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# Copyright (c) 2021 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 defining PerDurationDatabase class."""
import copy
class PerDurationDatabase:
"""List-like structure holding measurement results for one duration.
This is a building block for MeasurementDatabase.
This class hold measurements for single target duration value only,
so the logic is quite simple.
Several utility methods are added, accomplishing tasks useful for MLRsearch
(to be called by MeasurementDatabade).
"""
def __init__(self, duration, measurements):
"""Store (deep copy of) measurement results and normalize them.
The results have to have the corresponding target duration,
and there should be no duplicate target_tr values.
Empty iterable (zero measurements) is an acceptable input.
:param duration: All measurements have to have this target duration [s].
:param measurements: The measurement results to store.
:type duration: float
:type measurements: Iterable[ReceiveRateMeasurement]
:raises ValueError: If duration does not match or if TR duplicity.
"""
self.duration = duration
self.measurements = [copy.deepcopy(meas) for meas in measurements]
self._normalize()
def __repr__(self):
"""Return string executable to get equivalent instance.
:returns: Code to construct equivalent instance.
:rtype: str
"""
return (
u"PerDurationDatabase("
f"duration={self.duration!r},"
f"measurements={self.measurements!r})"
)
def _normalize(self):
"""Sort by target_tr, fail on detecting duplicate target_tr.
Also set effective loss ratios.
"""
measurements = self.measurements
measurements.sort(key=lambda measurement: measurement.target_tr)
# Detect duplicated TRs.
previous_tr = None
for measurement in measurements:
current_tr = measurement.target_tr
if current_tr == previous_tr:
raise ValueError(
u"Transmit rate conflict:"
f" {measurement!r} {previous_tr!r}"
)
previous_tr = current_tr
# Update effective ratios.
ratio_previous = None
for measurement in measurements:
if ratio_previous is None:
ratio_previous = measurement.loss_ratio
measurement.effective_loss_ratio = ratio_previous
continue
ratio_previous = max(ratio_previous, measurement.loss_ratio)
measurement.effective_loss_ratio = ratio_previous
def add(self, measurement):
"""Add measurement and normalize.
:param measurement: Measurement result to add to the database.
:type measurement: ReceiveRateMeasurement
"""
# TODO: We should deepcopy either everywhere or nowhere.
self.measurements.append(measurement)
self._normalize()
def get_valid_bounds(self, ratio):
"""Return None or a valid measurement for two tightest bounds.
The validity of a measurement to act as a bound is determined
by comparing the argument ratio with measurement's effective loss ratio.
Both lower and upper bounds are returned, both tightest and second
tightest. If some value is not available, None is returned instead.
:param ratio: Target ratio, valid has to be lower or equal.
:type ratio: float
:returns: Tightest lower bound, tightest upper bound,
second tightest lower bound, second tightest upper bound.
:rtype: 4-tuple of Optional[ReceiveRateMeasurement]
"""
lower_1, upper_1, lower_2, upper_2 = None, None, None, None
for measurement in self.measurements:
if measurement.effective_loss_ratio > ratio:
if upper_1 is None:
upper_1 = measurement
continue
upper_2 = measurement
break
lower_1, lower_2 = measurement, lower_1
return lower_1, upper_1, lower_2, upper_2
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