def update_schema():
from soudan_database import SoudanServer, RunDocumentClass
server = SoudanServer()
for id in server.get_database():
run_doc = server.get_run(id)
run_doc = RunDocumentClass.update_schema(run_doc)
print "Updating run number: %s" % run_doc.id
server.insert_rundoc(run_doc)
def processSpectrum(pfn_dir, divide_by_number = 1, outputfile='temp.root', \
force_overwrite=False, hist_name='hist', \
energy_scale='*1', cuts='', use_baseline_cut=False, \
opposite_baseline_cut=False):
tree_name = '%sTree' % hist_name
server = SoudanServer()
file_list = server.get_accepted_runs()
number_of_sigma = 2
mass_of_detector = 0.528 # in kg
file_to_output = TFile("%s" % outputfile, 'UPDATE')
tree_in_file = file_to_output.Get(tree_name)
hist = TH1D(hist_name, hist_name, 8192, 0, eval("8192%s" % energy_scale))
hist.Rebin(divide_by_number)
hist.GetXaxis().SetTitle("Energy (keV)")
hist.GetYaxis().SetTitle("Counts/keV/kg/day")
total_time = 0
for id in file_list:
print id
rundoc = server.get_run(id.id)
file_name = eval("rundoc.output_data_file_tier_3.%s.pfn" % pfn_dir)
open_file = TFile(file_name)
main_tree = open_file.Get("wf_analysis")
coinc_tree = open_file.Get("event_coincidence")
main_tree.AddFriend(coinc_tree)
real_cuts = cuts
main_tree.GetEntry(0)
if use_baseline_cut:
not_string = ""
if opposite_baseline_cut:
not_string = "!"
additional_cuts = " && %s(abs(fitConstant-%f) <= 3*%f) " % (not_string, \
rundoc.baseline_dict.average_fit_constant, \
rundoc.baseline_dict.average_fit_rms)
real_cuts += additional_cuts
file_to_output.cd()
main_tree.Draw("-energy%s>> +%s" % (energy_scale, hist.GetName()),real_cuts, "goff")
open_file.Close()
total_time += rundoc.livetime.run_seconds
total_time /= (3600.*24.)
hist.Scale(1./(mass_of_detector*hist.GetBinWidth(1)*total_time))
file_to_output.cd()
hist.Write(hist.GetName(), TObject.kOverwrite)
file_to_output.Close()
def look_at_number_of_entries_in_file():
server = SoudanServer()
tree = ROOT.TTree("temp", "temp")
num_entries = array.array('d', [0])
tree.Branch("entries", num_entries, "num_entries/D")
for id in server.get_database():
print id
rundoc = server.get_run(id)
if not rundoc: continue
num_entries[0] = rundoc.number_of_entries_in_tier1_root_tree/\
float(rundoc.livetime.run_seconds)
tree.Fill()
open_file = ROOT.TFile("temp.root", "recreate")
hist = ROOT.TH1D("hist", "hist", 1000, 0, 1000)
tree.Draw("entries >> hist")
raw_input("enter")
hist.Write()
def processSpectrum(doc_list, input_directory='..', type='pulser',\
hist_name='hist', \
energy_scale='*1', cuts='', use_baseline_cut=False, opposite_baseline_cut=False):
import re
from array import array
from ROOT import TFile, TH1D, TTree, TObject, TEventList, gROOT
from soudan_database import SoudanServer
number_of_sigma = 3
hist = TH1D(hist_name, hist_name, 8192, 0, eval("8192%s" % energy_scale))
hist.GetXaxis().SetTitle("Energy (keV)")
hist.GetYaxis().SetTitle("Counts")
server = SoudanServer()
for run_number in doc_list:
doc = server.get_run(run_number.id)
try:
string_of_file_name = eval('doc.output_data_file_tier_3.%s.lfn' % type)
except:
print "Incorrect type"
continue
print doc._get_id()
open_file = TFile("%s/%s" % (input_directory,string_of_file_name))
main_tree = open_file.Get("wf_analysis")
coinc_tree = open_file.Get("event_coincidence")
main_tree.AddFriend(coinc_tree)
real_cuts = cuts
if use_baseline_cut:
not_string = ""
if opposite_baseline_cut:
not_string = "!"
additional_cuts = " && %s(abs(fitConstant-%f) <= %f*%f) " % \
(not_string, doc.baseline_dict.average_fit_constant,\
number_of_sigma, doc.baseline_dict.average_fit_rms)
real_cuts += additional_cuts
gROOT.cd()
main_tree.Draw("-energy%s>> +%s" % (energy_scale, hist.GetName()),real_cuts, "goff")
open_file.Close()
return hist