make_root_from_grid_output.py

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#!/usr/bin/env python

from __future__ import print_function

from array import array

from ROOT import *

import glob

def process_one_file(fn):

  with open(fn, 'r') as inf:

    for line in inf:

      line = line.rstrip('\n').rstrip(' ')

      values = line.split(' ')

      run[0] = int(values[0])

      subrun[0] = int(values[1])

      cycle[0] = int(values[2])

      evt[0] = int(values[3])

      subevt[0] = int(values[4])
      
      npng1gamma[0] = float(values[5])

      npng2gamma[0] = float(values[6])

      ncgappng1[0] = float(values[7])

      ncgappng2[0] = float(values[8])
      
      nc[0] = int(values[9])
     
      ispi0[0] = int(values[10])

      tr.Fill()

        
file_list = [name for name in glob.glob('/pnfs/nova/persistent/users/acedeno/ncpi0/nd_fhc_nc_selection_stride_FlatFluxdataset1_offset0*')]
#file_list1 = [name for name in glob.glob('/pnfs/nova/persistent/users/acedeno/ncpi0/nd_fhc_nc_selection_stride_FlatFluxdataset1_offset0*')]
#file_list2 = [name for name in glob.glob('/pnfs/nova/persistent/users/acedeno/ncpi0/nd_fhc_nc_selection_stride_GenieLikedataset1_offset0*')]
#file_list3 = [name for name in glob.glob('/pnfs/nova/persistent/users/acedeno/ncpi0/nd_fhc_nc_selection_stride_2viewdataset1_offset0*')]

#file_list = [name for name in glob.glob('/pnfs/nova/persistent/users/acedeno/ncpi0/nd_fhc_nc_selection_stride_flatdataset1_offset*')]
#file_list = [name for name in glob.glob('/nova/app/users/acedeno/tag_releasesS18-06-14/NDAna/ncpi0_semi_inc_png_cvn/nd_fhc_nc_selection_stride_nominaldataset250_offset*')]
print(len(file_list))
#print(len(file_list1))
#print(len(file_list2))
#print(len(file_list3))

#~ for name in glob.glob('grid_output/*.txt'):

#~ for name in glob.glob('grid_output/nd_rhc_numubarcc_selection_stride2_offset0.1_of_200.txt'):

  #~ file_list.append(name)

# make the tree

outf = TFile('training_sample_FlatFlux.root', 'recreate')
#outf1 = TFile('training_sample_FlatFlux.root', 'recreate')
#outf2 = TFile('training_sample_GenieLike.root', 'recreate')
#outf3 = TFile('training_sample_2view.root', 'recreate')


tr = TTree('tr', 'tree of training sample')

# tree leave

run = array('i', [0])

subrun = array('i', [0])

cycle = array('i', [0])

evt = array('i', [0])

subevt = array('i', [0])

npng1gamma = array('f', [0.])

npng2gamma = array('f', [0.])

ncgappng1 = array('f', [0.])

ncgappng2 = array('f', [0.])

nc = array('i',[0])

ispi0 = array('i',[0])

tr.Branch('run', run, 'run/I')

tr.Branch('subrun', subrun, 'subrun/I')

tr.Branch('cycle', cycle, 'cycle/I')

tr.Branch('evt', evt, 'evt/I')
  
tr.Branch('subevt', subevt, 'subevt/I')

tr.Branch('npng1gamma', npng1gamma, 'npng1gamma/F')

tr.Branch('npng2gamma', npng2gamma, 'npng2gamma/F')

tr.Branch('ncgappng1', ncgappng1, 'ncgappng1/F')

tr.Branch('ncgappng2', ncgappng2, 'ncgappng2/F')

tr.Branch('nc', nc, 'nc/I')

tr.Branch('ispi0', ispi0, 'nc/I')

for f in file_list:

  process_one_file(f)

outf.Write()

#for k in file_list1:

 # process_one_file(k)

#outf1.Write()

#for i in file_list2:

 # process_one_file(i)

#outf2.Write()


#for j in file_list3:

 # process_one_file(j)

#outf3.Write()