Refactor jumpavg to be more readable and usable

[csit.git] / PyPI / jumpavg / jumpavg / AvgStdevMetadataFactory.py

diff --git a/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py b/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py
deleted file mode 100644 (file)
index 25bc600..0000000
--- a/PyPI/jumpavg/jumpavg/AvgStdevMetadataFactory.py
+++ /dev/null
@@ -1,54 +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 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
-        """
-        # Using Welford method to be more resistant to rounding errors.
-        # Adapted from code for sample standard deviation at:
-        # https://www.johndcook.com/blog/standard_deviation/
-        # The logic of plus operator is taken from
-        # https://www.johndcook.com/blog/skewness_kurtosis/
-        size = 0
-        avg = 0.0
-        moment_2 = 0.0
-        for value in values:
-            if not isinstance(value, AvgStdevMetadata):
-                value = AvgStdevMetadata(size=1, avg=value)
-            old_size = size
-            delta = value.avg - avg
-            size += value.size
-            avg += delta * value.size / size
-            moment_2 += value.stdev * value.stdev * value.size
-            moment_2 += delta * delta * old_size * value.size / size
-        if size < 1:
-            return AvgStdevMetadata()
-        stdev = math.sqrt(moment_2 / size)
-        ret_obj = AvgStdevMetadata(size=size, avg=avg, stdev=stdev)
-        return ret_obj