X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Flibraries%2Fpython%2FDropRateSearch.py;h=d090306cc5ffdbf8182f3de3f6f667319d29e7e2;hb=374ea2f45d17f361aa612becba657ecaade0d0b5;hp=912d2e9f53fd8a0ef5a562933c5b6b46401dfb88;hpb=4c6fe5602edcbd9857a846e5b13a21d5c671a2c8;p=csit.git

diff --git a/resources/libraries/python/DropRateSearch.py b/resources/libraries/python/DropRateSearch.py
index 912d2e9f53..d090306cc5 100644
--- a/resources/libraries/python/DropRateSearch.py
+++ b/resources/libraries/python/DropRateSearch.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2018 Cisco and/or its affiliates.
+# Copyright (c) 2019 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:
@@ -403,44 +403,13 @@ class DropRateSearch(object):
         while True:
             res = []
             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.append(self.measure_loss(
+                    rate, self._frame_size, self._loss_acceptance,
+                    self._loss_acceptance_type, traffic_type))
 
             res = self._get_res_based_on_search_type(res)
 
-            if self._search_linear_direction == SearchDirection.BOTTOM_UP:
-                # loss occurred 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
-                    # else we found the rate, which is value from previous run
-                    else:
-                        self._search_result = SearchResults.SUCCESS
-                        self._search_result_rate = prev_rate
-                    return
-                # 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
-                            rate = self._rate_max
-                            continue
-                        else:
-                            self._search_result = SearchResults.SUCCESS
-                            self._search_result_rate = prev_rate
-                            return
-                    else:
-                        continue
-                else:
-                    raise RuntimeError("Unknown search result")
-
-            elif self._search_linear_direction == SearchDirection.TOP_DOWN:
+            if self._search_linear_direction == SearchDirection.TOP_DOWN:
                 # loss occurred, decrease rate
                 if not res:
                     prev_rate = rate
@@ -466,8 +435,6 @@ class DropRateSearch(object):
             else:
                 raise Exception("Unknown search direction")
 
-        raise Exception("Wrong codepath")
-
     def verify_search_result(self):
         """Fail if search was not successful.
 
@@ -475,11 +442,10 @@ class DropRateSearch(object):
         :rtype: tuple
         :raises Exception: If search failed.
         """
-        if self._search_result == SearchResults.FAILURE:
-            raise Exception('Search FAILED')
-        elif self._search_result in [SearchResults.SUCCESS,
-                                     SearchResults.SUSPICIOUS]:
+        if self._search_result in [
+                SearchResults.SUCCESS, SearchResults.SUSPICIOUS]:
             return self._search_result_rate, self.get_latency()
+        raise Exception('Search FAILED')
 
     def binary_search(self, b_min, b_max, traffic_type, skip_max_rate=False,
                       skip_warmup=False):