From cb4b04fcf3cffd19a6cc5a2dacdb56b164ca11e5 Mon Sep 17 00:00:00 2001
From: Nikolai Hartmann <Nikolai.Hartmann@physik.uni-muenchen.de>
Date: Tue, 8 May 2018 13:17:49 +0200
Subject: [PATCH] Rename project class to ClassificationProject
---
__init__.py | 3 +++
compare.py | 16 ++++++++--------
toolkit.py | 36 ++++++++++++++++++------------------
3 files changed, 29 insertions(+), 26 deletions(-)
create mode 100644 __init__.py
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..2702f3d
--- /dev/null
+++ b/__init__.py
@@ -0,0 +1,3 @@
+from toolkit import ClassificationProject
+from compare import overlay_ROC, overlay_loss
+
diff --git a/compare.py b/compare.py
index 4f2332d..f0a2a3d 100755
--- a/compare.py
+++ b/compare.py
@@ -7,7 +7,7 @@ import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, auc
-from toolkit import KerasROOTClassification
+from toolkit import ClassificationProject
"""
A few functions to compare different setups
@@ -76,14 +76,14 @@ if __name__ == "__main__":
identifiers = ["DatasetNumber", "EventNumber"],
step_bkg = 100)
- example1 = KerasROOTClassification("test_sgd",
- optimizer="SGD",
- optimizer_opts=dict(lr=1000., decay=1e-6, momentum=0.9),
- **data_options)
+ example1 = ClassificationProject("test_sgd",
+ optimizer="SGD",
+ optimizer_opts=dict(lr=1000., decay=1e-6, momentum=0.9),
+ **data_options)
- example2 = KerasROOTClassification("test_adam",
- optimizer="Adam",
- **data_options)
+ example2 = ClassificationProject("test_adam",
+ optimizer="Adam",
+ **data_options)
if not os.path.exists("outputs/test_sgd/scores_test.h5"):
diff --git a/toolkit.py b/toolkit.py
index 7dc4d20..271989d 100755
--- a/toolkit.py
+++ b/toolkit.py
@@ -41,7 +41,7 @@ K.set_session(session)
import ROOT
-class KerasROOTClassification(object):
+class ClassificationProject(object):
"""Simple framework to load data from ROOT TTrees and train Keras
neural networks for classification according to some global settings.
@@ -751,9 +751,9 @@ def create_setter(dataset_name):
return setx
# define getters and setters for all datasets
-for dataset_name in KerasROOTClassification.dataset_names:
- setattr(KerasROOTClassification, dataset_name, property(create_getter(dataset_name),
- create_setter(dataset_name)))
+for dataset_name in ClassificationProject.dataset_names:
+ setattr(ClassificationProject, dataset_name, property(create_getter(dataset_name),
+ create_setter(dataset_name)))
if __name__ == "__main__":
@@ -764,21 +764,21 @@ if __name__ == "__main__":
filename = "/project/etp4/nhartmann/trees/allTrees_m1.8_NoSys.root"
- c = KerasROOTClassification("test4",
- signal_trees = [(filename, "GG_oneStep_1705_1105_505_NoSys")],
- bkg_trees = [(filename, "ttbar_NoSys"),
- (filename, "wjets_Sherpa221_NoSys")
- ],
- optimizer="Adam",
- #optimizer="SGD",
- #optimizer_opts=dict(lr=100., decay=1e-6, momentum=0.9),
+ c = ClassificationProject("test4",
+ signal_trees = [(filename, "GG_oneStep_1705_1105_505_NoSys")],
+ bkg_trees = [(filename, "ttbar_NoSys"),
+ (filename, "wjets_Sherpa221_NoSys")
+ ],
+ optimizer="Adam",
+ #optimizer="SGD",
+ #optimizer_opts=dict(lr=100., decay=1e-6, momentum=0.9),
earlystopping_opts=dict(monitor='val_loss',
- min_delta=0, patience=2, verbose=0, mode='auto'),
- selection="lep1Pt<5000", # cut out a few very weird outliers
- branches = ["met", "mt"],
- weight_expr = "eventWeight*genWeight",
- identifiers = ["DatasetNumber", "EventNumber"],
- step_bkg = 100)
+ min_delta=0, patience=2, verbose=0, mode='auto'),
+ selection="lep1Pt<5000", # cut out a few very weird outliers
+ branches = ["met", "mt"],
+ weight_expr = "eventWeight*genWeight",
+ identifiers = ["DatasetNumber", "EventNumber"],
+ step_bkg = 100)
np.random.seed(42)
c.train(epochs=20)
--
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