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:
6 # http://www.apache.org/licenses/LICENSE-2.0
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.
14 from BitCountingGroup import BitCountingGroup
15 from BitCountingGroupList import BitCountingGroupList
16 from BitCountingMetadataFactory import BitCountingMetadataFactory
17 from ClassifiedMetadataFactory import ClassifiedMetadataFactory
20 class BitCountingClassifier(object):
24 """Return the values in groups of optimal bit count.
26 TODO: Could we return BitCountingGroupList and let caller process it?
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
33 max_value = BitCountingMetadataFactory.find_max_value(values)
34 factory = BitCountingMetadataFactory(max_value)
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]
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