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>

1 files changed, 49 insertions, 0 deletions

diff --git a/resources/tools/presentation/new/jumpavg/AvgStdevMetadataFactory.py b/resources/tools/presentation/new/jumpavg/AvgStdevMetadataFactory.py
new file mode 100644
index 0000000000..d7d0517a57
--- /dev/null
+++ b/resources/tools/presentation/new/jumpavg/AvgStdevMetadataFactory.py
@@ -0,0 +1,49 @@
+# 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