feat(MLRsearch): use goal result as in draft05

[csit.git] / resources / libraries / python / MLRsearch / multiple_loss_ratio_search.py

diff --git a/resources/libraries/python/MLRsearch/multiple_loss_ratio_search.py b/resources/libraries/python/MLRsearch/multiple_loss_ratio_search.py
index 9f7be4f..4d3ff7c 100644 (file)
--- a/resources/libraries/python/MLRsearch/multiple_loss_ratio_search.py
+++ b/resources/libraries/python/MLRsearch/multiple_loss_ratio_search.py
@@ -25,6 +25,7 @@ from .dataclass import secondary_field
 from .discrete_load import DiscreteLoad
 from .discrete_result import DiscreteResult
 from .expander import GlobalWidth
 from .discrete_load import DiscreteLoad
 from .discrete_result import DiscreteResult
 from .expander import GlobalWidth

+from .goal_result import GoalResult

 from .limit_handler import LimitHandler
 from .load_rounding import LoadRounding
 from .measurement_database import MeasurementDatabase
 from .limit_handler import LimitHandler
 from .load_rounding import LoadRounding
 from .measurement_database import MeasurementDatabase


@@ -33,7 +34,6 @@ from .search_goal import SearchGoal
 from .selector import Selector
 from .target_scaling import TargetScaling
 from .trial_measurement import AbstractMeasurer
 from .selector import Selector
 from .target_scaling import TargetScaling
 from .trial_measurement import AbstractMeasurer

-from .trimmed_stat import TrimmedStat

 
 
 @dataclass
 
 
 @dataclass


@@ -126,7 +126,7 @@ class MultipleLossRatioSearch:
         self,
         measurer: AbstractMeasurer,
         debug: Optional[Callable[[str], None]] = None,
         self,
         measurer: AbstractMeasurer,
         debug: Optional[Callable[[str], None]] = None,

-    ) -> Pep3140Dict[SearchGoal, Optional[TrimmedStat]]:
+    ) -> Pep3140Dict[SearchGoal, GoalResult]:

         """Perform initial trials, create state object, proceed with main loop.
 
         Stateful arguments (measurer and debug) are stored.
         """Perform initial trials, create state object, proceed with main loop.
 
         Stateful arguments (measurer and debug) are stored.


@@ -139,7 +139,7 @@ class MultipleLossRatioSearch:
         :returns: Structure containing conditional throughputs and other stats,
             one for each search goal. If a value is None it means there is
             no lower bound (min load turned out to be an upper bound).
         :returns: Structure containing conditional throughputs and other stats,
             one for each search goal. If a value is None it means there is
             no lower bound (min load turned out to be an upper bound).

-        :rtype: Pep3140Dict[SearchGoal, Optional[TrimmedStat]]
+        :rtype: Pep3140Dict[SearchGoal, GoalResult]

         :raises RuntimeError: If total duration is larger than timeout,
             or if min load becomes an upper bound for a search goal
             that has fail fast true.
         :raises RuntimeError: If total duration is larger than timeout,
             or if min load becomes an upper bound for a search goal
             that has fail fast true.


@@ -168,7 +168,7 @@ class MultipleLossRatioSearch:
         for goal in self.config.goals:
             target = self.scaling.goal_to_final_target[goal]
             bounds = self.database.get_relevant_bounds(target=target)
         for goal in self.config.goals:
             target = self.scaling.goal_to_final_target[goal]
             bounds = self.database.get_relevant_bounds(target=target)

-            ret_dict[goal] = bounds.clo
+            ret_dict[goal] = GoalResult.from_bounds(bounds=bounds)

         return ret_dict
 
     def measure(self, duration: float, load: DiscreteLoad) -> DiscreteResult:
         return ret_dict
 
     def measure(self, duration: float, load: DiscreteLoad) -> DiscreteResult: