From 98999279fb6e20e5fa38632431fec13ab1c5a1f2 Mon Sep 17 00:00:00 2001
From: Wouter Deconinck <wdconinc@gmail.com>
Date: Wed, 16 Feb 2022 20:25:19 +0000
Subject: [PATCH] imaging_ml_data.py: no more mcparticles
---
benchmarks/imaging_shower_ML/options/imaging_ml_data.py | 8 +-------
.../imaging_shower_ML/scripts/prepare_tf_dataset.py | 4 ++--
2 files changed, 3 insertions(+), 9 deletions(-)
diff --git a/benchmarks/imaging_shower_ML/options/imaging_ml_data.py b/benchmarks/imaging_shower_ML/options/imaging_ml_data.py
index 8a570bec..6bf9d7c1 100644
--- a/benchmarks/imaging_shower_ML/options/imaging_ml_data.py
+++ b/benchmarks/imaging_shower_ML/options/imaging_ml_data.py
@@ -6,7 +6,6 @@ from GaudiKernel import SystemOfUnits as units
from Configurables import ApplicationMgr, EICDataSvc, PodioInput, PodioOutput, GeoSvc
from GaudiKernel.SystemOfUnits import MeV, GeV, mm, cm, mrad
-from Configurables import Jug__Base__InputCopier_dd4pod__Geant4ParticleCollection_dd4pod__Geant4ParticleCollection_ as MCCopier
from Configurables import Jug__Digi__CalorimeterHitDigi as CalHitDigi
from Configurables import Jug__Reco__CalorimeterHitReco as CalHitReco
from Configurables import Jug__Reco__CalorimeterHitsMerger as CalHitsMerger
@@ -38,11 +37,6 @@ podev = EICDataSvc('EventDataSvc', inputs=[f.strip() for f in kwargs['input'].sp
podin = PodioInput('PodioReader', collections=['mcparticles', 'EcalBarrelHits', 'EcalBarrelScFiHits'])
podout = PodioOutput('out', filename=kwargs['output'])
-copier = MCCopier('MCCopier',
- OutputLevel=WARNING,
- inputCollection='mcparticles',
- outputCollection='mcparticles2')
-
# Central Barrel Ecal (Imaging Cal.)
becal_img_daq = dict(
dynamicRangeADC=3*MeV,
@@ -139,7 +133,7 @@ podout.outputCommands = [
]
ApplicationMgr(
- TopAlg=[podin, copier,
+ TopAlg=[podin,
becal_img_digi, becal_img_reco, becal_img_merger, becal_img_sorter,
becal_scfi_digi, becal_scfi_reco, becal_scfi_merger, becal_scfi_sorter,
becal_combiner,
diff --git a/benchmarks/imaging_shower_ML/scripts/prepare_tf_dataset.py b/benchmarks/imaging_shower_ML/scripts/prepare_tf_dataset.py
index 52b2d529..d94d1cb6 100644
--- a/benchmarks/imaging_shower_ML/scripts/prepare_tf_dataset.py
+++ b/benchmarks/imaging_shower_ML/scripts/prepare_tf_dataset.py
@@ -85,8 +85,8 @@ if __name__ == '__main__':
df.loc[:, 'rc'] = rc
df.loc[:, 'eta'] = eta
- dfm = flatten_collection(rdf, 'mcparticles2', ['genStatus', 'pdgID', 'ps.x', 'ps.y', 'ps.z', 'mass'])
- dfm.rename(columns={c: c.replace('mcparticles2.', '') for c in dfm.columns}, inplace=True)
+ dfm = flatten_collection(rdf, 'mcparticles', ['genStatus', 'pdgID', 'ps.x', 'ps.y', 'ps.z', 'mass'])
+ dfm.rename(columns={c: c.replace('mcparticles.', '') for c in dfm.columns}, inplace=True)
# selete incident particles
dfm = dfm[dfm['genStatus'].isin([0, 1])]
# NOTE: assumed single particles
--
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