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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/AvgStdevMetadataFactory.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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+# 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.
+
+import math
+
+from AvgStdevMetadata import AvgStdevMetadata
+
+
+class AvgStdevMetadataFactory(object):
+ """Class factory which creates avg,stdev metadata from data."""
+
+ @staticmethod
+ def from_data(values):
+ """Return new metadata object fitting the values.
+
+ :param values: Run values to be processed.
+ :type values: Iterable of float or of AvgStdevMetadata
+ :returns: The metadata matching the values.
+ :rtype: AvgStdevMetadata
+ """
+ sum_0 = 0
+ sum_1 = 0.0
+ sum_2 = 0.0
+ for value in values:
+ if isinstance(value, AvgStdevMetadata):
+ sum_0 += value.size
+ sum_1 += value.avg * value.size
+ sum_2 += value.stdev * value.stdev * value.size
+ sum_2 += value.avg * value.avg * value.size
+ else: # The value is assumed to be float.
+ sum_0 += 1
+ sum_1 += value
+ sum_2 += value * value
+ if sum_0 < 1:
+ return AvgStdevMetadata()
+ avg = sum_1 / sum_0
+ stdev = math.sqrt(sum_2 / sum_0 - avg * avg)
+ ret_obj = AvgStdevMetadata(size=sum_0, avg=avg, stdev=stdev)
+ return ret_obj