diff options
Diffstat (limited to 'resources/libraries/python/DropRateSearch.py')
| -rw-r--r-- | resources/libraries/python/DropRateSearch.py | 237 |
1 files changed, 155 insertions, 82 deletions
diff --git a/resources/libraries/python/DropRateSearch.py b/resources/libraries/python/DropRateSearch.py index 1fba43efab..c25f34fcf6 100644 --- a/resources/libraries/python/DropRateSearch.py +++ b/resources/libraries/python/DropRateSearch.py @@ -16,6 +16,7 @@ from abc import ABCMeta, abstractmethod from enum import Enum, unique + @unique class SearchDirection(Enum): """Direction of linear search.""" @@ -23,6 +24,7 @@ class SearchDirection(Enum): TOP_DOWN = 1 BOTTOM_UP = 2 + @unique class SearchResults(Enum): """Result of the drop rate search.""" @@ -31,6 +33,7 @@ class SearchResults(Enum): FAILURE = 2 SUSPICIOUS = 3 + @unique class RateType(Enum): """Type of rate units.""" @@ -39,6 +42,7 @@ class RateType(Enum): PACKETS_PER_SECOND = 2 BITS_PER_SECOND = 3 + @unique class LossAcceptanceType(Enum): """Type of the loss acceptance criteria.""" @@ -46,6 +50,7 @@ class LossAcceptanceType(Enum): FRAMES = 1 PERCENTAGE = 2 + @unique class SearchResultType(Enum): """Type of search result evaluation.""" @@ -53,42 +58,43 @@ class SearchResultType(Enum): BEST_OF_N = 1 WORST_OF_N = 2 + class DropRateSearch(object): """Abstract class with search algorithm implementation.""" __metaclass__ = ABCMeta def __init__(self): - #duration of traffic run (binary, linear) + # duration of traffic run (binary, linear) self._duration = 60 - #initial start rate (binary, linear) + # initial start rate (binary, linear) self._rate_start = 100 - #step of the linear search, unit: RateType (self._rate_type) + # step of the linear search, unit: RateType (self._rate_type) self._rate_linear_step = 10 - #last rate of the binary search, unit: RateType (self._rate_type) + # last rate of the binary search, unit: RateType (self._rate_type) self._last_binary_rate = 0 - #linear search direction, permitted values: SearchDirection + # linear search direction, permitted values: SearchDirection self._search_linear_direction = SearchDirection.TOP_DOWN - #upper limit of search, unit: RateType (self._rate_type) + # upper limit of search, unit: RateType (self._rate_type) self._rate_max = 100 - #lower limit of search, unit: RateType (self._rate_type) + # lower limit of search, unit: RateType (self._rate_type) self._rate_min = 1 - #permitted values: RateType + # permitted values: RateType self._rate_type = RateType.PERCENTAGE - #accepted loss during search, units: LossAcceptanceType + # accepted loss during search, units: LossAcceptanceType self._loss_acceptance = 0 - #permitted values: LossAcceptanceType + # permitted values: LossAcceptanceType self._loss_acceptance_type = LossAcceptanceType.FRAMES - #size of frames to send + # size of frames to send self._frame_size = "64" - #binary convergence criterium type is self._rate_type - self._binary_convergence_threshold = 100000 - #numbers of traffic runs during one rate step + # binary convergence criterium type is self._rate_type + self._binary_convergence_threshold = 5000 + # numbers of traffic runs during one rate step self._max_attempts = 1 - #type of search result evaluation, unit: SearchResultType + # type of search result evaluation, unit: SearchResultType self._search_result_type = SearchResultType.BEST_OF_N - #result of search + # result of search self._search_result = None self._search_result_rate = None @@ -97,17 +103,17 @@ class DropRateSearch(object): loss_acceptance_type, traffic_type): """Send traffic from TG and measure count of dropped frames. - :param rate: offered traffic load - :param frame_size: size of frame - :param loss_acceptance: permitted drop ratio or frames count - :param loss_acceptance_type: type of permitted loss - :param traffic_type: traffic profile ([2,3]-node-L[2,3], ...) + :param rate: Offered traffic load. + :param frame_size: Size of frame. + :param loss_acceptance: Permitted drop ratio or frames count. + :param loss_acceptance_type: Type of permitted loss. + :param traffic_type: Traffic profile ([2,3]-node-L[2,3], ...). :type rate: int :type frame_size: str :type loss_acceptance: float :type loss_acceptance_type: LossAcceptanceType :type traffic_type: str - :return: drop threshold exceeded? (True/False) + :return: Drop threshold exceeded? (True/False) :rtype bool """ pass @@ -115,8 +121,8 @@ class DropRateSearch(object): def set_search_rate_boundaries(self, max_rate, min_rate): """Set search boundaries: min,max. - :param max_rate: upper value of search boundaries - :param min_rate: lower value of search boundaries + :param max_rate: Upper value of search boundaries. + :param min_rate: Lower value of search boundaries. :type max_rate: float :type min_rate: float :return: nothing @@ -132,7 +138,7 @@ class DropRateSearch(object): def set_search_linear_step(self, step_rate): """Set step size for linear search. - :param step_rate: linear search step size + :param step_rate: Linear search step size. :type step_rate: float :return: nothing """ @@ -162,7 +168,7 @@ class DropRateSearch(object): def _set_search_rate_type(self, rate_type): """Set rate type to one of RateType-s. - :param rate_type: type of rate to set + :param rate_type: Type of rate to set. :type rate_type: RateType :return: nothing """ @@ -174,7 +180,7 @@ class DropRateSearch(object): def set_search_frame_size(self, frame_size): """Set size of frames to send. - :param frame_size: size of frames + :param frame_size: Size of frames. :type frame_size: str :return: nothing """ @@ -183,7 +189,7 @@ class DropRateSearch(object): def set_duration(self, duration): """Set the duration of single traffic run. - :param duration: number of seconds for traffic to run + :param duration: Number of seconds for traffic to run. :type duration: int :return: nothing """ @@ -192,7 +198,7 @@ class DropRateSearch(object): def get_duration(self): """Return configured duration of single traffic run. - :return: number of seconds for traffic to run + :return: Number of seconds for traffic to run. :rtype: int """ return self._duration @@ -200,7 +206,7 @@ class DropRateSearch(object): def set_binary_convergence_threshold(self, convergence): """Set convergence for binary search. - :param convergence: treshold value number + :param convergence: Treshold value number. :type convergence: float :return: nothing """ @@ -209,7 +215,7 @@ class DropRateSearch(object): def get_binary_convergence_threshold(self): """Get convergence for binary search. - :return: treshold value number + :return: Treshold value number. :rtype: float """ return self._binary_convergence_threshold @@ -217,7 +223,7 @@ class DropRateSearch(object): def get_rate_type_str(self): """Return rate type representation. - :return: string representation of rate type + :return: String representation of rate type. :rtype: str """ if self._rate_type == RateType.PERCENTAGE: @@ -232,7 +238,7 @@ class DropRateSearch(object): def set_max_attempts(self, max_attempts): """Set maximum number of traffic runs during one rate step. - :param max_attempts: number of traffic runs + :param max_attempts: Number of traffic runs. :type max_attempts: int :return: nothing """ @@ -244,7 +250,7 @@ class DropRateSearch(object): def get_max_attempts(self): """Return maximum number of traffic runs during one rate step. - :return: number of traffic runs + :return: Number of traffic runs. :rtype: int """ return self._max_attempts @@ -266,7 +272,7 @@ class DropRateSearch(object): def _set_search_result_type(self, search_type): """Set type of search result evaluation to one of SearchResultType. - :param search_type: type of search result evaluation to set + :param search_type: Type of search result evaluation to set. :type search_type: SearchResultType :return: nothing """ @@ -275,34 +281,36 @@ class DropRateSearch(object): else: self._search_result_type = search_type - def _get_best_of_n(self, res_list): + @staticmethod + def _get_best_of_n(res_list): """Return best result of N traffic runs. - :param res_list: list of return values from all runs at one rate step + :param res_list: List of return values from all runs at one rate step. :type res_list: list - :return: True if at least one run is True, False otherwise + :return: True if at least one run is True, False otherwise. :rtype: boolean """ - #Return True if any element of the iterable is True. + # Return True if any element of the iterable is True. return any(res_list) - def _get_worst_of_n(self, res_list): + @staticmethod + def _get_worst_of_n(res_list): """Return worst result of N traffic runs. - :param res_list: list of return values from all runs at one rate step + :param res_list: List of return values from all runs at one rate step. :type res_list: list - :return: False if at least one run is False, True otherwise + :return: False if at least one run is False, True otherwise. :rtype: boolean """ - #Return False if not all elements of the iterable are True. + # Return False if not all elements of the iterable are True. return not all(res_list) - def _get_result_based_on_search_type(self, res_list): + def _get_res_based_on_search_type(self, res_list): """Return result of search based on search evaluation type. - :param res_list: list of return values from all runs at one rate step + :param res_list: List of return values from all runs at one rate step. :type res_list: list - :return: Boolean based on search result type + :return: Boolean based on search result type. :rtype: boolean """ if self._search_result_type == SearchResultType.BEST_OF_N: @@ -316,8 +324,8 @@ class DropRateSearch(object): def linear_search(self, start_rate, traffic_type): """Linear search of rate with loss below acceptance criteria. - :param start_rate: initial rate - :param traffic_type: traffic profile + :param start_rate: Initial rate. + :param traffic_type: Traffic profile. :type start_rate: float :param traffic_type: str :return: nothing @@ -327,25 +335,25 @@ class DropRateSearch(object): raise ValueError("Start rate is not in min,max range") rate = float(start_rate) - #the last but one step + # the last but one step prev_rate = None - #linear search + # linear search while True: res = [] - for n in range(self._max_attempts): + for dummy in range(self._max_attempts): res.append(self.measure_loss(rate, self._frame_size, self._loss_acceptance, self._loss_acceptance_type, traffic_type)) - res = self._get_result_based_on_search_type(res) + res = self._get_res_based_on_search_type(res) if self._search_linear_direction == SearchDirection.BOTTOM_UP: - #loss occured and it was above acceptance criteria - if res == False: - #if this is first run then we didn't find drop rate - if prev_rate == None: + # loss occured and it was above acceptance criteria + if not res: + # if this is first run then we didn't find drop rate + if prev_rate is None: self._search_result = SearchResults.FAILURE self._search_result_rate = None return @@ -354,13 +362,13 @@ class DropRateSearch(object): self._search_result = SearchResults.SUCCESS self._search_result_rate = prev_rate return - #there was no loss / loss below acceptance criteria - elif res == True: + # there was no loss / loss below acceptance criteria + elif res: prev_rate = rate rate += self._rate_linear_step if rate > self._rate_max: if prev_rate != self._rate_max: - #one last step with rate set to _rate_max + # one last step with rate set to _rate_max rate = self._rate_max continue else: @@ -373,13 +381,13 @@ class DropRateSearch(object): raise RuntimeError("Unknown search result") elif self._search_linear_direction == SearchDirection.TOP_DOWN: - #loss occured, decrease rate - if res == False: + # loss occured, decrease rate + if not res: prev_rate = rate rate -= self._rate_linear_step if rate < self._rate_min: if prev_rate != self._rate_min: - #one last step with rate set to _rate_min + # one last step with rate set to _rate_min rate = self._rate_min continue else: @@ -388,8 +396,8 @@ class DropRateSearch(object): return else: continue - #no loss => non/partial drop rate found - elif res == True: + # no loss => non/partial drop rate found + elif res: self._search_result = SearchResults.SUCCESS self._search_result_rate = rate return @@ -403,20 +411,21 @@ class DropRateSearch(object): def verify_search_result(self): """Fail if search was not successful. - :return: result rate + :return: Result rate. :rtype: float """ if self._search_result == SearchResults.FAILURE: raise Exception('Search FAILED') - elif self._search_result in [SearchResults.SUCCESS, SearchResults.SUSPICIOUS]: + elif self._search_result in [SearchResults.SUCCESS, + SearchResults.SUSPICIOUS]: return self._search_result_rate def binary_search(self, b_min, b_max, traffic_type): """Binary search of rate with loss below acceptance criteria. - :param b_min: min range rate - :param b_max: max range rate - :param traffic_type: traffic profile + :param b_min: Min range rate. + :param b_max: Max range rate. + :param traffic_type: Traffic profile. :type b_min: float :type b_max: float :type traffic_type: str @@ -430,13 +439,13 @@ class DropRateSearch(object): if float(b_max) < float(b_min): raise ValueError("Min rate is greater then max rate") - #binary search - #rate is half of interval + start of interval + # binary search + # rate is half of interval + start of interval rate = ((float(b_max) - float(b_min)) / 2) + float(b_min) - #rate diff with previous run + # rate diff with previous run rate_diff = abs(self._last_binary_rate - rate) - #convergence criterium + # convergence criterium if float(rate_diff) < float(self._binary_convergence_threshold): if not self._search_result_rate: self._search_result = SearchResults.FAILURE @@ -447,23 +456,87 @@ class DropRateSearch(object): self._last_binary_rate = rate res = [] - for n in range(self._max_attempts): + for dummy in range(self._max_attempts): res.append(self.measure_loss(rate, self._frame_size, self._loss_acceptance, self._loss_acceptance_type, traffic_type)) - res = self._get_result_based_on_search_type(res) + res = self._get_res_based_on_search_type(res) - #loss occured and it was above acceptance criteria - if res == False: + # loss occured and it was above acceptance criteria + if not res: self.binary_search(b_min, rate, traffic_type) - #there was no loss / loss below acceptance criteria - elif res == True: + # there was no loss / loss below acceptance criteria + else: self._search_result_rate = rate self.binary_search(rate, b_max, traffic_type) + + def combined_search(self, start_rate, traffic_type): + """Combined search of rate with loss below acceptance criteria. + + :param start_rate: Initial rate. + :param traffic_type: Traffic profile. + :type start_rate: float + :type traffic_type: str + :return: nothing + """ + + self.linear_search(start_rate, traffic_type) + + if self._search_result in [SearchResults.SUCCESS, + SearchResults.SUSPICIOUS]: + b_min = self._search_result_rate + b_max = self._search_result_rate + self._rate_linear_step + + # we found max rate by linear search + if self.floats_are_close_equal(float(b_min), self._rate_max): + return + + # limiting binary range max value into max range + if float(b_max) > self._rate_max: + b_max = self._rate_max + + # reset result rate + temp_rate = self._search_result_rate + self._search_result_rate = None + + # we will use binary search to refine search in one linear step + self.binary_search(b_min, b_max, traffic_type) + + # linear and binary search succeed + if self._search_result == SearchResults.SUCCESS: + return + # linear search succeed but binary failed or suspicious + else: + self._search_result = SearchResults.SUSPICIOUS + self._search_result_rate = temp_rate else: - raise RuntimeError("Unknown search result") + raise RuntimeError("Linear search FAILED") + + @staticmethod + def floats_are_close_equal(num_a, num_b, rel_tol=1e-9, abs_tol=0.0): + """Compares two float numbers for close equality. + + :param num_a: First number to compare. + :param num_b: Second number to compare. + :param rel_tol=1e-9: The relative tolerance. + :param abs_tol=0.0: The minimum absolute tolerance level. + :type num_a: float + :type num_b: float + :type rel_tol: float + :type abs_tol: float + :return: Returns True if num_a is close in value to num_b or equal. + False otherwise. + :rtype: boolean + """ + + if num_a == num_b: + return True + + if rel_tol < 0.0 or abs_tol < 0.0: + raise ValueError('Error tolerances must be non-negative') + + return abs(num_b - num_a) <= max(rel_tol * max(abs(num_a), abs(num_b)), + abs_tol) - def combined_search(self): - raise NotImplementedError |