X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fnew%2Futils.py;h=a688928cda22d96142f3d43ac5a744a41de7f7d9;hp=83f4f6249b9d78fb2a9a6055ebb629d2fd01d790;hb=0e8d8a59fd6b8477b17a9222a5cfb0d94d24ff22;hpb=6928c2b1620e5d020a19e944f416df6a1f4b85ad

diff --git a/resources/tools/presentation/new/utils.py b/resources/tools/presentation/new/utils.py
index 83f4f6249b..a688928cda 100644
--- a/resources/tools/presentation/new/utils.py
+++ b/resources/tools/presentation/new/utils.py
@@ -211,17 +211,19 @@ def archive_input_data(spec):
 def classify_anomalies(data):
     """Process the data and return anomalies and trending values.
 
-    Gathers data into groups with common trend value.
-    Decorates first value in the group to be an outlier, regression,
-    normal or progression.
+    Gather data into groups with average as trend value.
+    Decorate values within groups to be normal,
+    the first value of changed average as a regression, or a progression.
 
     :param data: Full data set with unavailable samples replaced by nan.
     :type data: pandas.Series
     :returns: Classification and trend values
     :rtype: 2-tuple, list of strings and list of floats
     """
-    bare_data = [sample for _, sample in data.iteritems()
-                 if not np.isnan(sample)]
+    # Nan mean something went wrong.
+    # Use 0.0 to cause that being reported as a severe regression.
+    bare_data = [0.0 if np.isnan(sample) else sample
+                 for _, sample in data.iteritems()]
     # TODO: Put analogous iterator into jumpavg library.
     groups = BitCountingClassifier.classify(bare_data)
     groups.reverse()  # Just to use .pop() for FIFO.