Patch: Start binary search from max range rate

[csit.git] / resources / libraries / python / DropRateSearch.py

diff --git a/resources/libraries/python/DropRateSearch.py b/resources/libraries/python/DropRateSearch.py
index c25f34f..8f8e371 100644 (file)
--- a/resources/libraries/python/DropRateSearch.py
+++ b/resources/libraries/python/DropRateSearch.py
@@ -320,14 +320,13 @@ class DropRateSearch(object):
         else:
             raise ValueError("Unknown search result type")
 
-
     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.
         :type start_rate: float
-        :param traffic_type: str
+        :type traffic_type: str
         :return: nothing
         """
 
@@ -350,7 +349,7 @@ class DropRateSearch(object):
             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
+                # 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:
@@ -381,7 +380,7 @@ class DropRateSearch(object):
                     raise RuntimeError("Unknown search result")
 
             elif self._search_linear_direction == SearchDirection.TOP_DOWN:
-                # loss occured, decrease rate
+                # loss occurred, decrease rate
                 if not res:
                     prev_rate = rate
                     rate -= self._rate_linear_step
@@ -420,15 +419,17 @@ class DropRateSearch(object):
                                      SearchResults.SUSPICIOUS]:
             return self._search_result_rate
 
-    def binary_search(self, b_min, b_max, traffic_type):
+    def binary_search(self, b_min, b_max, traffic_type, skip_max_rate=False):
         """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 skip_max_rate: Start with max rate first
         :type b_min: float
         :type b_max: float
         :type traffic_type: str
+        :type skip_max_rate: bool
         :return: nothing
         """
 
@@ -437,11 +438,15 @@ class DropRateSearch(object):
         if not self._rate_min <= float(b_max) <= self._rate_max:
             raise ValueError("Max rate is not in min,max range")
         if float(b_max) < float(b_min):
-            raise ValueError("Min rate is greater then max rate")
+            raise ValueError("Min rate is greater than max rate")
 
         # binary search
-        # rate is half of interval + start of interval
-        rate = ((float(b_max) - float(b_min)) / 2) + float(b_min)
+        if skip_max_rate:
+            # rate is half of interval + start of interval
+            rate = ((float(b_max) - float(b_min)) / 2) + float(b_min)
+        else:
+            # rate is max of interval
+            rate =  float(b_max)
         # rate diff with previous run
         rate_diff = abs(self._last_binary_rate - rate)
 
@@ -464,13 +469,13 @@ class DropRateSearch(object):
 
         res = self._get_res_based_on_search_type(res)
 
-        # loss occured and it was above acceptance criteria
+        # loss occurred and it was above acceptance criteria
         if not res:
-            self.binary_search(b_min, rate, traffic_type)
+            self.binary_search(b_min, rate, traffic_type, True)
         # there was no loss / loss below acceptance criteria
         else:
             self._search_result_rate = rate
-            self.binary_search(rate, b_max, traffic_type)
+            self.binary_search(rate, b_max, traffic_type, True)
 
     def combined_search(self, start_rate, traffic_type):
         """Combined search of rate with loss below acceptance criteria.
@@ -502,7 +507,7 @@ class DropRateSearch(object):
             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)
+            self.binary_search(b_min, b_max, traffic_type, True)
 
             # linear and binary search succeed
             if self._search_result == SearchResults.SUCCESS: