diff options
author | Vratko Polak <vrpolak@cisco.com> | 2018-06-08 18:07:35 +0200 |
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committer | Tibor Frank <tifrank@cisco.com> | 2018-06-11 08:30:21 +0000 |
commit | beeb2acb9ac153eaa54983bea46a76d596168965 (patch) | |
tree | 0465617b135a2e64693265969c48ff466db3d287 /resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py | |
parent | 3dcef45002a1b82c4503ec590d680950930fa193 (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>
Diffstat (limited to 'resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py')
-rw-r--r-- | resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py b/resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py new file mode 100644 index 0000000000..26db758ea8 --- /dev/null +++ b/resources/tools/presentation/new/jumpavg/AbstractGroupClassifier.py @@ -0,0 +1,33 @@ +# 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 |