1 files changed, 0 insertions, 73 deletions
diff --git a/resources/tools/presentation/new/jumpavg/ClassifiedBitCountingMetadata.py b/resources/tools/presentation/new/jumpavg/ClassifiedBitCountingMetadata.py
deleted file mode 100644
index 29359f0908..0000000000
--- a/resources/tools/presentation/new/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)