source: fact/tools/pyscripts/sandbox/vogler/DRS_End_Noise_RMS_2.py@ 16858

#!/usr/bin/python -tt
# ********************************
# Test script for the CalFits class
# 
# written by Thomas Kraehenbuehl, ETH Zurich
# tpk@phys.ethz.ch, +41 44 633 3973
# April 2012
# ********************************
#
# modified and adapted py Patrick Vogler
#
# ################################
from ROOT import gSystem
gSystem.Load("calfactfits_h.so")   # according to new naming scheme
from ROOT import *







#define filenames

# 2011 12 05
calibfilename = '/fact/raw/2011/12/05/20111205_011.drs.fits.gz'    # NROI 300, pedestal

datafilename = '/fact/raw/2011/12/05/20111205_022.fits.gz'          # NROI 300, 5 minutes physics data with


import numpy as np
from scipy import weave
from scipy.weave import converters

from plotters import Plotter         # ADC display
# from plotters import CamPlotter      # event display
#from drs_spikes import DRSSpikes


print "Testing object creation: "
caltest = CalFactFits(datafilename, calibfilename)
npcalevent  = np.empty( caltest.npix * caltest.nroi, np.float64) #.reshape(caltest.npix ,caltest.nroi)
caltest.SetNpcaldataPtr(npcalevent)


numroi = np.int64(caltest.nroi)
numpix = np.int64(caltest.npix)
numevents = np.int64(caltest.nevents)

num_LP_ev = 0   # number of ext Lightpulser events
num_ped = 0     # number of pedestal events


print "Common variables run information: "
print "ROI: ", numroi
print "#Pix: ", numpix
print "Number of events: ", numevents
print


event = np.zeros((numpix, numroi))  # create an array to store an event in the format numpix * numroi (2-dim array)
print "Array event created"
run_average = np.zeros((numpix, numroi))   # create an array to store the "average event" of a run
data_average_run = np.zeros(numroi)
print "Arrays created "


print "... looping..."

while caltest.GetCalEvent():    # Loop  ueber alle events
    # print npcalevent  ## Daten, Array   1 dim Laenge caltest.npix * caltest.nroi   1 Event


    if (caltest.event_triggertype == 4):  #ext LP event
        print 'event id:', caltest.event_id, '  Trigger Type:', caltest.event_triggertype
        num_LP_ev = num_LP_ev + 1
        event = np.reshape(npcalevent, (numpix, -1))     # bring the event the shape numpix * numroi (2-dim array)
        run_average += event**2

print "Looped ... "

run_average = run_average/num_LP_ev
run_average = np.sqrt(run_average)



for i in range (0, (numpix - 1) ):
    data_average_run += run_average[i]**2
print "Looped second loop "
data_average_run = data_average_run/numpix
data_average_run = np.sqrt(data_average_run)





del caltest
print "caltest deleted "



print "Common variables run information: "
print "ROI: ", numroi
print "#Pix: ", numpix
print "Number of events: ", numevents
print "Number of external Lightpulser events: ", num_LP_ev
print "Number of pedestal: ", num_ped
print



#####################################################################################################################
print "creating plotters ..."

#make a Plotter class ... this is an easy way for plotting ... but there are 
# many was to plot data ... without this class ... it was written for convenience, but there is no strong reason to use it...
#myplotter = Plotter('titel of the plot', xlabel='time in slices', ylabel='amplitude calibrated data ... in mV')

myplotter = Plotter('titel of the plot', xlabel='time in slices', ylabel='amplitude calibrated data ... in mV')
myplotter2 = Plotter('titel of the plot', xlabel='time in slices', ylabel='amplitude calibrated data ... in mV')
#myplotter3 = Plotter('titel of the plot', xlabel='time in slices', ylabel='amplitude calibrated data ... in mV')

myplotter4 = Plotter('titel of the plot', xlabel='time in slices', ylabel='amplitude calibrated data ... in mV')

print "Plotters created "
###################################################################################################################

myplotter(run_average[20], 'pix 20, average' )

myplotter2(run_average[21], 'pix 21, average' )

#myplotter3((run_average[22]) / num_LP_ev, 'pix 22, average' )

#myplotter3(data_average_run / (numpix * num_LP_ev), 'average signal (all pixel) over the whole run' )

myplotter4(data_average_run , 'RMS (all pixel) over the whole run' )


answer = raw_input('type "quit" to quit ')
while not 'quit' in answer:
     answer = raw_input('type "quit" to quit ')