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S2PatternLikelihood cut for SR2 DEC analysis #195

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S2PatternLikelihood cut for SR2 DEC analysis #195

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74 changes: 74 additions & 0 deletions lax/lichens/sciencerun2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -276,6 +276,80 @@ def pre(self, df):
# Contact: Jingqiang
S2PatternLikelihood = postsr1.S2PatternLikelihood

# S2PatternLikelihood cut for SR2 DEC analysis
# Contact: Alex
class S2PatternLikelihoodSR2DEC(StringLichen):
"""
Extended S2PatternLikelihood cut for SR2 DEC analysis (from 0 to 500 keVee).
Wiki note: xenon:xenon1t:dec:s2patternlikelihoodsr2dec
Contact: Alexander Bismark <[email protected]>
"""
version = 1

def pre(self, df):
def lin(s2, *par):
a, b = par
return a * s2 + b

phi1=4
phi2=10
phi3=16
phi4=22
phi5=22

# Load parameters
params_load_a = np.load('/dali/lgrandi/abismark/XENON1T/DEC_SR2/s2patternlikelihoodcut_he_r_phi_params_after18836_v2.npy')
params_load_b = np.load('/dali/lgrandi/abismark/XENON1T/DEC_SR2/s2patternlikelihoodcut_he_r_phi_params_before18836_v2.npy')
# Reshape parameters
params_a=[params_load_a[:phi1], params_load_a[phi1:phi1+phi2],
params_load_a[phi1+phi2:phi1+phi2+phi3], params_load_a[phi1+phi2+phi3:phi1+phi2+phi3+phi4],
params_load_a[phi1+phi2+phi3:phi1+phi2+phi3+phi4+phi5]]
params_b=[params_load_b[:phi1], params_load_b[phi1:phi1+phi2],
params_load_b[phi1+phi2:phi1+phi2+phi3], params_load_b[phi1+phi2+phi3:phi1+phi2+phi3+phi4],
params_load_b[phi1+phi2+phi3:phi1+phi2+phi3+phi4+phi5]]

r_here = 'r_3d_nn_tf'
phi_here = 'phi_3d_nn_tf'
df.loc[:,phi_here] = np.arccos(df.x_3d_nn_tf/df.r_3d_nn_tf)*np.sign(df.y_3d_nn_tf)
df.loc[:,'s2_top'] = df.s2 * df.s2_area_fraction_top
df_list=[]
R = np.linspace(0, 47+(47/4), 5+1)
for i in range(len(R)-1):
n = [phi1,phi2,phi3,phi4,phi5][i]
td = 2*np.pi/n
for j in range(n):
tmin, tmax, rmin, rmax = j*td-np.pi, j*td-np.pi+td, R[i], R[i+1]
box_cut = ((df[r_here]>rmin)&(df[r_here]<rmax)
&(df[phi_here]>tmin)&(df[phi_here]<tmax))
df_box_cut = df[box_cut]
a_here_after18836 = params_a[i][j][0]*np.ones(len(df[box_cut]))
b_here_after18836 = params_a[i][j][1]*np.ones(len(df[box_cut]))
a_here_before18836 = params_b[i][j][0]*np.ones(len(df[box_cut]))
b_here_before18836 = params_b[i][j][1]*np.ones(len(df[box_cut]))
df_box_cut.loc[:,'CutS2PatternLikelihoodHE_a_after18836'] = a_here_after18836
df_box_cut.loc[:,'CutS2PatternLikelihoodHE_b_after18836'] = b_here_after18836
df_box_cut.loc[:,'CutS2PatternLikelihoodHE_a_before18836'] = a_here_before18836
df_box_cut.loc[:,'CutS2PatternLikelihoodHE_b_before18836'] = b_here_before18836

df_list.append(df_box_cut)
del df_box_cut; del box_cut
del df
df=pd.concat(df_list)

return df

params_low_after18836 = (-387.119859, 388.32614412, 0.99968193, 145.56507149)
params_low_before18836 = (-368.31852913, 369.74654415, 0.99959666, 136.19160986)

string = (" ((run_number >= 18836)&\
(((s2_pattern_fit<\
CutS2PatternLikelihoodHE_a_after18836*s2_top+CutS2PatternLikelihoodHE_b_after18836) & (s2_top >5000)) \
| ((s2_pattern_fit < %.8f*s2_top + %.8f*s2_top**%.8f + %.8f) & (s2_top <= 5000) )))"%(params_low_after18836)+" | \
((run_number < 18836)&\
(((s2_pattern_fit<\
CutS2PatternLikelihoodHE_a_before18836*s2_top+CutS2PatternLikelihoodHE_b_before18836) & (s2_top >5000)) \
| ((s2_pattern_fit < %.8f*s2_top + %.8f*s2_top**%.8f + %.8f) & (s2_top <= 5000) )))"%(params_low_before18836))


##
# S1 quality cuts
Expand Down