From fda769eb948c4c48f0985dd11e9dd788a0204df6 Mon Sep 17 00:00:00 2001
From: Tooba Ali <alit1@myumanitoba.ca>
Date: Mon, 7 Nov 2022 23:13:10 +0000
Subject: [PATCH] Update benchmarks/dis/analysis/truth_reconstruction.py
---
.../dis/analysis/truth_reconstruction.py | 51 ++++++++++++++++---
1 file changed, 43 insertions(+), 8 deletions(-)
diff --git a/benchmarks/dis/analysis/truth_reconstruction.py b/benchmarks/dis/analysis/truth_reconstruction.py
index 5f2003d5..53b74a37 100644
--- a/benchmarks/dis/analysis/truth_reconstruction.py
+++ b/benchmarks/dis/analysis/truth_reconstruction.py
@@ -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)))
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]))
- Y_s = np.array(ak.flatten(Y_list[j]))
- if i == 0: #Momentum ratio
+ X = X_list[j]
+ Y = Y_list[j]
+ 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)))
else: #Angle difference
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
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)
- 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
+ Y_plot[j] = ratio
fig = plt.figure()
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
###################################################################################################
#Repeat the following steps for each variable (momentum,theta,phi,eta)
- X_s = np.array(ak.flatten(X1))
- Y_s = np.array(ak.flatten(Y1))
+ X_len = ak.count(X1,axis=None)
+ 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
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)
@@ -250,11 +273,23 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
def particle_plots(boolean_particle):
#filtered lists w.r.t the particle
- theta_mc_fil = ak.Array(theta_mc[simID][booll])[boolean_particle]
+ theta_mc_fil = ak.Array(theta_mc[simID][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_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()
gs = fig.add_gridspec(2, 2, wspace=0.01)
--
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