CSIT-1110: Use jumpavg library from pip

+ Move the jumpavg library code to separate directory.
- Bump to 0.1.2 has to be done later.

Change-Id: I9722ede48f00e99eeb68ca3f91e0bdeee2937973
Signed-off-by: Vratko Polak <vrpolak@cisco.com>

20 files changed, 1157 insertions, 0 deletions

diff --git a/PyPI/README.txt b/PyPI/README.txt
new file mode 100644
index 0000000000..5dd27e3ac7
--- /dev/null
+++ b/PyPI/README.txt
@@ -0,0 +1,6 @@
+Directories here hold code to be released into Python Package Index (PyPI).
+
+Mosly libraries, so people could expect them in resources/libraries/python/.
+But these libraries cannot be there, because that is a package hierarchy
+used by robot code, but we want the libraries here
+to be NOT read from cloned CSIT git repo, but from pip.
diff --git a/PyPI/jumpavg/.gitignore b/PyPI/jumpavg/.gitignore
new file mode 100644
index 0000000000..894a44cc06
--- /dev/null
+++ b/PyPI/jumpavg/.gitignore
@@ -0,0 +1,104 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
diff --git a/PyPI/jumpavg/LICENSE.txt b/PyPI/jumpavg/LICENSE.txt
new file mode 100644
index 0000000000..261eeb9e9f
--- /dev/null
+++ b/PyPI/jumpavg/LICENSE.txt
@@ -0,0 +1,201 @@
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diff --git a/PyPI/jumpavg/MANIFEST.in b/PyPI/jumpavg/MANIFEST.in
new file mode 100644
index 0000000000..58073271d1
--- /dev/null
+++ b/PyPI/jumpavg/MANIFEST.in
@@ -0,0 +1,6 @@
+
+# Include the README
+include README.rst
+
+# Include the license file
+include LICENSE.txt
diff --git a/PyPI/jumpavg/README.rst b/PyPI/jumpavg/README.rst
new file mode 100644
index 0000000000..2bdde2b9d0
--- /dev/null
+++ b/PyPI/jumpavg/README.rst
@@ -0,0 +1,28 @@
+Jumpavg library
+===============
+
+Origins
+-------
+
+This library was developed as anomaly detection logic
+for PAL_ (Presentation and Analysis Layer)
+of CSIT_ (Continuous System and Integration Testing)
+project of fd.io_ (Fast Data), one of LFN_
+(Linux Foundation Networking) projects.
+
+In order to make this code available in PyPI_ (Python Package Index),
+the setuputils stuff has been added,
+and the code has been moved into a separate directory_,
+in order to not intervere of otherwise tightly coupled CSIT code.
+
+Usage
+-----
+
+TODO.
+
+.. _PAL: https://wiki.fd.io/view/CSIT/Design_Optimizations#Presentation_and_Analytics_Layer
+.. _CSIT: https://wiki.fd.io/view/CSIT
+.. _fd.io: https://fd.io/
+.. _LFN: https://www.linuxfoundation.org/projects/networking/
+.. _PyPI: https://pypi.org/
+.. _directory: https://gerrit.fd.io/r/gitweb?p=csit.git;a=tree;f=PyPI/jumpavg;hb=refs/heads/master
diff --git a/PyPI/jumpavg/jumpavg/AbstractGroupClassifier.py b/PyPI/jumpavg/jumpavg/AbstractGroupClassifier.py
new file mode 100644
index 0000000000..2612b009da
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/AbstractGroupClassifier.py
@@ -0,0 +1,40 @@
+# 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
new file mode 100644
index 0000000000..3235dbd485
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/AbstractGroupMetadata.py
@@ -0,0 +1,42 @@
+# 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
new file mode 100644
index 0000000000..efc1a90cd4
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/AvgStdevMetadata.py
@@ -0,0 +1,54 @@
+# 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
new file mode 100644
index 0000000000..6d2e967a88
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py
@@ -0,0 +1,51 @@
+# 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
+        """
+        sum_0 = 0
+        sum_1 = 0.0
+        sum_2 = 0.0
+        for value in values:
+            if isinstance(value, AvgStdevMetadata):
+                sum_0 += value.size
+                sum_1 += value.avg * value.size
+                sum_2 += value.stdev * value.stdev * value.size
+                sum_2 += value.avg * value.avg * value.size
+            else:  # The value is assumed to be float.
+                sum_0 += 1
+                sum_1 += value
+                sum_2 += value * value
+        if sum_0 < 1:
+            return AvgStdevMetadata()
+        avg = sum_1 / sum_0
+        stdev = math.sqrt(sum_2 / sum_0 - avg * avg)
+        ret_obj = AvgStdevMetadata(size=sum_0, avg=avg, stdev=stdev)
+        return ret_obj
diff --git a/PyPI/jumpavg/jumpavg/BitCountingClassifier.py b/PyPI/jumpavg/jumpavg/BitCountingClassifier.py
new file mode 100644
index 0000000000..9a723199d2
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/BitCountingClassifier.py
@@ -0,0 +1,70 @@
+# 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
new file mode 100644
index 0000000000..2071c061ea
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/BitCountingGroup.py
@@ -0,0 +1,50 @@
+# 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
new file mode 100644
index 0000000000..1f69c0635d
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/BitCountingGroupList.py
@@ -0,0 +1,87 @@
+# 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
new file mode 100644
index 0000000000..d25d355cab
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/BitCountingMetadata.py
@@ -0,0 +1,109 @@
+# 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
new file mode 100644
index 0000000000..567c3d4fe6
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/BitCountingMetadataFactory.py
@@ -0,0 +1,85 @@
+# 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
new file mode 100644
index 0000000000..29359f0908
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/ClassifiedBitCountingMetadata.py
@@ -0,0 +1,73 @@
+# 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
new file mode 100644
index 0000000000..7fdea7c162
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/ClassifiedMetadataFactory.py
@@ -0,0 +1,42 @@
+# 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
new file mode 100644
index 0000000000..9de8ae8919
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/RunGroup.py
@@ -0,0 +1,34 @@
+# 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
new file mode 100644
index 0000000000..8e41ed9fe2
--- /dev/null
+++ b/PyPI/jumpavg/jumpavg/__init__.py
@@ -0,0 +1,16 @@
+# 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.cfg b/PyPI/jumpavg/setup.cfg
new file mode 100644
index 0000000000..b4abd1bd30
--- /dev/null
+++ b/PyPI/jumpavg/setup.cfg
@@ -0,0 +1,7 @@
+[metadata]
+# This includes the license file in the wheel.
+license_file = LICENSE.txt
+
+[bdist_wheel]
+# TODO: Make the code work both on Python 2 and 3.
+universal=0
diff --git a/PyPI/jumpavg/setup.py b/PyPI/jumpavg/setup.py
new file mode 100644
index 0000000000..aa56efd9c9
--- /dev/null
+++ b/PyPI/jumpavg/setup.py
@@ -0,0 +1,52 @@
+"""A setup module for setuptools.
+
+See:
+https://packaging.python.org/en/latest/distributing.html
+"""
+
+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:
+    long_description = f.read()
+
+setup(
+    name="jumpavg",
+    version="0.1.2",  # This is currently the only place listing the version.
+    description="Library for finding changes in time series by grouping results.",
+    long_description=long_description,
+    long_description_content_type="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",
+    classifiers=[
+        "Development Status :: 3 - Alpha",
+        "Intended Audience :: Science/Research",
+        # Pick your license as you wish
+        "License :: OSI Approved :: Apache Software License",
+        "Natural Language :: English",
+        # TODO: Test which Python versions is the code compatible with.
+        "Programming Language :: Python :: 2.7",
+        "Topic :: Scientific/Engineering :: Information Analysis"
+    ],
+    keywords="progression regression anomaly detection",
+    packages=find_packages(exclude=[]),
+    # TODO: python_requires="~=2.7"
+    install_requires=[],
+    # TODO: Include simulator and tests.
+    extras_require={
+    },
+    package_data={
+    },
+    entry_points={
+        "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",
+    },
+)