resources/tools/presentation/new/jumpavg/BitCountingClassifier.py

   1 # Copyright (c) 2018 Cisco and/or its affiliates.
   2 # Licensed under the Apache License, Version 2.0 (the "License");
   3 # you may not use this file except in compliance with the License.
   4 # You may obtain a copy of the License at:
   5 #
   6 #     http://www.apache.org/licenses/LICENSE-2.0
   7 #
   8 # Unless required by applicable law or agreed to in writing, software
   9 # distributed under the License is distributed on an "AS IS" BASIS,
  10 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  11 # See the License for the specific language governing permissions and
  12 # limitations under the License.
  13
  14 from BitCountingGroup import BitCountingGroup
  15 from BitCountingGroupList import BitCountingGroupList
  16 from BitCountingMetadataFactory import BitCountingMetadataFactory
  17 from ClassifiedMetadataFactory import ClassifiedMetadataFactory
  18
  19
  20 class BitCountingClassifier(object):
  21
  22     @staticmethod
  23     def classify(values):
  24         """Return the values in groups of optimal bit count.
  25
  26         TODO: Could we return BitCountingGroupList and let caller process it?
  27
  28         :param values: Sequence of runs to classify.
  29         :type values: Iterable of float or of AvgStdevMetadata
  30         :returns: Classified group list.
  31         :rtype: list of BitCountingGroup
  32         """
  33         max_value = BitCountingMetadataFactory.find_max_value(values)
  34         factory = BitCountingMetadataFactory(max_value)
  35         opened_at = []
  36         closed_before = [BitCountingGroupList()]
  37         for index, value in enumerate(values):
  38             singleton = BitCountingGroup(factory, [value])
  39             newly_opened = closed_before[index].with_group_appended(singleton)
  40             opened_at.append(newly_opened)
  41             record_group_list = newly_opened
  42             for previous in range(index):
  43                 previous_opened_list = opened_at[previous]
  44                 still_opened = (
  45                     previous_opened_list.with_value_added_to_last_group(value))
  46                 opened_at[previous] = still_opened
  47                 if still_opened.bits < record_group_list.bits:
  48                     record_group_list = still_opened
  49             closed_before.append(record_group_list)
  50         partition = closed_before[-1]
  51         previous_average = partition[0].metadata.avg
  52         for group in partition:
  53             if group.metadata.avg == previous_average:
  54                 group.metadata = ClassifiedMetadataFactory.with_classification(
  55                     group.metadata, "normal")
  56             elif group.metadata.avg < previous_average:
  57                 group.metadata = ClassifiedMetadataFactory.with_classification(
  58                     group.metadata, "regression")
  59             elif group.metadata.avg > previous_average:
  60                 group.metadata = ClassifiedMetadataFactory.with_classification(
  61                     group.metadata, "progression")
  62             previous_average = group.metadata.avg
  63         return partition.group_list