From 8be7b2f2a09afd142076fc36c79bef58813b3a70 Mon Sep 17 00:00:00 2001
From: Nikolai Hartmann <Nikolai.Hartmann@physik.uni-muenchen.de>
Date: Mon, 30 Apr 2018 15:11:01 +0200
Subject: [PATCH] trying ...
---
toolkit.py | 54 ++++++++++++++++++++++++++++++++++++++++++++++--------
1 file changed, 46 insertions(+), 8 deletions(-)
diff --git a/toolkit.py b/toolkit.py
index 9904ec7..822d71c 100755
--- a/toolkit.py
+++ b/toolkit.py
@@ -9,7 +9,7 @@ import logging
logger = logging.getLogger("KerasROOTClassification")
logger.addHandler(logging.NullHandler())
-from root_numpy import tree2array, rec2array
+from root_numpy import tree2array, rec2array, array2root
import numpy as np
import pandas as pd
import h5py
@@ -418,10 +418,38 @@ class KerasROOTClassification(object):
- def evaluate(self):
- pass
-
- def write_friend_tree(self):
+ def evaluate(self, x_eval):
+ logger.debug("Evaluate score for {}".format(x_eval))
+ x_eval = self.scaler.transform(x_eval)
+ logger.debug("Evaluate for transformed array: {}".format(x_eval))
+ return self.model.predict(x_eval)
+
+
+ def write_friend_tree(self, score_name,
+ source_filename, source_treename,
+ target_filename, target_treename,
+ batch_size=100000):
+ f = ROOT.TFile.Open(source_filename)
+ tree = f.Get(source_treename)
+ entries = tree.GetEntries()
+ if os.path.exists(target_filename):
+ raise IOError("{} already exists, if you want to recreate it, delete it first".format(target_filename))
+ for start in range(0, entries, batch_size):
+ logger.debug("Loading next batch")
+ x_eval = rec2array(tree2array(tree,
+ branches=self.branches,
+ start=start, stop=start+batch_size))
+ scores = np.array(self.evaluate(x_eval), dtype=[(score_name, np.float64)])
+ print(len(scores))
+ print(scores)
+ if start == 0:
+ mode = "recreate"
+ else:
+ mode = "update"
+ logger.debug("Write to root file")
+ array2root(scores, target_filename, treename=target_treename, mode=mode)
+
+ def write_all_friend_trees(self):
pass
@@ -561,7 +589,7 @@ if __name__ == "__main__":
logging.basicConfig()
logging.getLogger("KerasROOTClassification").setLevel(logging.INFO)
- #logging.getLogger("KerasROOTClassification").setLevel(logging.DEBUG)
+ logging.getLogger("KerasROOTClassification").setLevel(logging.DEBUG)
filename = "/project/etp4/nhartmann/trees/allTrees_m1.8_NoSys.root"
@@ -582,5 +610,15 @@ if __name__ == "__main__":
c.load()
#c.train(epochs=20)
c.plot_ROC()
- # c.plot_loss()
- # c.plot_accuracy()
+ c.plot_loss()
+ c.plot_accuracy()
+
+ c.write_friend_tree("test4_score",
+ source_filename=filename, source_treename="GG_oneStep_1705_1105_505_NoSys",
+ target_filename="friend.root", target_treename="test4_score")
+
+ np.random.seed(1234)
+
+ c.write_friend_tree("test4_score",
+ source_filename=filename, source_treename="ttbar_NoSys",
+ target_filename="friend_ttbar_NoSys.root", target_treename="test4_score")
--
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