Refactor jumpavg to be more readable and usable

This is the python3 change, the python2 is still used for testing bisect.

+ New version is 0.2.0 due to amount o API changes.
+ Jumpavg is now part of CSIT resource package tree.
+ Perpatch migrated to new jumpavg.
- PAL NOT updated (the update moved to a different Change).

Change-Id: I7d7a8bf8a411196c20c2a40a8c64478d6709bc07
Signed-off-by: Vratko Polak <vrpolak@cisco.com>

24 files changed, 787 insertions, 789 deletions

diff --git a/PyPI/jumpavg/jumpavg b/PyPI/jumpavg/jumpavg
new file mode 120000
index 0000000000..df32002d6b
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg
@@ -0,0 +1 @@
+../../resources/libraries/python/jumpavg
\ No newline at end of file
diff --git a/PyPI/jumpavg/jumpavg/AbstractGroupClassifier.py b/PyPI/jumpavg/jumpavg/AbstractGroupClassifier.py
deleted file mode 100644
index 2612b009da..0000000000
--- a/PyPI/jumpavg/jumpavg/AbstractGroupClassifier.py
+++ /dev/null
@@ -1,40 +0,0 @@
-# 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.
-
-"""Module holding AbstractGroupClassifier class."""
-
-from abc import ABCMeta, abstractmethod
-
-
-class AbstractGroupClassifier(object):
-    """Abstract class defining API for classifier.
-
-    The classifier is an object with classify() method
-    which divides data into groups containing metadata.
-    """
-
-    __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
diff --git a/PyPI/jumpavg/jumpavg/AbstractGroupMetadata.py b/PyPI/jumpavg/jumpavg/AbstractGroupMetadata.py
deleted file mode 100644
index 3235dbd485..0000000000
--- a/PyPI/jumpavg/jumpavg/AbstractGroupMetadata.py
+++ /dev/null
@@ -1,42 +0,0 @@
-# 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.
-
-"""Module holding AbstractGroupMetadata class."""
-
-from abc import ABCMeta, abstractmethod
-
-
-class AbstractGroupMetadata(object):
-    """Abstract classdefining API for metadata.
-
-    At this level, only __str__() and __repr() methods are required."""
-
-    __metaclass__ = ABCMeta
-
-    @abstractmethod
-    def __str__(self):
-        """Return string with human readable description of the group.
-
-        :returns: Readable description.
-        :rtype: str
-        """
-        pass
-
-    @abstractmethod
-    def __repr__(self):
-        """Return string executable as Python constructor call.
-
-        :returns: Executable constructor call.
-        :rtype: str
-        """
-        pass
diff --git a/PyPI/jumpavg/jumpavg/AvgStdevMetadata.py b/PyPI/jumpavg/jumpavg/AvgStdevMetadata.py
deleted file mode 100644
index efc1a90cd4..0000000000
--- a/PyPI/jumpavg/jumpavg/AvgStdevMetadata.py
+++ /dev/null
@@ -1,54 +0,0 @@
-# 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.
-
-"""Module for holding AvgStdevMetadata class."""
-
-from AbstractGroupMetadata import AbstractGroupMetadata
-
-
-class AvgStdevMetadata(AbstractGroupMetadata):
-    """Class for metadata specifying the average and standard deviation."""
-
-    def __init__(self, size=0, avg=0.0, stdev=0.0):
-        """Construct the metadata by setting the values needed.
-
-        The values are sanitized, so faulty callers to not cause math errors.
-
-        :param size: Number of values participating in this group.
-        :param avg: Population average of the participating sample values.
-        :param stdev: Population standard deviation of the sample values.
-        :type size: int
-        :type avg: float
-        :type stdev: float
-        """
-        self.size = size if size >= 0 else 0
-        self.avg = avg if size >= 1 else 0.0
-        self.stdev = stdev if size >= 2 else 0.0
-
-    def __str__(self):
-        """Return string with human readable description of the group.
-
-        :returns: Readable description.
-        :rtype: str
-        """
-        return "size={size} avg={avg} stdev={stdev}".format(
-            size=self.size, avg=self.avg, stdev=self.stdev)
-
-    def __repr__(self):
-        """Return string executable as Python constructor call.
-
-        :returns: Executable constructor call.
-        :rtype: str
-        """
-        return "AvgStdevMetadata(size={size},avg={avg},stdev={stdev})".format(
-            size=self.size, avg=self.avg, stdev=self.stdev)
diff --git a/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py b/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py
deleted file mode 100644
index 25bc600aeb..0000000000
--- a/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py
+++ /dev/null
@@ -1,54 +0,0 @@
-# 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.
-
-"""Module holding AvgStdevMetadataFactory class."""
-
-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
-        """
-        # Using Welford method to be more resistant to rounding errors.
-        # Adapted from code for sample standard deviation at:
-        # https://www.johndcook.com/blog/standard_deviation/
-        # The logic of plus operator is taken from
-        # https://www.johndcook.com/blog/skewness_kurtosis/
-        size = 0
-        avg = 0.0
-        moment_2 = 0.0
-        for value in values:
-            if not isinstance(value, AvgStdevMetadata):
-                value = AvgStdevMetadata(size=1, avg=value)
-            old_size = size
-            delta = value.avg - avg
-            size += value.size
-            avg += delta * value.size / size
-            moment_2 += value.stdev * value.stdev * value.size
-            moment_2 += delta * delta * old_size * value.size / size
-        if size < 1:
-            return AvgStdevMetadata()
-        stdev = math.sqrt(moment_2 / size)
-        ret_obj = AvgStdevMetadata(size=size, avg=avg, stdev=stdev)
-        return ret_obj
diff --git a/PyPI/jumpavg/jumpavg/BitCountingClassifier.py b/PyPI/jumpavg/jumpavg/BitCountingClassifier.py
deleted file mode 100644
index 9a723199d2..0000000000
--- a/PyPI/jumpavg/jumpavg/BitCountingClassifier.py
+++ /dev/null
@@ -1,70 +0,0 @@
-# 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.
-
-"""Module holding BitCountingClassifier class.
-
-This is the main class to be used by callers."""
-
-from AbstractGroupClassifier import AbstractGroupClassifier
-from BitCountingGroup import BitCountingGroup
-from BitCountingGroupList import BitCountingGroupList
-from BitCountingMetadataFactory import BitCountingMetadataFactory
-from ClassifiedMetadataFactory import ClassifiedMetadataFactory
-
-
-class BitCountingClassifier(AbstractGroupClassifier):
-    """Classifier using Minimal Description Length principle."""
-
-    def classify(self, values):
-        """Return the values in groups of optimal bit count.
-
-        The current implementation could be a static method,
-        but we might support options in later versions,
-        for example for chosing encodings.
-
-        :param values: Sequence of runs to classify.
-        :type values: Iterable of float or of AvgStdevMetadata
-        :returns: Classified group list.
-        :rtype: BitCountingGroupList
-        """
-        max_value = BitCountingMetadataFactory.find_max_value(values)
-        factory = BitCountingMetadataFactory(max_value)
-        opened_at = []
-        closed_before = [BitCountingGroupList()]
-        for index, value in enumerate(values):
-            singleton = BitCountingGroup(factory, [value])
-            newly_opened = closed_before[index].with_group_appended(singleton)
-            opened_at.append(newly_opened)
-            record_group_list = newly_opened
-            for previous in range(index):
-                previous_opened_list = opened_at[previous]
-                still_opened = (
-                    previous_opened_list.with_value_added_to_last_group(value))
-                opened_at[previous] = still_opened
-                if still_opened.bits < record_group_list.bits:
-                    record_group_list = still_opened
-            closed_before.append(record_group_list)
-        partition = closed_before[-1]
-        previous_average = partition[0].metadata.avg
-        for group in partition:
-            if group.metadata.avg == previous_average:
-                group.metadata = ClassifiedMetadataFactory.with_classification(
-                    group.metadata, "normal")
-            elif group.metadata.avg < previous_average:
-                group.metadata = ClassifiedMetadataFactory.with_classification(
-                    group.metadata, "regression")
-            elif group.metadata.avg > previous_average:
-                group.metadata = ClassifiedMetadataFactory.with_classification(
-                    group.metadata, "progression")
-            previous_average = group.metadata.avg
-        return partition
diff --git a/PyPI/jumpavg/jumpavg/BitCountingGroup.py b/PyPI/jumpavg/jumpavg/BitCountingGroup.py
deleted file mode 100644
index 2071c061ea..0000000000
--- a/PyPI/jumpavg/jumpavg/BitCountingGroup.py
+++ /dev/null
@@ -1,50 +0,0 @@
-# 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.
-
-"""Module holding BitCountingGroup class."""
-
-from RunGroup import RunGroup
-
-
-class BitCountingGroup(RunGroup):
-    """RunGroup with BitCountingMetadata.
-
-    Support with_run_added() method to simplify extending the group.
-    As bit content has to be re-counted, metadata factory is stored.
-    """
-
-    def __init__(self, metadata_factory, values=[]):
-        """Create the group from metadata factory and values.
-
-        :param metadata_factory: Factory object to create metadata with.
-        :param values: The runs belonging to this group.
-        :type metadata_factory: BitCountingMetadataFactory
-        :type values: Iterable of float or of AvgStdevMetadata
-        """
-        self.metadata_factory = metadata_factory
-        metadata = metadata_factory.from_data(values)
-        super(BitCountingGroup, self).__init__(metadata, values)
-
-    def with_run_added(self, value):
-        """Create and return a new group with one more run that self.
-
-        :param value: The run value to add to the group.
-        :type value: float or od AvgStdevMetadata
-        :returns: New group with the run added.
-        :rtype: BitCountingGroup
-        """
-        values = list(self.values)
-        values.append(value)
-        return BitCountingGroup(self.metadata_factory, values)
-        # TODO: Is there a good way to save some computation
-        # by copy&updating the metadata incrementally?
diff --git a/PyPI/jumpavg/jumpavg/BitCountingGroupList.py b/PyPI/jumpavg/jumpavg/BitCountingGroupList.py
deleted file mode 100644
index 1f69c0635d..0000000000
--- a/PyPI/jumpavg/jumpavg/BitCountingGroupList.py
+++ /dev/null
@@ -1,87 +0,0 @@
-# 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.
-
-"""Module holding BitCountingGroupList class."""
-
-from BitCountingGroup import BitCountingGroup
-from BitCountingMetadataFactory import BitCountingMetadataFactory
-
-
-class BitCountingGroupList(list):
-    """List of BitCountingGroup which tracks overall bit count.
-
-    This is useful, as bit count of a subsequent group
-    depends on average of the previous group.
-    Having the logic encapsulated here spares the caller
-    the effort to pass averages around.
-
-    Method with_value_added_to_last_group() delegates to BitCountingGroup,
-    with_group_appended() adds new group with recalculated bits.
-
-    TODO: last_group.metadata_factory.max_value in with_group_appended()
-    is ugly, find a more natural class design.
-    """
-
-    def __init__(self, group_list=[], bits=None):
-        """Create a group list from given list of groups.
-
-        :param group_list: List of groups to compose this group.
-        :param bits: Bit count if known, else None.
-        :type group_list: list of BitCountingGroup
-        :type bits: float or None
-        """
-        super(BitCountingGroupList, self).__init__(group_list)
-        if bits is not None:
-            self.bits = bits
-            return
-        bits = 0.0
-        for group in group_list:
-            bits += group.metadata.bits
-        self.bits = bits
-
-    def with_group_appended(self, group):
-        """Create and return new group list with given group more than self.
-
-        The group argument object is updated with derivative metadata.
-
-        :param group: Next group to be appended to the group list.
-        :type group: BitCountingGroup
-        :returns: New group list with added group.
-        :rtype: BitCountingGroupList
-        """
-        group_list = list(self)
-        if group_list:
-            last_group = group_list[-1]
-            factory = BitCountingMetadataFactory(
-                last_group.metadata_factory.max_value, last_group.metadata.avg)
-            group.metadata_factory = factory
-            group.metadata = factory.from_data(group.values)
-        group_list.append(group)
-        bits = self.bits + group.metadata.bits
-        return BitCountingGroupList(group_list, bits)
-
-    def with_value_added_to_last_group(self, value):
-        """Create and return new group list with value added to last group.
-
-        :param value: The run value to add to the last group.
-        :type value: float or od AvgStdevMetadata
-        :returns: New group list with the last group updated.
-        :rtype: BitCountingGroupList
-        """
-        group_list = list(self)
-        last_group = group_list[-1]
-        bits_before = last_group.metadata.bits
-        last_group = last_group.with_run_added(value)
-        group_list[-1] = last_group
-        bits = self.bits - bits_before + last_group.metadata.bits
-        return BitCountingGroupList(group_list, bits)
diff --git a/PyPI/jumpavg/jumpavg/BitCountingMetadata.py b/PyPI/jumpavg/jumpavg/BitCountingMetadata.py
deleted file mode 100644
index d25d355cab..0000000000
--- a/PyPI/jumpavg/jumpavg/BitCountingMetadata.py
+++ /dev/null
@@ -1,109 +0,0 @@
-# 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.
-
-"""Module holding BitCountingMetadata class."""
-
-import math
-
-from AvgStdevMetadata import AvgStdevMetadata
-
-
-class BitCountingMetadata(AvgStdevMetadata):
-    """Class for metadata which includes information content of a group.
-
-    The information content is based on an assumption
-    that the data consists of independent random values
-    from a normal distribution.
-    """
-
-    def __init__(self, max_value, size=0, avg=0.0, stdev=0.0, prev_avg=None):
-        """Construct the metadata by computing from the values needed.
-
-        The bit count is not real, as that would depend on numeric precision
-        (number of significant bits in values).
-        The difference is assumed to be constant per value,
-        which is consistent with Gauss distribution
-        (but not with floating point mechanic).
-        The hope is the difference will have
-        no real impact on the classification procedure.
-
-        :param max_value: Maximal expected value.
-            TODO: This might be more optimal,
-            but max-invariant algorithm will be nicer.
-        :param size: Number of values participating in this group.
-        :param avg: Population average of the participating sample values.
-        :param stdev: Population standard deviation of the sample values.
-        :param prev_avg: Population average of the previous group.
-            If None, no previous average is taken into account.
-            If not None, the given previous average is used to discourage
-            consecutive groups with similar averages
-            (opposite triangle distribution is assumed).
-        :type max_value: float
-        :type size: int
-        :type avg: float
-        :type stdev: float
-        :type prev_avg: float or None
-        """
-        super(BitCountingMetadata, self).__init__(size, avg, stdev)
-        self.max_value = max_value
-        self.prev_avg = prev_avg
-        self.bits = 0.0
-        if self.size < 1:
-            return
-        # Length of the sequence must be also counted in bits,
-        # otherwise the message would not be decodable.
-        # Model: probability of k samples is 1/k - 1/(k+1)
-        # == 1/k/(k+1)
-        self.bits += math.log(size * (size + 1), 2)
-        if prev_avg is None:
-            # Avg is considered to be uniformly distributed
-            # from zero to max_value.
-            self.bits += math.log(max_value + 1.0, 2)
-        else:
-            # Opposite triangle distribution with minimum.
-            self.bits += math.log(
-                max_value * (max_value + 1) / (abs(avg - prev_avg) + 1), 2)
-        if self.size < 2:
-            return
-        # Stdev is considered to be uniformly distributed
-        # from zero to max_value. That is quite a bad expectation,
-        # but resilient to negative samples etc.
-        self.bits += math.log(max_value + 1.0, 2)
-        # Now we know the samples lie on sphere in size-1 dimensions.
-        # So it is (size-2)-sphere, with radius^2 == stdev^2 * size.
-        # https://en.wikipedia.org/wiki/N-sphere
-        sphere_area_ln = math.log(2) + math.log(math.pi) * ((size - 1) / 2.0)
-        sphere_area_ln -= math.lgamma((size - 1) / 2.0)
-        sphere_area_ln += math.log(stdev + 1.0) * (size - 2)
-        sphere_area_ln += math.log(size) * ((size - 2) / 2.0)
-        self.bits += sphere_area_ln / math.log(2)
-
-    def __str__(self):
-        """Return string with human readable description of the group.
-
-        :returns: Readable description.
-        :rtype: str
-        """
-        return "size={size} avg={avg} stdev={stdev} bits={bits}".format(
-            size=self.size, avg=self.avg, stdev=self.stdev, bits=self.bits)
-
-    def __repr__(self):
-        """Return string executable as Python constructor call.
-
-        :returns: Executable constructor call.
-        :rtype: str
-        """
-        return ("BitCountingMetadata(max_value={max_value},size={size}," +
-                "avg={avg},stdev={stdev},prev_avg={prev_avg})").format(
-                    max_value=self.max_value, size=self.size, avg=self.avg,
-                    stdev=self.stdev, prev_avg=self.prev_avg)
diff --git a/PyPI/jumpavg/jumpavg/BitCountingMetadataFactory.py b/PyPI/jumpavg/jumpavg/BitCountingMetadataFactory.py
deleted file mode 100644
index 567c3d4fe6..0000000000
--- a/PyPI/jumpavg/jumpavg/BitCountingMetadataFactory.py
+++ /dev/null
@@ -1,85 +0,0 @@
-# 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.
-
-"""Module holding BitCountingMetadataFactory class."""
-
-import math
-
-from AvgStdevMetadata import AvgStdevMetadata
-from AvgStdevMetadataFactory import AvgStdevMetadataFactory
-from BitCountingMetadata import BitCountingMetadata
-
-
-class BitCountingMetadataFactory(object):
-    """Class for factory which creates bit counting metadata from data.
-
-    TODO: Summarize the methods?
-    """
-
-    @staticmethod
-    def find_max_value(values):
-        """Return the max value.
-
-        This is a separate helper method,
-        because the whole set of values is usually larger than in from_data().
-
-        :param values: Run values to be processed.
-        :type values: Iterable of float
-        :returns: 0.0 or the biggest value found.
-        :rtype: float
-        """
-        max_value = 0.0
-        for value in values:
-            if isinstance(value, AvgStdevMetadata):
-                value = value.avg
-            if value > max_value:
-                max_value = value
-        return max_value
-
-    def __init__(self, max_value, prev_avg=None):
-        """Construct the factory instance with given arguments.
-
-        :param max_value: Maximal expected value.
-        :param prev_avg: Population average of the previous group.
-            If None, no previous average is taken into account.
-            If not None, the given previous average is used to discourage
-            consecutive groups with similar averages
-            (opposite triangle distribution is assumed).
-        :type max_value: float
-        :type prev_avg: float or None
-        """
-        self.max_value = max_value
-        self.prev_avg = prev_avg
-
-    def from_avg_stdev_metadata(self, metadata):
-        """Return new metadata object by adding bits to existing metadata.
-
-        :param metadata: Metadata to count bits for.
-        :type metadata: AvgStdevMetadata
-        :returns: The metadata with bits counted.
-        :rtype: BitCountingMetadata
-        """
-        return BitCountingMetadata(
-            max_value=self.max_value, size=metadata.size,
-            avg=metadata.avg, stdev=metadata.stdev, prev_avg=self.prev_avg)
-
-    def from_data(self, 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: BitCountingMetadata
-        """
-        metadata = AvgStdevMetadataFactory.from_data(values)
-        return self.from_avg_stdev_metadata(metadata)
diff --git a/PyPI/jumpavg/jumpavg/ClassifiedBitCountingMetadata.py b/PyPI/jumpavg/jumpavg/ClassifiedBitCountingMetadata.py
deleted file mode 100644
index 29359f0908..0000000000
--- a/PyPI/jumpavg/jumpavg/ClassifiedBitCountingMetadata.py
+++ /dev/null
@@ -1,73 +0,0 @@
-# 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.
-
-"""Module holding ClassifiedBitCountingMetadata class."""
-
-from BitCountingMetadata import BitCountingMetadata
-
-
-class ClassifiedBitCountingMetadata(BitCountingMetadata):
-    """Class for metadata which includes classification.
-
-    TODO: Can we create ClassifiedMetadata and inherit (also) from that?
-    """
-
-    def __init__(
-            self, max_value, size=0, avg=0.0, stdev=0.0, prev_avg=None,
-            classification=None):
-        """Delegate to ancestor constructors and set classification.
-
-        :param max_value: Maximal expected value.
-        :param size: Number of values participating in this group.
-        :param avg: Population average of the participating sample values.
-        :param stdev: Population standard deviation of the sample values.
-        :param prev_avg: Population average of the previous group.
-            If None, no previous average is taken into account.
-            If not None, the given previous average is used to discourage
-            consecutive groups with similar averages
-            (opposite triangle distribution is assumed).
-        :param classification: Arbitrary object classifying this group.
-        :type max_value: float
-        :type size: int
-        :type avg: float
-        :type stdev: float
-        :type prev_avg: float
-        :type classification: object
-        """
-        super(ClassifiedBitCountingMetadata, self).__init__(
-            max_value, size, avg, stdev, prev_avg)
-        self.classification = classification
-
-    def __str__(self):
-        """Return string with human readable description of the group.
-
-        :returns: Readable description.
-        :rtype: str
-        """
-        # str(super(...)) describes the proxy, not the proxied object.
-        super_str = super(ClassifiedBitCountingMetadata, self).__str__()
-        return super_str + " classification={classification}".format(
-            classification=self.classification)
-
-    def __repr__(self):
-        """Return string executable as Python constructor call.
-
-        :returns: Executable constructor call.
-        :rtype: str
-        """
-        return ("ClassifiedBitCountingMetadata(max_value={max_value}," +
-                "size={size},avg={avg},stdev={stdev},prev_avg={prev_avg}," +
-                "classification={cls})").format(
-                    max_value=self.max_value, size=self.size, avg=self.avg,
-                    stdev=self.stdev, prev_avg=self.prev_avg,
-                    cls=self.classification)
diff --git a/PyPI/jumpavg/jumpavg/ClassifiedMetadataFactory.py b/PyPI/jumpavg/jumpavg/ClassifiedMetadataFactory.py
deleted file mode 100644
index 7fdea7c162..0000000000
--- a/PyPI/jumpavg/jumpavg/ClassifiedMetadataFactory.py
+++ /dev/null
@@ -1,42 +0,0 @@
-# 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.
-
-"""Module holding ClassifiedBitCountingMetadata class."""
-
-from ClassifiedBitCountingMetadata import ClassifiedBitCountingMetadata
-
-
-class ClassifiedMetadataFactory(object):
-    """Class for factory which adds classification to bit counting metadata."""
-
-    @staticmethod
-    def with_classification(metadata, classification):
-        """Return new metadata object with added classification.
-
-        TODO: Is there a way to add classification to any metadata,
-        without messing up constructors and __repr__()?
-
-        FIXME: Factories take raw resources. Find a name for the thing
-        which takes semi-finished products. Transformer?
-
-        :param metadata: Existing metadata without classification.
-        :param classification: Arbitrary object classifying this group.
-        :type metadata: BitCountingMetadata
-        :type classification: object
-        :returns: The metadata with added classification.
-        :rtype: ClassifiedBitCountingMetadata
-        """
-        return ClassifiedBitCountingMetadata(
-            max_value=metadata.max_value, size=metadata.size, avg=metadata.avg,
-            stdev=metadata.stdev, prev_avg=metadata.prev_avg,
-            classification=classification)
diff --git a/PyPI/jumpavg/jumpavg/RunGroup.py b/PyPI/jumpavg/jumpavg/RunGroup.py
deleted file mode 100644
index 9de8ae8919..0000000000
--- a/PyPI/jumpavg/jumpavg/RunGroup.py
+++ /dev/null
@@ -1,34 +0,0 @@
-# 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.
-
-"""Module holding RunGroup class."""
-
-
-class RunGroup(object):
-    """Effectively a named touple of data and metadata.
-
-    TODO: This feels like an abstract class.
-    Most uses assume restrictions on metadata type.
-    Can this be defined similarly to C++ templates?
-    """
-
-    def __init__(self, metadata, values):
-        """Create the group from metadata and values.
-
-        :param metadata: Metadata object to associate with the group.
-        :param values: The runs belonging to this group.
-        :type metadata: AbstractGroupMetadata
-        :type values: Iterable of float or od AvgStdevMetadata
-        """
-        self.metadata = metadata
-        self.values = values
diff --git a/PyPI/jumpavg/setup.py b/PyPI/jumpavg/setup.py
index 206373ac47..c80e38f069 100644
--- a/PyPI/jumpavg/setup.py
+++ b/PyPI/jumpavg/setup.py
@@ -1,40 +1,47 @@
+#!/usr/bin/env python3
+
 """A setup module for setuptools.
 
 See:
 https://packaging.python.org/en/latest/distributing.html
 """
 
-from setuptools import setup, find_packages
+from setuptools import (setup, find_packages)
 from os import path
 from io import open
 
 here = path.abspath(path.dirname(__file__))
-with open(path.join(here, "README.rst"), encoding="utf-8") as f:
+with open(path.join(here, u"README.rst"), encoding=u"utf-8") as f:
     long_description = f.read()
 
 setup(
-    name="jumpavg",
-    version="0.1.4",  # This is currently the only place listing the version.
-    description="Library for finding changes in time series by grouping results.",
+    name=u"jumpavg",
+    version=u"0.2.0",  # This is currently the only place listing the version.
+    description=(
+        u"Library for locating changes in time series by grouping results."
+    ),
     long_description=long_description,
-    long_description_content_type="text/x-rst",
+    long_description_content_type=u"text/x-rst",
     # TODO: Create a separate webpage for jumpavg library.
-    url="https://gerrit.fd.io/r/gitweb?p=csit.git;a=tree;f=PyPI/jumpavg;hb=refs/heads/master",
-    author="Cisco Systems Inc. and/or its affiliates",
-    author_email="csit-dev@lists.fd.io",
+    url=(
+        u"https://gerrit.fd.io/r/gitweb?p=csit.git;a=tree;f=PyPI/jumpavg"
+        u";hb=refs/heads/master"
+    ),
+    author=u"Cisco Systems Inc. and/or its affiliates",
+    author_email=u"csit-dev@lists.fd.io",
     classifiers=[
-        "Development Status :: 3 - Alpha",
-        "Intended Audience :: Science/Research",
+        u"Development Status :: 3 - Alpha",
+        u"Intended Audience :: Science/Research",
         # Pick your license as you wish
-        "License :: OSI Approved :: Apache Software License",
-        "Natural Language :: English",
+        u"License :: OSI Approved :: Apache Software License",
+        u"Natural Language :: English",
         # TODO: Test which Python versions is the code compatible with.
-        "Programming Language :: Python :: 2.7",
-        "Topic :: Scientific/Engineering :: Information Analysis"
+        u"Programming Language :: Python :: 2.7",
+        u"Topic :: Scientific/Engineering :: Information Analysis"
     ],
-    keywords="progression regression anomaly detection",
+    keywords=u"progression regression anomaly detection statistics bits",
     packages=find_packages(exclude=[]),
-    # TODO: python_requires="~=2.7"
+    python_requires="~=3.6"
     install_requires=[],
     # TODO: Include simulator and tests.
     extras_require={
@@ -42,11 +49,14 @@ setup(
     package_data={
     },
     entry_points={
-        "console_scripts": [
+        u"console_scripts": [
         ],
     },
     project_urls={
-        "Bug Reports": "https://jira.fd.io/projects/CSIT/issues",
-        "Source": "https://gerrit.fd.io/r/gitweb?p=csit.git;a=tree;f=PyPI/jumpavg;hb=refs/heads/master",
+        u"Bug Reports": u"https://jira.fd.io/projects/CSIT/issues",
+        u"Source": (
+            u"https://gerrit.fd.io/r/gitweb?p=csit.git;a=tree;f=PyPI/jumpavg"
+            u";hb=refs/heads/master"
+        ),
     },
 )
diff --git a/resources/libraries/bash/function/per_patch.sh b/resources/libraries/bash/function/per_patch.sh
index 919789b5f4..ea7ea4f837 100644
--- a/resources/libraries/bash/function/per_patch.sh
+++ b/resources/libraries/bash/function/per_patch.sh
@@ -108,11 +108,12 @@ function compare_test_results () {
     set -exuo pipefail
 
     cd "${VPP_DIR}" || die "Change directory operation failed."
-    # Reusing CSIT main virtualenv.
+    # Ply is installed as system level package, but not seen for some reason.
     pip3 install -r "${PYTHON_SCRIPTS_DIR}/perpatch_requirements.txt" || {
-        die "Perpatch Python requirements installation failed."
+        die "Compare script Python requirements installation failed."
     }
-    python3 "${PYTHON_SCRIPTS_DIR}/compare_perpatch.py"
+    # Reusing CSIT main virtualenv.
+    python3 "${TOOLS_DIR}/integrated/compare_perpatch.py"
     # The exit code determines the vote result.
 }
 
diff --git a/resources/libraries/python/jumpavg/AvgStdevStats.py b/resources/libraries/python/jumpavg/AvgStdevStats.py
new file mode 100644
index 0000000000..9a8decd932
--- /dev/null
+++ b/resources/libraries/python/jumpavg/AvgStdevStats.py
@@ -0,0 +1,113 @@
+# Copyright (c) 2019 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.
+
+"""Module holding AvgStdevStats class."""
+
+import math
+
+
+class AvgStdevStats:
+    """Class for statistics which include average and stdev of a group.
+
+    Contrary to other stats types, adding values to the group
+    is computationally light without any caching.
+
+    Instances are only statistics, the data itself is stored elsewhere.
+    """
+
+    def __init__(self, size=0, avg=0.0, stdev=0.0):
+        """Construct the stats object by storing the values needed.
+
+        Each value has to be numeric.
+        The values are not sanitized depending on size, wrong initialization
+        can cause delayed math errors.
+
+        :param size: Number of values participating in this group.
+        :param avg: Population average of the participating sample values.
+        :param stdev: Population standard deviation of the sample values.
+        :type size: int
+        :type avg: float
+        :type stdev: float
+        """
+        self.size = size
+        self.avg = avg
+        self.stdev = stdev
+
+    def __str__(self):
+        """Return string with human readable description of the group.
+
+        :returns: Readable description.
+        :rtype: str
+        """
+        return f"size={self.size} avg={self.avg} stdev={self.stdev}"
+
+    def __repr__(self):
+        """Return string executable as Python constructor call.
+
+        :returns: Executable constructor call.
+        :rtype: str
+        """
+        return (
+            f"AvgStdevStats(size={self.size!r},avg={self.avg!r}"
+            f",stdev={self.stdev!r})"
+        )
+
+    @classmethod
+    def for_runs(cls, runs):
+        """Return new stats instance describing the sequence of runs.
+
+        If you want to append data to existing stats object,
+        you can simply use the stats object as the first run.
+
+        Instead of a verb, "for" is used to start this method name,
+        to signify the result contains less information than the input data.
+
+        Here, Run is a hypothetical abstract class, an union of float and cls.
+        Defining that as a real abstract class in Python 2 is too much hassle.
+
+        :param runs: Sequence of data to describe by the new metadata.
+        :type runs: Iterable[Union[float, cls]]
+        :returns: The new stats instance.
+        :rtype: cls
+        """
+        # Using Welford method to be more resistant to rounding errors.
+        # Adapted from code for sample standard deviation at:
+        # https://www.johndcook.com/blog/standard_deviation/
+        # The logic of plus operator is taken from
+        # https://www.johndcook.com/blog/skewness_kurtosis/
+        total_size = 0
+        total_avg = 0.0
+        moment_2 = 0.0
+        for run in runs:
+            if isinstance(run, (float, int)):
+                run_size = 1
+                run_avg = run
+                run_stdev = 0.0
+            else:
+                run_size = run.size
+                run_avg = run.avg
+                run_stdev = run.stdev
+            old_total_size = total_size
+            delta = run_avg - total_avg
+            total_size += run_size
+            total_avg += delta * run_size / total_size
+            moment_2 += run_stdev * run_stdev * run_size
+            moment_2 += delta * delta * old_total_size * run_size / total_size
+        if total_size < 1:
+            # Avoid division by zero.
+            return cls(size=0)
+        # TODO: Is it worth tracking moment_2 instead, and compute and cache
+        # stdev on demand, just to possibly save some sqrt calls?
+        total_stdev = math.sqrt(moment_2 / total_size)
+        ret_obj = cls(size=total_size, avg=total_avg, stdev=total_stdev)
+        return ret_obj
diff --git a/resources/libraries/python/jumpavg/BitCountingGroup.py b/resources/libraries/python/jumpavg/BitCountingGroup.py
new file mode 100644
index 0000000000..0c1aabba30
--- /dev/null
+++ b/resources/libraries/python/jumpavg/BitCountingGroup.py
@@ -0,0 +1,173 @@
+# Copyright (c) 2019 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.
+
+"""Module holding BitCountingGroup class."""
+
+import copy
+
+from .AvgStdevStats import AvgStdevStats
+from .BitCountingStats import BitCountingStats
+
+
+class BitCountingGroup:
+    # TODO: Inherit from collections.abc.Sequence in Python 3.
+    """Group of runs which tracks bit count in an efficient manner.
+
+    This class contains methods that mutate the internal state,
+    use copy() method to save the previous state.
+
+    The Sequence-like access is related to the list of runs,
+    for example group[0] returns the first run in the list.
+    Writable list-like methods are not implemented.
+
+    As the group bit count depends on previous average
+    and overall maximal value, those values are assumed
+    to be known beforehand (and immutable).
+
+    As the caller is allowed to divide runs into groups in any way,
+    a method to add a single run in an efficient manner is provided.
+    """
+
+    def __init__(self, run_list=None, stats=None, bits=None,
+                 max_value=None, prev_avg=None, comment="unknown"):
+        """Set the internal state and partially the stats.
+
+        A "group" stands for an Iterable of runs, where "run" is either
+        a float value, or a stats-like object (only size, avg and stdev
+        are accessed). Run is a hypothetical abstract class,
+        defining it in Python 2 is too much hassle.
+
+        Only a copy of the run list argument value is stored in the instance,
+        so it is not a problem if the value object is mutated afterwards.
+
+        It is not verified whether the user provided values are valid,
+        e.g. whether the stats and bits values reflect the runs.
+
+        :param run_list: List of run to compose into this group. Default: empty.
+        :param stats: Stats object used for computing bits.
+        :param bits: Cached value of information content.
+        :param max_value: Maximal sample value to be used for computing.
+        :param prev_avg: Average of the previous group, affects bits.
+        :param comment: Any string giving more info, e.g. "regression".
+        :type run_list: Iterable[Run]
+        :type stats: Optional[AvgStdevStats]
+        :type bits: Optional[float]
+        :type max_value: float
+        :type prev_avg: Optional[float]
+        :type comment: str
+        """
+        self.run_list = copy.deepcopy(run_list) if run_list else list()
+        self.stats = stats
+        self.cached_bits = bits
+        self.max_value = max_value
+        self.prev_avg = prev_avg
+        self.comment = comment
+        if self.stats is None:
+            self.stats = AvgStdevStats.for_runs(self.run_list)
+
+    def __str__(self):
+        """Return string with human readable description of the group.
+
+        :returns: Readable description.
+        :rtype: str
+        """
+        return f"stats={self.stats} bits={self.cached_bits}"
+
+    def __repr__(self):
+        """Return string executable as Python constructor call.
+
+        :returns: Executable constructor call.
+        :rtype: str
+        """
+        return (
+            f"BitCountingGroup(run_list={self.run_list!r},stats={self.stats!r}"
+            f",bits={self.cached_bits!r},max_value={self.max_value!r}"
+            f",prev_avg={self.prev_avg!r},comment={self.comment!r})"
+        )
+
+    def __getitem__(self, index):
+        """Return the run at the index.
+
+        :param index: Index of the run to return.
+        :type index: int
+        :returns: The run at the index.
+        :rtype: Run
+        """
+        return self.run_list[index]
+
+    def __len__(self):
+        """Return the number of runs in the group.
+
+        :returns: The Length of run_list.
+        :rtype: int
+        """
+        return len(self.run_list)
+
+    def copy(self):
+        """Return a new instance with copied internal state.
+
+        :returns: The copied instance.
+        :rtype: BitCountingGroup
+        """
+        stats = AvgStdevStats.for_runs([self.stats])
+        return self.__class__(
+            run_list=self.run_list, stats=stats, bits=self.cached_bits,
+            max_value=self.max_value, prev_avg=self.prev_avg,
+            comment=self.comment)
+
+    @property
+    def bits(self):
+        """Return overall bit content of the group list.
+
+        If not cached, compute from stats and cache.
+
+        :returns: The overall information content in bits.
+        :rtype: float
+        """
+        if self.cached_bits is None:
+            self.cached_bits = BitCountingStats.for_runs(
+                [self.stats], self.max_value, self.prev_avg).bits
+        return self.cached_bits
+
+    def append(self, run):
+        """Mutate to add the new run, return self.
+
+        Stats are updated, but old bits value is deleted from cache.
+
+        :param run: The run value to add to the group.
+        :type value: Run
+        :returns: The updated self.
+        :rtype: BitCountingGroup
+        """
+        self.run_list.append(run)
+        self.stats = AvgStdevStats.for_runs([self.stats, run])
+        self.cached_bits = None
+        return self
+
+    def extend(self, runs):
+        """Mutate to add the new runs, return self.
+
+        This is saves small amount of computation
+        compared to adding runs one by one in a loop.
+
+        Stats are updated, but old bits value is deleted from cache.
+
+        :param runs: The runs to add to the group.
+        :type value: Iterable[Run]
+        :returns: The updated self.
+        :rtype: BitCountingGroup
+        """
+        self.run_list.extend(runs)
+        self.stats = AvgStdevStats.for_runs([self.stats] + runs)
+        self.cached_bits = None
+        return self
diff --git a/resources/libraries/python/jumpavg/BitCountingGroupList.py b/resources/libraries/python/jumpavg/BitCountingGroupList.py
new file mode 100644
index 0000000000..bcc5e43267
--- /dev/null
+++ b/resources/libraries/python/jumpavg/BitCountingGroupList.py
@@ -0,0 +1,185 @@
+# Copyright (c) 2019 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.
+
+"""Module holding BitCountingGroupList class."""
+
+import copy
+
+from .BitCountingGroup import BitCountingGroup
+
+
+class BitCountingGroupList:
+    # TODO: Inherit from collections.abc.Sequence in Python 3.
+    """List of data groups which tracks overall bit count.
+
+    The Sequence-like access is related to the list of groups,
+    for example group_list[0] returns the first group in the list.
+    Writable list-like methods are not implemented.
+
+    The overall bit count is the sum of bit counts of each group.
+    Group is a sequence of data samples accompanied by their stats.
+    Different partitioning of data samples into the groups
+    results in different overall bit count.
+    This can be used to group samples in various contexts.
+
+    As the group bit count depends on previous average
+    and overall maximal value, order of groups is important.
+    Having the logic encapsulated here spares the caller
+    the effort to pass averages around.
+
+    The data can be only added, and there is some logic to skip
+    recalculations if the bit count is not needed.
+    """
+
+    def __init__(self, group_list=None, bits_except_last=0.0, max_value=None):
+        """Set the internal state without any calculations.
+
+        The group list argument is copied deeply, so it is not a problem
+        if the value object is mutated afterwards.
+
+        A "group" stands for an Iterable of runs, where "run" is either
+        a float value, or a stats-like object (only size, avg and stdev
+        are accessed). Run is a hypothetical abstract class,
+        defining it in Python 2 is too much hassle.
+
+        It is not verified whether the user provided values are valid,
+        e.g. whether the cached bits values make sense.
+
+        The max_value is required and immutable,
+        it is recommended the callers find their maximum beforehand.
+
+        :param group_list: List of groups to compose this group list (or empty).
+        :param bits_except_last: Partial sum of all but one group bits.
+        :param max_value: Maximal sample value to base bits computation on.
+        :type group_list: Iterable[BitCountingGroup]
+        :type bits_except_last: float
+        :type max_value: float
+        """
+        self.group_list = copy.deepcopy(group_list) if group_list else list()
+        self.bits_except_last = bits_except_last
+        self.max_value = max_value
+
+    def __str__(self):
+        """Return string with human readable description of the group list.
+
+        :returns: Readable description.
+        :rtype: str
+        """
+        return u"group_list={self.group_list} bits={self.bits}"
+
+    def __repr__(self):
+        """Return string executable as Python constructor call.
+
+        :returns: Executable constructor call.
+        :rtype: str
+        """
+        return (
+            f"BitCountingGroupList(group_list={self.group_list!r}"
+            f",bits_except_last={self.bits_except_last!r}"
+            f",max_value={self.max_value!r})"
+        )
+
+    def __getitem__(self, index):
+        """Return the group at the index.
+
+        :param index: Index of the group to return.
+        :type index: int
+        :returns: The group at the index.
+        :rtype: BitCountingGroup
+        """
+        return self.group_list[index]
+
+    def __len__(self):
+        """Return the length of the group list.
+
+        :returns: The Length of group_list.
+        :rtype: int
+        """
+        return len(self.group_list)
+
+    def copy(self):
+        """Return a new instance with copied internal state.
+
+        :returns: The copied instance.
+        :rtype: BitCountingGroupList
+        """
+        return self.__class__(
+            group_list=self.group_list, bits_except_last=self.bits_except_last,
+            max_value=self.max_value
+        )
+
+    @property
+    def bits(self):
+        """Return overall bit content of the group list.
+
+        :returns: The overall information content in bits.
+        :rtype: float
+        """
+        if not self.group_list:
+            return 0.0
+        # TODO: Is it worth to cache the overall result?
+        return self.bits_except_last + self.group_list[-1].bits
+
+    def append_group_of_runs(self, runs):
+        """Mutate to add a new group based on the runs, return self.
+
+        The argument is copied before adding to the group list,
+        so further edits do not affect the grup list.
+        The argument can also be a group, only runs from it are used.
+
+        :param runs: Runs to form the next group to be appended to self.
+        :type runs: Union[Iterable[Run], BitCountingGroup]
+        :returns: The updated self.
+        :rtype: BitCountingGroupList
+        """
+        prev_avg = self.group_list[-1].stats.avg if self.group_list else None
+        if isinstance(runs, BitCountingGroup):
+            # It is faster to avoid stats recalculation.
+            new_group = runs.copy()
+            new_group.max_value = self.max_value
+            new_group.prev_avg = prev_avg
+            new_group.cached_bits = None
+        else:
+            new_group = BitCountingGroup(
+                run_list=runs, max_value=self.max_value, prev_avg=prev_avg)
+        self.bits_except_last = self.bits
+        self.group_list.append(new_group)
+        return self
+
+    def append_run_to_to_last_group(self, run):
+        """Mutate to add new run at the end of the last group.
+
+        Basically a one-liner, only returning group list instead of last group.
+
+        :param run: The run value to add to the last group.
+        :type run: Run
+        :returns: The updated self.
+        :rtype: BitCountingGroupList
+        :raises IndexError: If group list is empty, no last group to add to.
+        """
+        self.group_list[-1].append(run)
+        return self
+
+    def extend_runs_to_last_group(self, runs):
+        """Mutate to add new runs to the end of the last group.
+
+        A faster alternative to appending runs one by one in a loop.
+
+        :param runs: The runs to add to the last group.
+        :type runs: Iterable[Run]
+        :returns: The updated self
+        :rtype: BitCountingGroupList
+        :raises IndexError: If group list is empty, no last group to add to.
+        """
+        self.group_list[-1].extend(runs)
+        return self
diff --git a/resources/libraries/python/jumpavg/BitCountingStats.py b/resources/libraries/python/jumpavg/BitCountingStats.py
new file mode 100644
index 0000000000..0addec013b
--- /dev/null
+++ b/resources/libraries/python/jumpavg/BitCountingStats.py
@@ -0,0 +1,169 @@
+# Copyright (c) 2019 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.
+
+"""Module holding BitCountingStats class."""
+
+import math
+
+from .AvgStdevStats import AvgStdevStats
+
+
+class BitCountingStats(AvgStdevStats):
+    """Class for statistics which include information content of a group.
+
+    The information content is based on an assumption that the data
+    consists of independent random values from a normal distribution.
+
+    Instances are only statistics, the data itself is stored elsewhere.
+
+    The coding needs to know the previous average, and a maximal value
+    so both values are required as inputs.
+
+    This is a subclass of AvgStdevStats, even though all methods are overriden.
+    Only for_runs method calls the parent implementation, without using super().
+    """
+
+    def __init__(
+            self, size=0, avg=None, stdev=0.0, max_value=None, prev_avg=None):
+        """Construct the stats object by computing from the values needed.
+
+        The values are not sanitized, faulty callers can cause math errors.
+
+        The None values are allowed for stats for zero size data,
+        but such stats can report arbitrary avg and max_value.
+        Stats for nonzero size data cannot contain None,
+        else ValueError is raised.
+
+        The max_value needs to be numeric for nonzero size,
+        but its relations to avg and prev_avg are not examined.
+
+        The bit count is not real, as that would depend on numeric precision
+        (number of significant bits in values).
+        The difference is assumed to be constant per value,
+        which is consistent with Gauss distribution
+        (but not with floating point mechanic).
+        The hope is the difference will have
+        no real impact on the classification procedure.
+
+        :param size: Number of values participating in this group.
+        :param avg: Population average of the participating sample values.
+        :param stdev: Population standard deviation of the sample values.
+        :param max_value: Maximal expected value.
+            TODO: This might be more optimal,
+            but max-invariant algorithm will be nicer.
+        :param prev_avg: Population average of the previous group.
+            If None, no previous average is taken into account.
+            If not None, the given previous average is used to discourage
+            consecutive groups with similar averages
+            (opposite triangle distribution is assumed).
+        :type avg: float
+        :type size: int
+        :type stdev: float
+        :type max_value: Union[float, NoneType]
+        :type prev_avg: Union[float, NoneType]
+        """
+        self.avg = avg
+        self.size = size
+        self.stdev = stdev
+        self.max_value = max_value
+        self.prev_avg = prev_avg
+        # Zero size should in principle have non-zero bits (coding zero size),
+        # but zero allows users to add empty groups without affecting bits.
+        self.bits = 0.0
+        if self.size < 1:
+            return
+        if avg is None:
+            raise ValueError(f"Avg is None: {self!r}")
+        if max_value is None or max_value <= 0.0:
+            raise ValueError(f"Invalid max value: {self!r}")
+        # Length of the sequence must be also counted in bits,
+        # otherwise the message would not be decodable.
+        # Model: probability of k samples is 1/k - 1/(k+1) == 1/k/(k+1)
+        # This is compatible with zero size leading to zero bits.
+        self.bits += math.log(size * (size + 1), 2)
+        if prev_avg is None:
+            # Avg is considered to be uniformly distributed
+            # from zero to max_value.
+            self.bits += math.log(max_value + 1.0, 2)
+        else:
+            # Opposite triangle distribution with minimum.
+            self.bits += math.log(
+                max_value * (max_value + 1) / (abs(avg - prev_avg) + 1), 2)
+        if self.size < 2:
+            return
+        # Stdev is considered to be uniformly distributed
+        # from zero to max_value. That is quite a bad expectation,
+        # but resilient to negative samples etc.
+        self.bits += math.log(max_value + 1.0, 2)
+        # Now we know the samples lie on sphere in size-1 dimensions.
+        # So it is (size-2)-sphere, with radius^2 == stdev^2 * size.
+        # https://en.wikipedia.org/wiki/N-sphere
+        sphere_area_ln = math.log(2) + math.log(math.pi) * ((size - 1) / 2.0)
+        sphere_area_ln -= math.lgamma((size - 1) / 2.0)
+        sphere_area_ln += math.log(stdev + 1.0) * (size - 2)
+        sphere_area_ln += math.log(size) * ((size - 2) / 2.0)
+        self.bits += sphere_area_ln / math.log(2)
+
+    def __str__(self):
+        """Return string with human readable description of the group.
+
+        :returns: Readable description.
+        :rtype: str
+        """
+        return (
+            f"size={self.size} avg={self.avg} stdev={self.stdev}"
+            f" bits={self.bits}"
+        )
+
+    def __repr__(self):
+        """Return string executable as Python constructor call.
+
+        :returns: Executable constructor call.
+        :rtype: str
+        """
+        return (
+            f"BitCountingStats(size={self.size!r},avg={self.avg!r}"
+            f",stdev={self.stdev!r},max_value={self.max_value!r}"
+            f",prev_avg={self.prev_avg!r})"
+        )
+
+    @classmethod
+    def for_runs(cls, runs, max_value=None, prev_avg=None):
+        """Return new stats instance describing the sequence of runs.
+
+        If you want to append data to existing stats object,
+        you can simply use the stats object as the first run.
+
+        Instead of a verb, "for" is used to start this method name,
+        to signify the result contains less information than the input data.
+
+        The two optional values can come from outside of the runs provided.
+
+        The max_value cannot be None for non-zero size data.
+        The implementation does not check if no datapoint exceeds max_value.
+
+        TODO: Document the behavior for zero size result.
+
+        :param runs: Sequence of data to describe by the new metadata.
+        :param max_value: Maximal expected value.
+        :param prev_avg: Population average of the previous group, if any.
+        :type runs: Iterable[Union[float, AvgStdevStats]]
+        :type max_value: Union[float, NoneType]
+        :type prev_avg: Union[float, NoneType]
+        :returns: The new stats instance.
+        :rtype: cls
+        """
+        asd = AvgStdevStats.for_runs(runs)
+        ret_obj = cls(size=asd.size, avg=asd.avg, stdev=asd.stdev,
+                      max_value=max_value, prev_avg=prev_avg)
+        return ret_obj
diff --git a/PyPI/jumpavg/jumpavg/__init__.py b/resources/libraries/python/jumpavg/__init__.py
index 8e41ed9fe2..cb8b3df43d 100644
--- a/PyPI/jumpavg/jumpavg/__init__.py
+++ b/resources/libraries/python/jumpavg/__init__.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2018 Cisco and/or its affiliates.
+# Copyright (c) 2019 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:
@@ -14,3 +14,9 @@
 """
 __init__ file for "jumpavg" Python package.
 """
+
+from .AvgStdevStats import AvgStdevStats
+from .BitCountingStats import BitCountingStats
+from .BitCountingGroup import BitCountingGroup
+from .BitCountingGroupList import BitCountingGroupList
+from .classify import classify
diff --git a/resources/libraries/python/jumpavg/classify.py b/resources/libraries/python/jumpavg/classify.py
new file mode 100644
index 0000000000..5f5ce6160c
--- /dev/null
+++ b/resources/libraries/python/jumpavg/classify.py
@@ -0,0 +1,76 @@
+# Copyright (c) 2019 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.
+
+"""Module holding the classify function
+
+Classification os one of primary purposes of this package.
+
+Minimal message length principle is used
+for grouping results into the list of groups,
+assuming each group is a population of different Gaussian distribution.
+"""
+
+from .AvgStdevStats import AvgStdevStats
+from .BitCountingGroupList import BitCountingGroupList
+
+
+def classify(values):
+    """Return the values in groups of optimal bit count.
+
+    Here, a value is either a float, or an iterable of floats.
+    Such iterables represent an undivisible sequence of floats.
+
+    Internally, such sequence is replaced by AvgStdevStats
+    after maximal value is found.
+
+    :param values: Sequence of runs to classify.
+    :type values: Iterable[Union[float, Iterable[float]]]
+    :returns: Classified group list.
+    :rtype: BitCountingGroupList
+    """
+    processed_values = list()
+    max_value = 0.0
+    for value in values:
+        if isinstance(value, (float, int)):
+            if value > max_value:
+                max_value = value
+            processed_values.append(value)
+        else:
+            for subvalue in value:
+                if subvalue > max_value:
+                    max_value = subvalue
+            processed_values.append(AvgStdevStats.for_runs(value))
+    open_at = list()
+    closed_before = [BitCountingGroupList(max_value=max_value)]
+    for index, value in enumerate(processed_values):
+        newly_open = closed_before[index].copy()
+        newly_open.append_group_of_runs([value])
+        open_at.append(newly_open)
+        record_group_list = newly_open
+        for previous_index, old_open in enumerate(open_at[:index]):
+            new_open = old_open.copy().append_run_to_to_last_group(value)
+            open_at[previous_index] = new_open
+            if new_open.bits < record_group_list.bits:
+                record_group_list = new_open
+        closed_before.append(record_group_list)
+    partition = closed_before[-1]
+    previous_average = partition[0].stats.avg
+    for group in partition:
+        if group.stats.avg == previous_average:
+            group.comment = u"normal"
+        elif group.stats.avg < previous_average:
+            group.comment = u"regression"
+        elif group.stats.avg > previous_average:
+            group.comment = u"progression"
+        previous_average = group.stats.avg
+    return partition
diff --git a/resources/tools/doc_gen/.gitignore b/resources/tools/doc_gen/.gitignore
index beb0d8f0cf..02254b9e4c 100644
--- a/resources/tools/doc_gen/.gitignore
+++ b/resources/tools/doc_gen/.gitignore
@@ -1,2 +1,3 @@
 _build/**
 **/*tar.gz
+/tmp
diff --git a/resources/tools/scripts/compare_perpatch.py b/resources/tools/integrated/compare_perpatch.py
index c2c165c76d..dd15490506 100644
--- a/resources/tools/scripts/compare_perpatch.py
+++ b/resources/tools/integrated/compare_perpatch.py
@@ -25,8 +25,7 @@ this script votes -1 (by exiting with code 1), otherwise it votes +1 (exit 0).
 import json
 import sys
 
-from jumpavg.BitCountingMetadataFactory import BitCountingMetadataFactory
-from jumpavg.BitCountingClassifier import BitCountingClassifier
+from resources.libraries.python import jumpavg
 
 
 def hack(value_list):
@@ -75,10 +74,8 @@ while 1:
         sys.exit(1)
     parent_iterations.append(parent_lines)
     current_iterations.append(current_lines)
-classifier = BitCountingClassifier()
 exit_code = 0
 for test_index in range(num_tests):
-    val_max = 1.0
     parent_values = list()
     current_values = list()
     for iteration_index in range(len(parent_iterations)):
@@ -92,35 +89,42 @@ for test_index in range(num_tests):
     print(f"Time-ordered MRR values for current build: {current_values}")
     parent_values = hack(parent_values)
     current_values = hack(current_values)
-    parent_max = BitCountingMetadataFactory.find_max_value(parent_values)
-    current_max = BitCountingMetadataFactory.find_max_value(current_values)
-    val_max = max(val_max, parent_max, current_max)
-    factory = BitCountingMetadataFactory(val_max)
-    parent_stats = factory.from_data(parent_values)
-    current_factory = BitCountingMetadataFactory(val_max, parent_stats.avg)
-    current_stats = current_factory.from_data(current_values)
-    both_stats = factory.from_data(parent_values + current_values)
+    max_value = max([1.0] + parent_values + current_values)
+    parent_stats = jumpavg.AvgStdevStats.for_runs(parent_values)
+    current_stats = jumpavg.AvgStdevStats.for_runs(current_values)
+    parent_group_list = jumpavg.BitCountingGroupList(
+        max_value=max_value).append_group_of_runs([parent_stats])
+    combined_group_list = parent_group_list.copy().extend_runs_to_last_group(
+        [current_stats])
+    separated_group_list = parent_group_list.append_group_of_runs(
+        [current_stats])
     print(f"Value-ordered MRR values for parent build: {parent_values}")
     print(f"Value-ordered MRR values for current build: {current_values}")
-    difference = (current_stats.avg - parent_stats.avg) / parent_stats.avg
-    print(f"Difference of averages relative to parent: {100 * difference}%")
+    avg_diff = (current_stats.avg - parent_stats.avg) / parent_stats.avg
+    print(f"Difference of averages relative to parent: {100 * avg_diff}%")
     print(f"Jumpavg representation of parent group: {parent_stats}")
     print(f"Jumpavg representation of current group: {current_stats}")
-    print(f"Jumpavg representation of both as one group: {both_stats}")
-    bits = parent_stats.bits + current_stats.bits - both_stats.bits
-    compared = u"longer" if bits >= 0 else u"shorter"
     print(
-        f"Separate groups are {compared} than single group by {abs(bits)} bits"
+        f"Jumpavg representation of both as one group:"
+        f" {combined_group_list[0].stats}"
     )
-    classified_list = classifier.classify([parent_stats, current_stats])
+    bits_diff = separated_group_list.bits - combined_group_list.bits
+    compared = u"longer" if bits_diff >= 0 else u"shorter"
+    print(
+        f"Separate groups are {compared} than single group"
+        f" by {abs(bits_diff)} bits"
+    )
+    # TODO: Version of classify that takes max_value and list of stats?
+    # That matters if only stats (not list of floats) are given.
+    classified_list = jumpavg.classify([parent_values, current_values])
     if len(classified_list) < 2:
         print(f"Test test_index {test_index}: normal (no anomaly)")
         continue
-    anomaly = classified_list[1].metadata.classification
+    anomaly = classified_list[1].comment
     if anomaly == u"regression":
         print(f"Test test_index {test_index}: anomaly regression")
-        exit_code = 1
+        exit_code = 3  # 1 or 2 can be caused by other errors
         continue
     print(f"Test test_index {test_index}: anomaly {anomaly}")
-print(f"Exit code {exit_code}")
+print(f"Exit code: {exit_code}")
 sys.exit(exit_code)
diff --git a/resources/tools/scripts/perpatch_requirements.txt b/resources/tools/scripts/perpatch_requirements.txt
index 3fca076af2..2275fb82f2 100644
--- a/resources/tools/scripts/perpatch_requirements.txt
+++ b/resources/tools/scripts/perpatch_requirements.txt
@@ -1,4 +1,4 @@
-# Copyright (c) 2018 Cisco and/or its affiliates.
+# Copyright (c) 2019 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:
@@ -11,6 +11,5 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# TODO: Convert to use the code from cloned CSIT git, not from pip.
-jumpavg==0.1.3
+# TODO: Ply should be installed as system package, fix bootstrap to see it.
 ply==3.11