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authorVratko Polak <vrpolak@cisco.com>2018-06-08 18:07:35 +0200
committerTibor Frank <tifrank@cisco.com>2018-06-11 08:30:21 +0000
commitbeeb2acb9ac153eaa54983bea46a76d596168965 (patch)
tree0465617b135a2e64693265969c48ff466db3d287 /resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py
parent3dcef45002a1b82c4503ec590d680950930fa193 (diff)
CSIT-1110: Integrate anomaly detection into PAL
+ Keep the original detection, + add the new one as subdirectory (both in source and in rendered tree). - The new detection is not rebased over "Add dpdk mrr tests to trending". New detection features: + Do not remove (nor detect) outliers. + Trend line shows the constant average within a group. + Anomaly circles are placed at the changed average. + Small bias against too similar averages. + Should be ready for moving the detection library out to pip. Change-Id: I7ab1a92b79eeeed53ba65a071b1305e927816a89 Signed-off-by: Vratko Polak <vrpolak@cisco.com>
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diff --git a/resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py b/resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py
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+# Copyright (c) 2018 Cisco and/or its affiliates.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at:
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from abc import ABCMeta, abstractmethod
+
+
+class AbstractGroupClassifier(object):
+
+ __metaclass__ = ABCMeta
+
+ @abstractmethod
+ def classify(self, values):
+ """Divide values into consecutive groups with metadata.
+
+ The metadata does not need to follow any specific rules,
+ although progression/regression/outlier description would be fine.
+
+ :param values: Sequence of runs to classify.
+ :type values: Iterable of float or of AvgStdevMetadata
+ :returns: Classified groups
+ :rtype: Iterable of RunGroup
+ """
+ pass