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EIC
benchmarks
physics_benchmarks
Commits
fda769eb
Commit
fda769eb
authored
Nov 7, 2022
by
Tooba Ali
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Update benchmarks/dis/analysis/truth_reconstruction.py
parent
22265ed0
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benchmarks/dis/analysis/truth_reconstruction.py
+43
-8
43 additions, 8 deletions
benchmarks/dis/analysis/truth_reconstruction.py
with
43 additions
and
8 deletions
benchmarks/dis/analysis/truth_reconstruction.py
+
43
−
8
View file @
fda769eb
...
@@ -111,9 +111,17 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
...
@@ -111,9 +111,17 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
Y_plot
=
list
(
np
.
zeros
(
len
(
X_list
)))
Y_plot
=
list
(
np
.
zeros
(
len
(
X_list
)))
for
j
in
range
(
len
(
X_list
)):
#Repeat the following steps for each particle (pions,protons,electrons,neutrons,photons)
for
j
in
range
(
len
(
X_list
)):
#Repeat the following steps for each particle (pions,protons,electrons,neutrons,photons)
X_s
=
np
.
array
(
ak
.
flatten
(
X_list
[
j
]))
X
=
X_list
[
j
]
Y_s
=
np
.
array
(
ak
.
flatten
(
Y_list
[
j
]))
Y
=
Y_list
[
j
]
if
i
==
0
:
#Momentum ratio
X_len
=
ak
.
count
(
X
,
axis
=
None
)
Y_len
=
ak
.
count
(
Y
,
axis
=
None
)
if
X_len
>
Y_len
:
F_boolean
=
np
.
ones_like
(
Y
)
==
1
else
:
F_boolean
=
np
.
ones_like
(
X
)
==
1
X_s
=
np
.
array
(
ak
.
flatten
(
X
[
F_boolean
]))
#Filtered lists
Y_s
=
np
.
array
(
ak
.
flatten
(
Y
[
F_boolean
]))
if
i
==
0
:
#Momentum
ratio
=
np
.
array
((
ak
.
Array
(
Y_s
)
/
ak
.
Array
(
X_s
)))
ratio
=
np
.
array
((
ak
.
Array
(
Y_s
)
/
ak
.
Array
(
X_s
)))
else
:
#Angle difference
else
:
#Angle difference
ratio
=
np
.
array
((
ak
.
Array
(
Y_s
)
-
(
ak
.
Array
(
X_s
))))
ratio
=
np
.
array
((
ak
.
Array
(
Y_s
)
-
(
ak
.
Array
(
X_s
))))
...
@@ -174,8 +182,16 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
...
@@ -174,8 +182,16 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
if
i
>
0
:
#for each variable theta, phi, and eta
if
i
>
0
:
#for each variable theta, phi, and eta
for
j
in
range
(
len
(
M_list
)):
#Repeat the following steps for each particle (pions,protons,electrons,neutrons,photons)
for
j
in
range
(
len
(
M_list
)):
#Repeat the following steps for each particle (pions,protons,electrons,neutrons,photons)
M_s
=
np
.
array
(
ak
.
flatten
(
M_list
[
j
]))
X
=
X_list
[
j
]
Y
=
Y_list
[
j
]
M_mc
=
M_list
[
j
]
boolean_M
=
np
.
ones_like
(
M_mc
)
==
1
X_s
=
np
.
array
(
ak
.
flatten
(
X
[
boolean_M
]))
Y_s
=
np
.
array
(
ak
.
flatten
(
Y
[
boolean_M
]))
M_s
=
np
.
array
(
ak
.
flatten
(
M_mc
))
ratio
=
np
.
array
((
ak
.
Array
(
Y_s
)
-
(
ak
.
Array
(
X_s
))))
X_plot
[
j
]
=
M_s
X_plot
[
j
]
=
M_s
Y_plot
[
j
]
=
ratio
fig
=
plt
.
figure
()
fig
=
plt
.
figure
()
gs
=
fig
.
add_gridspec
(
3
,
2
,
wspace
=
0
)
gs
=
fig
.
add_gridspec
(
3
,
2
,
wspace
=
0
)
...
@@ -207,8 +223,15 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
...
@@ -207,8 +223,15 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
###################################################################################################
###################################################################################################
#Repeat the following steps for each variable (momentum,theta,phi,eta)
#Repeat the following steps for each variable (momentum,theta,phi,eta)
X_s
=
np
.
array
(
ak
.
flatten
(
X1
))
X_len
=
ak
.
count
(
X1
,
axis
=
None
)
Y_s
=
np
.
array
(
ak
.
flatten
(
Y1
))
Y_len
=
ak
.
count
(
Y1
,
axis
=
None
)
if
X_len
>
Y_len
:
F_boolean
=
np
.
ones_like
(
Y1
)
==
1
else
:
F_boolean
=
np
.
ones_like
(
X1
)
==
1
X_s
=
np
.
array
(
ak
.
flatten
(
X1
[
F_boolean
]))
Y_s
=
np
.
array
(
ak
.
flatten
(
Y1
[
F_boolean
]))
#Histogram
#Histogram
if
i
==
0
and
particle
in
particle_dict
.
keys
():
#Momentum in Single events
if
i
==
0
and
particle
in
particle_dict
.
keys
():
#Momentum in Single events
h
,
xedges
,
yedges
,
image
=
plt
.
hist2d
(
x
=
X_s
,
y
=
Y_s
,
bins
=
11
)
h
,
xedges
,
yedges
,
image
=
plt
.
hist2d
(
x
=
X_s
,
y
=
Y_s
,
bins
=
11
)
...
@@ -254,7 +277,19 @@ def particle_plots(boolean_particle):
...
@@ -254,7 +277,19 @@ def particle_plots(boolean_particle):
theta_rc_fil
=
ak
.
Array
(
theta_rc
[
recID
][
booll
])[
boolean_particle
]
theta_rc_fil
=
ak
.
Array
(
theta_rc
[
recID
][
booll
])[
boolean_particle
]
phi_mc_fil
=
ak
.
Array
(
phi_mc
[
simID
][
booll
])[
boolean_particle
]
phi_mc_fil
=
ak
.
Array
(
phi_mc
[
simID
][
booll
])[
boolean_particle
]
phi_rc_fil
=
ak
.
Array
(
phi_rc
[
recID
][
booll
])[
boolean_particle
]
phi_rc_fil
=
ak
.
Array
(
phi_rc
[
recID
][
booll
])[
boolean_particle
]
ratio
=
np
.
array
((
ak
.
Array
(
theta_rc_fil
)
-
(
ak
.
Array
(
theta_mc_fil
))))
theta_mc_fil_len
=
ak
.
count
(
theta_mc_fil
,
axis
=
None
)
theta_rc_fil_len
=
ak
.
count
(
theta_rc_fil
,
axis
=
None
)
if
theta_mc_fil_len
>
theta_rc_fil_len
:
F_boolean
=
np
.
ones_like
(
theta_rc_fil
)
==
1
else
:
F_boolean
=
np
.
ones_like
(
theta_mc_fil
)
==
1
#filtered lists w.r.t length
theta_mc_F
=
np
.
array
(
ak
.
flatten
(
theta_mc_fil
[
F_boolean
]))
theta_rc_F
=
np
.
array
(
ak
.
flatten
(
theta_rc_fil
[
F_boolean
]))
phi_mc_F
=
np
.
array
(
ak
.
flatten
(
phi_mc_fil
[
F_boolean
]))
phi_rc_F
=
np
.
array
(
ak
.
flatten
(
phi_rc_fil
[
F_boolean
]))
ratio
=
np
.
array
((
ak
.
Array
(
theta_rc_F
)
-
(
ak
.
Array
(
theta_mc_F
))))
fig
=
plt
.
figure
()
fig
=
plt
.
figure
()
gs
=
fig
.
add_gridspec
(
2
,
2
,
wspace
=
0.01
)
gs
=
fig
.
add_gridspec
(
2
,
2
,
wspace
=
0.01
)
...
...
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