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>

15 files changed, 31 insertions, 776 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/jumpavg/__init__.py b/PyPI/jumpavg/jumpavg/__init__.py
deleted file mode 100644
index 8e41ed9fe2..0000000000
--- a/PyPI/jumpavg/jumpavg/__init__.py
+++ /dev/null
@@ -1,16 +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.
-
-"""
-__init__ file for "jumpavg" Python package.
-"""
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"
+        ),
     },
 )