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authorVratko Polak <vrpolak@cisco.com>2018-06-14 14:04:03 +0200
committerTibor Frank <tifrank@cisco.com>2018-06-15 10:44:11 +0000
commit6149ec451efff00068f38e3343e66cdec7b943f4 (patch)
treeec51cb4339782d37889f29383f303f9bdf35faa0 /PyPI/jumpavg/jumpavg/BitCountingClassifier.py
parent2f99b522d591a95d6ac4f11db8a34b8162258ecd (diff)
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>
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diff --git a/PyPI/jumpavg/jumpavg/BitCountingClassifier.py b/PyPI/jumpavg/jumpavg/BitCountingClassifier.py
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+++ b/PyPI/jumpavg/jumpavg/BitCountingClassifier.py
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+# Copyright (c) 2018 Cisco and/or its affiliates.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at:
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""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