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from xerawdp_helpers import * # helper functions for retrieving xerawdp data
from Kr83m_Basic import *
import numpy as np
import pandas as pd
import glob
%matplotlib inline
import matplotlib.pyplot as plt
from IPython.display import display, Image
import hax
hax.init(main_data_paths=['/project/lgrandi/xenon100/archive/root/merged/xenon100/run_14_pax4.1.2/',
'/project/lgrandi/tunnell/run_14/paxProcessed_kr83mDiffusion/'],
raw_data_local_path='/project/lgrandi/tunnell/')
#hax.ipython.code_hider()
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datasets_pax = ['xe100_150413_1839','xe100_150414_1535',
'xe100_150419_1611','xe100_150420_0304',
'xe100_150420_1809']
data = hax.minitrees.load(datasets_pax, treemakers=Kr83m_Basic)
print(len(data.values))
In [3]:
datasets_pax_new = ['xe100_150413_1839','xe100_150414_1535','xe100_150415_1749',
'xe100_150416_1832','xe100_150419_1611','xe100_150420_0304',
'xe100_150420_1809']
for i in range(len(datasets_pax_new)):
datasets_pax_new[i] += '_pax4.9.1'
data = hax.minitrees.load(datasets_pax_new, treemakers=Kr83m_Basic)
print(len(data.values))
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# from 2015 Kr83m diffusion-mode data
datasets_xerawdp = ['xe100_150413_1839','xe100_150414_1535','xe100_150415_1749',
'xe100_150416_1832','xe100_150419_1611','xe100_150420_0304',
'xe100_150420_1809']
# xerawdp path
xerawdpPath = '/project/lgrandi/tunnell/run_14/NewNN/'
# get xerawdp tree, apply event restrictions, and retrieve desirable data
# see xerawdp_helpers.py for details
xerawdpTree = load_xerawdp_tree(datasets_xerawdp, xerawdpPath)
print(xerawdpTree.GetEntries())
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# from 2015 Kr83m diffusion-mode data
datasets_xerawdp = ['xe100_150413_1839','xe100_150414_1535','xe100_150415_1749',
'xe100_150416_1832','xe100_150419_1611','xe100_150420_0304',
'xe100_150420_1809']
# xerawdp path
xerawdpPath = '/project/lgrandi/tunnell/run_14/NewNN/'
# get xerawdp tree, apply event restrictions, and retrieve desirable data
# see xerawdp_helpers.py for details
xerawdpTree = load_xerawdp_tree(datasets_xerawdp, xerawdpPath)
if 'xerawdp_krRestricted.pkl' not in glob.glob('*'):
df_xerawdp = build_xerawdp_df(xerawdpTree)
df_xerawdp.to_pickle('xerawdp_krRestricted.pkl')
else:
df_xerawdp = pd.read_pickle('xerawdp_krRestricted.pkl')
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n = 0
for i in range(xerawdpTree.GetEntries()):
xerawdpTree.GetEntry(i)
if xerawdpTree.NbS1Peaks < 2 or xerawdpTree.S1sTot[0] == 0 or xerawdpTree.NbS2Peaks < 1:
continue
if xerawdpTree.S1sCoin[0] < 2 or xerawdpTree.S1sCoin[1] < 2:
continue
if xerawdpTree.cS2sTot[0] < 150:
continue
if xerawdpTree.S1sLeftEdge[1]-xerawdpTree.S1sRightEdge[0] <= 0:
continue
dt_s1 = (xerawdpTree.S1sPeak[1]-xerawdpTree.S1sPeak[0])*10
if dt_s1 < 400 or dt_s1 > 2000:
continue
if xerawdpTree.NbS2Peaks > 1 and xerawdpTree.cS2sTot[1] > 150:
continue
if xerawdpTree.S2sRightEdge[0]-xerawdpTree.S2sLeftEdge[0] < xerawdpTree.S1sRightEdge[1]-xerawdpTree.S1sLeftEdge[0]:
continue
if xerawdpTree.S1sTot[1]/xerawdpTree.S1sTot[0] < 0.1 or xerawdpTree.S1sTot[1]/xerawdpTree.S1sTot[0] > 1.0:
continue
n += 1
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print(n)
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print(xerawdpTree.GetEntries())
203805/5093213 with xerawdpTree.S1sTot[0] <= 0, same for just xerawdpTree.S1sTot[0] == 0
342335/5093213 with dt in [400,2000] ns
Data File | Xerawdp Events | Pax 4.1 Events | Pax 4.9 Partial Events |
---|---|---|---|
xe100_150413_1839 | 961512 | 938512 | 561512 |
xe100_150414_1535 | 854036 | 820036 | 821036 |
xe100_150415_1749 | 1172055 | N/A | 585000 |
xe100_150416_1832 | 1148282 | N/A | 473282 |
xe100_150419_1611 | 500000 | 486000 | 358000 |
xe100_150420_0304 | 405328 | 389328 | 404328 |
xe100_150420_1809 | 52000 | 104000 | 52000 |
Total | 5093213 | 2737876 | 3255158 |
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