From 63caa09664debc5edce658346b2bbc5bf8a2eb97 Mon Sep 17 00:00:00 2001
From: Chao Peng <cpeng@anl.gov>
Date: Tue, 22 Nov 2022 02:14:18 +0000
Subject: [PATCH] Fix some typos for imaging ML benchmark
---
benchmarks/imaging_shower_ML/config.yml | 2 +-
benchmarks/imaging_shower_ML/scripts/epcut_scan.py | 4 ++--
benchmarks/imaging_shower_ML/scripts/ml_training.py | 5 +++--
3 files changed, 6 insertions(+), 5 deletions(-)
diff --git a/benchmarks/imaging_shower_ML/config.yml b/benchmarks/imaging_shower_ML/config.yml
index 5d4429b8..bb410998 100644
--- a/benchmarks/imaging_shower_ML/config.yml
+++ b/benchmarks/imaging_shower_ML/config.yml
@@ -7,7 +7,7 @@ ml_shower:epi_separation:
- |
if [[ ${DETECTOR} =~ athena
|| ${DETECTOR} =~ ecce && ${DETECTOR_CONFIG} =~ imaging ]] ; then
- pip3 install -r rbenchmarks/imaging_shower_ML/equirements.txt
+ pip3 install -r benchmarks/imaging_shower_ML/requirements.txt
python3 benchmarks/imaging_shower_ML/run_benchmark.py -t imcal_epi -n 1000 --pmin 1.8 --pmax 2.2 --nocut-samples
fi
diff --git a/benchmarks/imaging_shower_ML/scripts/epcut_scan.py b/benchmarks/imaging_shower_ML/scripts/epcut_scan.py
index 30dddbe4..4340f31f 100644
--- a/benchmarks/imaging_shower_ML/scripts/epcut_scan.py
+++ b/benchmarks/imaging_shower_ML/scripts/epcut_scan.py
@@ -1,7 +1,7 @@
"""
A script to scan the optimized cut on layer and E/p.
- It scan all the possible ScFi layers (20 in the EPIC brycecanyon configuration)
- The results give the best cut (highest pion rejection) on [layer, E/p] with a targeted electron efficiency
+ It groups [event, layer] and scan the E/p cut layer-wise (e.g., EPIC brycecanyon configuration has 16 ScFi layers)
+ The best 2D cut (highest rejection power) on [layer, E/p] that satisfies required effiiency will be given
Chao Peng (ANL)
2022/11/13
diff --git a/benchmarks/imaging_shower_ML/scripts/ml_training.py b/benchmarks/imaging_shower_ML/scripts/ml_training.py
index 6955ac24..5720dc19 100644
--- a/benchmarks/imaging_shower_ML/scripts/ml_training.py
+++ b/benchmarks/imaging_shower_ML/scripts/ml_training.py
@@ -131,7 +131,7 @@ if __name__ == '__main__':
if args.seed > 0:
np.random.seed(args.seed)
- tf.random.seed(args.seed)
+ tf.random.set_seed(args.seed)
df = pd.read_hdf(args.data_store, key=imcal_info.ml_data_key)
# NOTE: assumed event index is exactly the same as df
@@ -274,7 +274,8 @@ if __name__ == '__main__':
),
test=OrderedDict(
sample_size=count_pid_labels(ytest, pids),
- efficiencies=OrderedDict([(labels.name, eff) for labels, eff in effs])
+ efficiencies=OrderedDict([(labels.name, eff) for labels, eff in effs]),
+ rejections=OrderedDict([(labels.name, 1./eff) for labels, eff in effs]),
),
)
res_json = json.dumps(result, indent=4, cls=NpEncoder)
--
GitLab