def loopOverRecords(self, cuts, energyScaler,
use_baseline_cut = True,
opposite_baseline_cut = False):
server = SoudanServer()
file_list = server.get_accepted_runs()
for id in file_list:
print id
rundoc = server.get_run(id.id)
file_name = rundoc.output_data_file_tier_2.pfn
wf_file_name = rundoc.root_data_file_tier_1.pfn
open_file = ROOT.TFile(file_name)
main_tree = open_file.Get("wf_analysis")
coinc_tree = open_file.Get("event_coincidence")
wf_open_file = ROOT.TFile(wf_file_name)
wf_tree = wf_open_file.Get("gretaDec")
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
if not self.printWaveformToPS(main_tree, wf_tree, real_cuts, energyScaler): break
def analyze_timing(outputfile='temp.root', force_overwrite=False):
force_overwrite = True
timing_list_name = "timing_list"
time_run_list_name = "time_of_run_list"
server = SoudanServer()
file_to_output = ROOT.TFile(outputfile, 'recreate');
objects_to_write = []
apickle = None
if server.pickle_is_in_database(timing_list_name):
print "Already exists"
apickle = server.get_pickle(timing_list_name)
time_list = apickle.pickle
timing_list_name = None
else:
apickle = PickleDocumentClass()
force_overwrite = True
if force_overwrite:
time_list = []
file_list = server.get_accepted_runs()
# generate final plots
start_time = None
for id in file_list:
print id
rundoc = server.get_run(id.id)
if not start_time:
start_time = rundoc.time_of_start_of_run
timeofstart = rundoc.time_of_start_of_run
file_name = rundoc.output_data_file_tier_2.pfn
open_file = ROOT.TFile(file_name)
main_tree = open_file.Get("wf_analysis")
coinc_tree = open_file.Get("event_coincidence")
main_tree.AddFriend(coinc_tree)
main_tree.GetEntry(0)
first_time = main_tree.eventTime
main_tree.GetEntry(main_tree.GetEntries()-1)
last_time = main_tree.eventTime
time_list.append((time.mktime(timeofstart.timetuple()), \
first_time, last_time, \
main_tree.runNumber))
open_file.Close()
apickle.pickle = time_list
server.insert_pickle(apickle, timing_list_name)
conversion_code = "convert_gretina_time_to_real_time"
dynamic_function = None
pickle = None
if server.pickle_is_in_database(conversion_code):
pickle = server.get_pickle(conversion_code)
if not force_overwrite:
dynamic_function = pickle.pickle
conversion_code = None
if not pickle:
pickle = PickleDocumentClass()
if not dynamic_function:
start_run_number = time_list[0][3]
start_time = time_list[0][0]
last_time = time_list[0][0]
scrap_list = []
def find_offset(scrap_list):
agraph = ROOT.TGraph(len(scrap_list))
for i in range(len(scrap_list)):
agraph.SetPoint(i, scrap_list[i][1], scrap_list[i][0])
pol1 = ROOT.TF1("pol1", "pol1")
agraph.Fit(pol1)
return pol1.GetParameter(0)
run_dict = {}
for start, event, last, runN in time_list:
if event < last_time:
# We have cycled, do the fitting
run_dict[start_run_number] = find_offset(scrap_list)
del scrap_list[:]
start_run_number = runN
last_time = event
scrap_list.append((start, event*1e-8, runN))
run_dict[start_run_number] = find_offset(scrap_list)
# Now make some dynamic code
run_numbers = run_dict.keys()
run_numbers.sort()
run_numbers.reverse()
code = """
def dynamic_function(run_number, event_time):
if run_number >= %i:
return %f + event_time*1e-8 """ % (run_numbers[0], run_dict[run_numbers[0]])
for i in range(1, len(run_numbers)):
code += """
elif run_number >= %i:
return %f + event_time*1e-8""" % (run_numbers[i], run_dict[run_numbers[i]])
code += """
return 0 """
pickle.pickle = code
server.insert_pickle(pickle, conversion_code)
code_obj = compile(code,'<string>', 'exec')
dynamic_function = types.FunctionType(code_obj.co_consts[0], globals())
apickle = None
mydict = None
if not server.pickle_is_in_database(time_run_list_name):
apickle = PickleDocumentClass()
else:
apickle = server.get_pickle(time_run_list_name)
time_run_list_name = None
mydict = apickle.pickle
if force_overwrite:
scratch_list = {}
start_time = 0
for start, event, last, runN in time_list:
if runN == 1933: print "Yes"
print runN
if start_time == 0: start_time = dynamic_function(runN, event)
scratch_list[runN] = (dynamic_function( runN, event ) - start_time,
dynamic_function( runN, last ) - start_time)
apickle.pickle = scratch_list
server.insert_pickle(apickle, time_run_list_name)
mydict = scratch_list
keys = mydict.keys()
new_graph = ROOT.TGraph(len(keys))
keys.sort()
for i in range(len(keys)):
first, last = mydict[keys[i]]
new_graph.SetPoint(i, keys[i], last - first)
c1 = ROOT.TCanvas()
new_graph.Draw("APL")
c1.Update()
raw_input("E")
#c1.Print("temp.eps")
file_to_output.cd()
for object in objects_to_write:
object.Write(object.GetName(), TObject.kOverwrite)
file_to_output.Close()