From 778a981dea833bd76b02008abd91278b505ad7c5 Mon Sep 17 00:00:00 2001
From: Nikolai Hartmann <nikolai.hartmann@gmx.de>
Date: Mon, 22 Oct 2018 10:52:54 +0200
Subject: [PATCH] scale and shift example data for tests randomly
---
test/test_toolkit.py | 14 ++++++++++++++
1 file changed, 14 insertions(+)
diff --git a/test/test_toolkit.py b/test/test_toolkit.py
index 15d148b..ecd3aa2 100644
--- a/test/test_toolkit.py
+++ b/test/test_toolkit.py
@@ -8,12 +8,22 @@ from keras.layers import GRU
from KerasROOTClassification import ClassificationProject, ClassificationProjectRNN
def create_dataset(path):
+
+ # create example dataset with (low-weighted) noise added
X, y = make_classification(n_samples=10000, random_state=1)
X2 = np.random.normal(size=20*10000).reshape(-1, 20)
y2 = np.concatenate([np.zeros(5000), np.ones(5000)])
X = np.concatenate([X, X2])
y = np.concatenate([y, y2])
w = np.concatenate([np.ones(10000), 0.01*np.ones(10000)])
+
+ # shift and scale randomly (to check if transformation is working)
+ shift = np.random.rand(20)*100
+ scale = np.random.rand(20)*1000
+ X *= scale
+ X += shift
+
+ # write to root files
branches = ["var_{}".format(i) for i in range(len(X[0]))]
df = pd.DataFrame(X, columns=branches)
df["class"] = y
@@ -41,6 +51,8 @@ def test_ClassificationProject(tmp_path):
nodes=128,
)
c.train(epochs=200)
+ c.plot_all_inputs()
+ c.plot_loss()
assert min(c.history.history["val_loss"]) < 0.18
@@ -71,4 +83,6 @@ def test_ClassificationProjectRNN(tmp_path):
)
assert sum([isinstance(layer, GRU) for layer in c.model.layers]) == 2
c.train(epochs=200)
+ c.plot_all_inputs()
+ c.plot_loss()
assert min(c.history.history["val_loss"]) < 0.18
--
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