def plot_sensor_energies(towers_list):
c = TCanvas("c", "c", 800, 1200)
# gStyle.SetPalette(0)
c.SetGridx(1)
c.SetGridy(1)
gStyle.SetOptStat(0)
h = TH2F("h", "title", 4, 0., 4., 44, 20., 64.)
h.GetXaxis().SetTitle("sector number")
h.GetYaxis().SetTitle("pad number")
for t in towers_list:
h.Fill(t.sector, t.pad, t.energy)
h.SetTitle("")
h.DrawCopy("colztext")
# input("wait plot sensor")
c.Print("./energies.png")
TColor.InvertPalette()
def parse_rocketio_errors(results):
rode_dict_buff = {}
rode_dict_lock = {}
rod_dict_buff = {}
rod_dict_lock = {}
sb_suf = "_nonsb"
if(results[0].sb == 1):
sb_suf = "_sb"
for error in results:
#print error.date, error.sb_total_time, error.sb_time_run, error.sb_length
#cool magic numbers, because string looks like
#ROD 0x320900: rocketio problem: Lock status == 0xf , buffer status == 0x5
pos_rod = error.text.find("ROD") + 4
pos_lock = error.text.find("Lock") + 15
pos_buff = error.text.find("buffer") + 17
if error.msgID == 'TRT::ROD05Module':
rod = '0x'+str(error.text[pos_rod:pos_rod+6])
else:
rod = str(error.text[pos_rod:pos_rod+8])
lock = str(error.text[pos_lock:pos_lock+3])
buff = str(error.text[pos_buff:pos_buff+3])
bin_lock = bin(int(lock, 16))[2:].zfill(4)
bin_buff = bin(int(buff, 16))[2:].zfill(4)
if buff == '0xf':
if not rod+'_'+lock in rode_dict_lock:
rode_dict_lock[rod+'_'+lock] = 1
else:
rode_dict_lock[rod+'_'+lock] += 1
if not rod in rod_dict_lock:
rod_dict_lock[rod] = 1
else:
rod_dict_lock[rod] += 1
else:
if not rod+'_'+buff in rode_dict_buff:
rode_dict_buff[rod+'_'+buff] = 1
else:
rode_dict_buff[rod+'_'+buff] += 1
if not rod in rod_dict_buff:
rod_dict_buff[rod] = 1
else:
rod_dict_buff[rod] += 1
rode_dict_lock = OrderedDict(sorted(rode_dict_lock.items()))
rod_dict_lock = OrderedDict(sorted(rod_dict_lock.items()))
rode_dict_buff = OrderedDict(sorted(rode_dict_buff.items()))
rod_dict_buff = OrderedDict(sorted(rod_dict_buff.items()))
for key, value in rod_dict_buff.items():
if rod_dict_buff[key] < 10:
del rod_dict_buff[key]
for key2, val2 in rode_dict_buff.items():
if key2[:8] == key:
del rode_dict_buff[key2]
for key, value in rod_dict_lock.items():
if rod_dict_lock[key] < 10:
del rod_dict_lock[key]
for key2, val2 in rode_dict_lock.items():
if key2[:8] == key:
del rode_dict_lock[key2]
for key, value in rod_dict_lock.items():
print key, value
#gStyle.SetPalette(kBird)
#gStyle.SetPalette(kCMYK)
gStyle.SetPalette(kRainBow)
TColor.InvertPalette()
make_plot_all_rods(rode_dict_lock, rod_dict_lock, "all_rods_lock_errors" + sb_suf)
make_plot_all_rods(rode_dict_buff, rod_dict_buff, "all_rods_buff_errors" + sb_suf)
if(results[0].sb == 1):
make_time_rod_evo(rode_dict_lock, rod_dict_lock, results, True)
make_minute_plots(rod_dict_buff, rod_dict_lock, results)
def plot_hist(group_data, stacked=False, fitted=False):
group_name = str(group_data[0].run_number)
group_size = len(group_data)
if stacked:
print('Plotting stacked histogram.')
run_canvas = TCanvas()
run_canvas.SetLogy()
gStyle.SetPalette(87)
if group_name == '2946':
TColor.InvertPalette()
hs = THStack('hs', 'Group %s Histograms' % group_name)
for run in group_data:
tab = ' '
title = str(run.run_number) + tab + 'Average temperature: ' + str(
round(run.temperature_average, 2))
hist = make_hist(title, run.energies, 0, 270000)
hs.Add(hist)
hs.Draw('nostack PLC')
run_canvas.BuildLegend()
path = 'output/group_' + str(group_data[0].run_number) + '/'
run_canvas.Print(
(path + str(group_data[0].run_number) + '_stacked_histogram.pdf['))
run_canvas.Print(
(path + str(group_data[0].run_number) + '_stacked_histogram.pdf'))
run_canvas.Print(
(path + str(group_data[0].run_number) + '_stacked_histogram.pdf]'))
else:
hists_and_fits = []
hist_range = [20000, 60000, 150000, 350000, 550000]
for i in range(len(group_data)):
run = group_data[i]
hist = make_hist(str(run.run_number), run.energies, 0,
hist_range[i])
if fitted:
K_key = 'K_' + str(run.run_number)
K_pars = parameters.fit_pars[K_key]
K_fit = find_peak_fit('K', K_pars[0], K_pars[1], K_pars[2],
K_pars[3], K_pars[4], K_pars[5],
K_pars[6])
Tl_key = 'Tl_' + str(run.run_number)
Tl_pars = parameters.fit_pars[Tl_key]
Tl_fit = find_peak_fit('Tl', Tl_pars[0], Tl_pars[1],
Tl_pars[2], Tl_pars[3], Tl_pars[4],
Tl_pars[5], Tl_pars[6])
hists_and_fits.append([hist, K_fit, Tl_fit])
write_run_output(group_name, run, K_fit, Tl_fit)
else:
hists_and_fits.append([hist])
run_canvas = TCanvas("run_canvas", "run canvas")
run_canvas.Divide(3, int(group_size / 2))
file_name = ''
canvas_index = 1
for entry in hists_and_fits:
pad = run_canvas.cd(canvas_index)
pad.SetLogy()
run = entry[0]
if len(entry) == 3:
print('Plotting fitted histogram.')
file_name = '_fitted_histograms.pdf'
fit1 = entry[1]
fit2 = entry[2]
run.Fit(fit1, 'LR')
run.Fit(fit2, 'LR+')
else:
print('Plotting histogram.')
file_name = '_histograms.pdf'
run.Draw()
canvas_index += 1
path = 'output/group_' + group_name + '/'
run_canvas.Print((path + group_name + file_name + '['))
run_canvas.Print((path + group_name + file_name))
run_canvas.Print((path + group_name + file_name + ']'))
