diff --git a/database/lappd_raw_dist.json b/database/lappd_raw_dist.json
index 148fc34d0642b9100b1f76e0f1fee539177ee0dc..29f8f9ce619e38ef9d7645fa373e635d973ce6c2 100644
--- a/database/lappd_raw_dist.json
+++ b/database/lappd_raw_dist.json
@@ -1,4 +1,44 @@
{
+ "Calorimeter": {
+ "plots": [
+ {
+ "title": "Calorimeter Peak Time Distribution",
+ "func_code": "unpack_time({ch}, true)",
+ "xlabel": "Time (ns)",
+ "ylabel": "Counts",
+ "hist_range": [64, 0, 256],
+ "path": "ecal_peak_time.png"
+ },
+ {
+ "title": "Calorimeter Peak Height Distribution",
+ "func_code": "unpack_height({ch}, true)",
+ "xlabel": "ADC Value",
+ "ylabel": "Counts",
+ "hist_range": [100, 0, 500],
+ "path": "ecal_peak_height.png"
+ }
+ ]
+ },
+ "Scintillator2": {
+ "plots": [
+ {
+ "title": "Scintillator2 Peak Time Distribution",
+ "func_code": "unpack_time({ch}, true)",
+ "xlabel": "Time (ns)",
+ "ylabel": "Counts",
+ "hist_range": [64, 0, 256],
+ "path": "scint2_peak_time.png"
+ },
+ {
+ "title": "Scintillator2 Peak Height Distribution",
+ "func_code": "unpack_height({ch}, true)",
+ "xlabel": "ADC Value",
+ "ylabel": "Counts",
+ "hist_range": [100, 0, 500],
+ "path": "scint2_peak_height.png"
+ }
+ ]
+ },
"LAPPD": {
"plots": [
{
diff --git a/database/lappd_tcuts_dist.json b/database/lappd_tcuts_dist.json
new file mode 100644
index 0000000000000000000000000000000000000000..c3dc6a91462d3e1bf30b5e5dffb81381519cb115
--- /dev/null
+++ b/database/lappd_tcuts_dist.json
@@ -0,0 +1,25 @@
+{
+ "LAPPD": {
+ "plots": [
+ {
+ "title": "LAPPD Peak Time Distribution",
+ "func_code": "{ch}_peak.time - ecal.time",
+ "xlabel": "Time (ns)",
+ "ylabel": "Counts",
+ "hist_range": [80, -160, 160],
+ "path": "tcuts_lappd_peak_time.png",
+ "filter_code": "{ch}_peak.height > 0"
+ },
+ {
+ "title": "LAPPD Peak Height Distribution",
+ "func_code": "{ch}_peak.height",
+ "xlabel": "ADC Value",
+ "ylabel": "Counts",
+ "hist_range": [100, 0, 100],
+ "path": "tcuts_lappd_peak_height.png",
+ "filter_code": "{ch}_peak.height > 0"
+ }
+ ]
+ }
+}
+
diff --git a/database/run443_timing.json b/database/run443_timing.json
new file mode 100644
index 0000000000000000000000000000000000000000..74e7b089dc29c099e4d0226bd4448237af360b7b
--- /dev/null
+++ b/database/run443_timing.json
@@ -0,0 +1,618 @@
+{
+ "C4": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C6_1": {
+ "cut": [
+ 110.15,
+ 130.15
+ ],
+ "ref": "0"
+ },
+ "C6_4": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C6_2": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C6_3": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C7_1": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C7_4": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C7_2": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C7_3": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C5_1": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C5_4": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C5_2": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C5_3": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C9_1": {
+ "cut": [
+ 110.15,
+ 130.15
+ ],
+ "ref": "0"
+ },
+ "C9_2": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C9_4": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C9_3": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C8_2": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C8_3": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C8_1": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C8_4": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C1": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C2": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "C3": {
+ "cut": [
+ 105.95,
+ 125.95
+ ],
+ "ref": "0"
+ },
+ "LAPPD_E7": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E2": {
+ "cut": [
+ -111.75,
+ -71.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E8": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E4": {
+ "cut": [
+ -99.75,
+ -59.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D4": {
+ "cut": [
+ -99.75,
+ -59.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D8": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D2": {
+ "cut": [
+ -99.75,
+ -59.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D7": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F4": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E5": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E1": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E6": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D6": {
+ "cut": [
+ -99.75,
+ -59.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D1": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D5": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C4": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F8": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F3": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F7": {
+ "cut": [
+ -91.75,
+ -51.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_E3": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_D3": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C7": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C3": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C8": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F5": {
+ "cut": [
+ -99.75,
+ -59.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F1": {
+ "cut": [
+ -99.75,
+ -59.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F6": {
+ "cut": [
+ -91.75,
+ -51.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_F2": {
+ "cut": [
+ -83.75,
+ -43.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C2": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C6": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C1": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_C5": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G4": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G8": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G3": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G7": {
+ "cut": [
+ -119.75,
+ -79.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B7": {
+ "cut": [
+ -119.75,
+ -79.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B3": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B8": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B4": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G1": {
+ "cut": [
+ -95.75,
+ -55.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G6": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G2": {
+ "cut": [
+ -87.75,
+ -47.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H6": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A6": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B2": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B6": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B1": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_G5": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H4": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H8": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H3": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A3": {
+ "cut": [
+ -119.75,
+ -79.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A8": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A4": {
+ "cut": [
+ -75.75,
+ -35.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_B5": {
+ "cut": [
+ -75.75,
+ -35.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H2": {
+ "cut": [
+ -71.75,
+ -31.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H7": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H1": {
+ "cut": [
+ -79.75,
+ -39.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_H5": {
+ "cut": [
+ -115.75,
+ -75.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A1": {
+ "cut": [
+ -87.75,
+ -47.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A5": {
+ "cut": [
+ -87.75,
+ -47.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A7": {
+ "cut": [
+ -75.75,
+ -35.75
+ ],
+ "ref": "ecal.time"
+ },
+ "LAPPD_A2": {
+ "cut": [
+ -71.75,
+ -31.75
+ ],
+ "ref": "ecal.time"
+ }
+}
\ No newline at end of file
diff --git a/scripts/root/dataframe_analysis.C b/scripts/root/dataframe_analysis.C
index 22c1828598d2e237494ce5d889a8b5c4d21c21af..e548f8e5b7dffad23dcba1209497743968b08ab0 100644
--- a/scripts/root/dataframe_analysis.C
+++ b/scripts/root/dataframe_analysis.C
@@ -69,3 +69,19 @@ Peak get_maximum_peak(const std::vector<Peak> &peaks, Filter &&f, Args&&... args
return res;
}
+Peak peak_sum(const std::vector<Peak> &peaks, double thres = 0.)
+{
+ Peak res(0., 0., 0., 0);
+
+ for (auto &peak : peaks) {
+ if (peak.height > thres) {
+ res.time += peak.time;
+ res.integral += peak.integral;
+ res.height += peak.height;
+ res.pos ++;
+ }
+ }
+ res.time /= (double)res.pos;
+ return res;
+}
+
diff --git a/scripts/signal_timing_cuts.py b/scripts/signal_timing_cuts.py
index 6c6d6ba149a0f7de520aa39e8897788bb42b0ffb..0e2e30b148faca5fcef6a09ad3d44425d046e243 100644
--- a/scripts/signal_timing_cuts.py
+++ b/scripts/signal_timing_cuts.py
@@ -49,7 +49,10 @@ gROOT.SetBatch(args.batch)
# root dataframe
rdf = ROOT.RDataFrame('EvTree', args.root_file)
-save_list = ['ecal', 'ecal_ch', 'scint2', 'scint2_ch']
+save_list = [
+ 'ecal', 'ecal_ch',
+ # 'scint2', 'scint2_ch'
+]
# read json
json_data = dict()
diff --git a/scripts/signal_timing_cuts_lappd.py b/scripts/signal_timing_cuts_lappd.py
new file mode 100644
index 0000000000000000000000000000000000000000..ad5c3f78edd3ff36c05a759e358b49c07ec880bd
--- /dev/null
+++ b/scripts/signal_timing_cuts_lappd.py
@@ -0,0 +1,173 @@
+import ROOT
+import os
+import numpy as np
+import pandas as pd
+import argparse
+import json
+from matplotlib import pyplot as plt
+from ROOT import gROOT, gSystem, gInterpreter, gStyle, gPad, kRed, kAzure
+from plot_utils import prepare_canvas, prepare_figure, my_style, get_hist_contents
+
+
+# make sure the relative path for root scripts is correct
+owd = os.getcwd()
+script_dir = os.path.dirname(os.path.realpath(__file__))
+os.chdir(os.path.join(script_dir, '..'))
+print('working directory is ' + os.getcwd())
+
+# rootlogon macro
+gROOT.Macro('rootlogon.C')
+
+# the functions that process data are defined in scripts/root/dataframe_analysis.C
+func_code = open(os.path.join(script_dir, 'root', 'dataframe_analysis.C')).read()
+gInterpreter.Declare(func_code)
+
+# global style
+my_style.cd()
+bprops = dict(boxstyle='round', facecolor='wheat', alpha=0.2)
+
+# argument parser
+parser = argparse.ArgumentParser('timing cuts study')
+parser.add_argument('root_file', help='root file output from analyzer')
+parser.add_argument('json_file', help='output timing cut in json')
+parser.add_argument('-b', dest='batch', action='store_true', help='set to batch mode')
+parser.add_argument('--read-cuts', dest='read', action='store_true', help='directly use cuts defined in json file.')
+parser.add_argument('--snapshot', dest='snap', default='', type=str, help='path to save the data with trigger cuts')
+parser.add_argument('--plot-dir', dest='out_dir', default='.', type=str, help='directory to save the plot')
+parser.add_argument('--layout', dest='layout', default=os.path.join(script_dir, '..', 'database/channels_layout.json'),
+ help='json data for channels layout')
+args = parser.parse_args()
+
+# recover paths
+for attr in ['root_file', 'json_file', 'snap', 'out_dir', 'layout']:
+ setattr(args, attr, os.path.join(owd, getattr(args, attr)))
+
+os.makedirs(args.out_dir, exist_ok=True)
+
+# batch mode
+gROOT.SetBatch(args.batch)
+
+# root dataframe
+rdf = ROOT.RDataFrame('EvTree', args.root_file)
+save_list = [
+ 'ecal', 'ecal_ch'
+]
+
+# read json
+json_data = dict()
+if os.path.exists(args.json_file):
+ with open(args.json_file, 'r') as f:
+ json_data.update(json.load(f))
+
+with open(args.layout, 'r') as f:
+ channels_layout = json.load(f)
+
+
+# main function
+def timing_cuts_search(df, cuts_dict, cut_width, hbins=100):
+ for ch, cuts in cuts_dict.items():
+ search = cuts['cut']
+ ref = cuts['ref']
+ hist = df.Define('peak_time', 'unpack_time({}, true, {})'.format(ch, ref))\
+ .Histo1D(ROOT.RDF.TH1DModel('time_hist1', '', hbins, *search), 'peak_time')
+
+ pos = hist.GetBinCenter(hist.GetMaximumBin())
+ height = hist.GetMaximum()
+ if height > 0:
+ cuts_dict[ch]['cut'] = (pos - cut_width, pos + cut_width)
+ return cuts_dict
+
+
+# plot distributions with cuts
+def plot_dist_tcuts(df, canvas, pads_dict, cuts_dict, attr, hrange=(128, -256, 256), use_ref=False, hthres=0):
+ stacks, hists = [], []
+ for ch, pad in pads_dict.items():
+ cut = cuts_dict[ch]['cut']
+ ref = cuts_dict[ch]['ref'] if use_ref else '0'
+ stacks.append(ROOT.THStack('hs_' + ch, ch))
+ attr_name = '{}_{}'.format(ch, attr)
+ hists.append(
+ df.Define(attr_name, 'unpack_{}({}, true, {})'.format(attr, ch, ref))\
+ .Histo1D(ROOT.RDF.TH1DModel(attr_name + '_h', '', *hrange), attr_name)
+ )
+ hists[-1].SetFillColorAlpha(38, 0.7)
+ hists[-1].SetFillStyle(3000)
+ hists[-1].SetLineStyle(2)
+ hists[-1].SetLineColor(kAzure - 6)
+ stacks[-1].Add(hists[-1].GetPtr())
+
+ # cut peaks
+ hists.append(
+ df.Filter('{}_peak.height > {}'.format(ch, hthres))\
+ .Define(attr_name + '_cut', '{}_peak.{} - {}'.format(ch, attr, ref))\
+ .Histo1D(ROOT.RDF.TH1DModel(attr_name + '_hcut', '', *hrange), attr_name + '_cut')
+ )
+ hists[-1].SetFillColorAlpha(46, 0.7)
+ hists[-1].SetFillStyle(3000)
+ hists[-1].SetLineStyle(2)
+ hists[-1].SetLineColor(kRed + 3)
+ stacks[-1].Add(hists[-1].GetPtr())
+
+ pad.cd()
+ stacks[-1].Draw('nostack')
+ canvas.Update()
+ return stacks, hists
+
+
+
+# =============================================================================
+# MaPMT sum channel timing study
+# =============================================================================
+print('Study timing cuts for MaPMT sum channels...')
+# calorimeter (trigger) channels
+sum_channels = channels_layout['LAPPD']
+# peak search range
+if args.read:
+ sum_cuts = {c: json_data[c] for chs in sum_channels for c in chs}
+else:
+ sum_search = {c: {'cut': (-100, -50), 'ref': 'ecal.time'} for chs in sum_channels for c in chs}
+ # change sum timing search range for special cases
+ sum_cuts = timing_cuts_search(rdf, sum_search, cut_width=20)
+ json_data.update(sum_cuts)
+
+sum_height_cut = 0
+
+# apply cuts
+for ch, cut in sum_cuts.items():
+ rdf = rdf.Define('{}_peak'.format(ch), 'get_maximum_peak({}.peaks, time_cut_rel, {}, {}, {})'\
+ .format(ch, *cut['cut'], cut['ref']))
+ save_list.append('{}_peak'.format(ch))
+
+# plot timing distributions with t-cuts
+c1 = ROOT.TCanvas('sum_time', '', 1920, 1080)
+pads1 = prepare_canvas(c1, sum_channels, pad_label='MaPMT Sum Peak Time',
+ x_label='Time Rel. to ECal. (ns)', y_label='Counts')
+res1 = plot_dist_tcuts(rdf, c1, pads1, sum_cuts, 'time', hrange=(80, -160, 160), hthres=sum_height_cut, use_ref=True)
+c1.SaveAs(os.path.join(args.out_dir, 'tcuts_sum_time.png'))
+
+# plot height distributions with t-cuts
+c2 = ROOT.TCanvas('sum_height', '', 1920, 1080)
+pads2 = prepare_canvas(c2, sum_channels, pad_label='MaPMT Sum Peak Height', x_label='ADC Value', y_label='Counts')
+res2 = plot_dist_tcuts(rdf, c2, pads2, sum_cuts, 'height', hrange=(100, 0, 1000), hthres=sum_height_cut)
+c2.SaveAs(os.path.join(args.out_dir, 'tcuts_sum_height.png'))
+
+
+# =============================================================================
+# Ending
+# =============================================================================
+rdf.Report().Print()
+# save json
+if not args.read:
+ with open(args.json_file, 'w') as f:
+ json.dump(json_data, f, indent=2)
+
+# save data
+if args.snap:
+ print('Saving data snapshot to \"{}\", with columns:\n{}'.format(args.snap, save_list))
+ rdf.Snapshot('EvTree', args.snap, save_list)
+
+# this keeps the canvas
+if not args.batch:
+ print("press enter to quit")
+ input()
+
diff --git a/scripts/trigger_timing_cuts.py b/scripts/trigger_timing_cuts.py
index 554bbe03f62b3bbadbabaa77363a52ae77289aab..71e606860fd45bc35ebf5456b4da469d10fee475 100644
--- a/scripts/trigger_timing_cuts.py
+++ b/scripts/trigger_timing_cuts.py
@@ -49,7 +49,8 @@ gROOT.SetBatch(args.batch)
# root dataframe
rdf = ROOT.RDataFrame('EvTree', args.root_file)
-save_list = ['Cer{}{}_{}'.format(i, j, k) for i in np.arange(1, 5) for j in np.arange(1, 5) for k in np.arange(1, 6)]
+# save_list = ['Cer{}{}_{}'.format(i, j, k) for i in np.arange(1, 5) for j in np.arange(1, 5) for k in np.arange(1, 6)]
+save_list = ['LAPPD_{}{}'.format(l, i) for i in np.arange(1, 9) for l in 'ABCDEFGH']
# read json
json_data = dict()
@@ -125,7 +126,7 @@ else:
ecal_search = {c: {'cut': (105, 135), 'ref': '0'} for chs in ecal_channels for c in chs}
# change ecal timing search range for special cases
# ecal_search['C4']['cut'] = (100, 130)
- ecal_cuts = timing_cuts_search(rdf, ecal_search, cut_width=20)
+ ecal_cuts = timing_cuts_search(rdf, ecal_search, cut_width=10)
json_data.update(ecal_cuts)
ecal_height_cut = 0
@@ -159,6 +160,7 @@ save_list += ['ecal', 'ecal_ch']
+"""
# =============================================================================
# Scint channel timing study
# =============================================================================
@@ -199,6 +201,7 @@ rdf = rdf.Define('scint2', 'get_maximum_peak({})'.format(s2_vec))\
.Define('scint2_ch', 'std::vector<TString> ch_list{}; return ch_list[scint2.pos];'.format(s2_vec_str))\
.Filter('scint2.height > {}'.format(s2_height_cut), 'Scint2 Signal Cut')
save_list += ['scint2', 'scint2_ch']
+"""