in)

numpy.set_printoptions(threshold='nan')
# print "Length pde=",len(pde),"pde=", pde,"\n\n"
    
fig = plt.figure(1)
figs.append(fig)

nbins = 100
nsub = 1
xmin = 0
xmax = 5000
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(sn,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("Serial Number")
plt.title("Vover="+str(Vover)+" V")
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')


nbins = 100
nsub = 2
xmin = 0
xmax = 30
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(temp,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("Temperature (degC)")
plt.title("Vover="+str(Vover)+" V")
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')

nbins = 100
nsub = 3
xmin = 65
xmax = 80
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(voltage,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("Vop (V)")
plt.title("Vover="+str(Vover)+" V. Mean="+'{:.3f}'.format(numpy.average(voltage)))
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')

plt.tight_layout()
fig = plt.figure(2)
figs.append(fig)

nsub = 1
xmin = 0
xmax = 10
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(gain,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("Gain (10^5)")
plt.title("Vover="+str(Vover)+" V")
plt.title("Vover="+str(Vover)+" V. Mean="+'{:.3f}'.format(numpy.average(gain)))
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')

nsub = 2
xmin = 0
xmax = 0.3
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(pde,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("PDE")
plt.title("Vover="+str(Vover)+" V. Mean="+'{:.3f}'.format(numpy.average(pde)))
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')
# plt.figtext(0.2,0.8,'example text')


nsub = 3
xmin = 0
xmax = 3
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(DR,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("Dark Rate (MHz)")
plt.title("Vover="+str(Vover)+" V. Mean="+'{:.3f}'.format(numpy.average(DR)))
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')


nsub = 4
xmin = 0
xmax = 1
plt.subplot(2,2,nsub)
binwidth = (xmax-xmin)/float(nbins)
n, bins, patches = plt.hist(xtalk,bins=numpy.arange(xmin,xmax,binwidth),histtype='step',color='black',log=False)
plt.ylabel("Entries")
plt.xlabel("Cross Talk")
plt.title("Vover="+str(Vover)+" V. Mean="+'{:.3f}'.format(numpy.average(xtalk)))
plt.axis([xmin,xmax,0,10000])
plt.autoscale(enable=True,axis='y')


plt.tight_layout()
# plt.show()
pdfname = "plot_sipm_pde_V"+str(int(10*Vover))+".pdf"
print "PDF filename=",pdfname
with PdfPages(pdfname) as pdf:
    for fig in figs:
        pdf.savefig(fig)