From a0c31bdc97fd97c89460a5c6bee0d56c16452fbc Mon Sep 17 00:00:00 2001
From: Nikolai Hartmann <Nikolai.Hartmann@physik.uni-muenchen.de>
Date: Wed, 9 May 2018 10:49:53 +0200
Subject: [PATCH] adding README
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+# KerasROOTClassification
+
+This is an attempt to simplify the training of Keras models from ROOT TTree input.
+
+The recommended usage is to put this module in your python path and
+create run scripts to define and train your model.
+
+For example:
+
+```python
+import numpy as np
+import logging
+
+from KerasROOTClassification import ClassificationProject
+
+logging.basicConfig()
+logging.getLogger("KerasROOTClassification").setLevel(logging.INFO)
+
+c = ClassificationProject("my_project", # this will also be the name of the project directory
+ signal_trees = [(filename1, treename1)],
+ bkg_trees = [(filename2, treename2),
+ (filename3, treename3),
+ ],
+ optimizer="Adam",
+ selection="some-selection-expression",
+ branches = ["var1", "var2", "var3"],
+ weight_expr = "some-weight-expression",
+ identifiers = ["var4", "var5"], # variables that identify which events were used for training
+ step_bkg = 10, # take every 10th bkg event for training
+ step_sig = 2, # take every second sig event for training
+)
+
+c.train(epochs=20)
+```
+
+Previously created projects can be inspected in iypthon like
+
+```
+ipython -i -m KerasROOTClassification.browse <project-dir>
+```
+
+# Conda setup
+
+An example for a mini conda setup that contains the nescessary packages:
+
+```sh
+conda install keras pandas matplotlib scikit-learn pydot graphviz jupyter
+pip install root_numpy
+```
--
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