feat(MLRsearch): MLRsearch v7

Replaces MLRv2, suitable for "big bang" upgrade across CSIT.
PyPI metadata updated only partially (full edits will come separately).
Pylint wants less complexity, but the differences are only minor.

+ Use the same (new CSIT) defaults everywhere, also in Python library.
+ Update also PLRsearch to use the new result class.
+ Make upper bound optional in UTI.
+ Fix ASTF approximate duration detection.
+ Do not keep approximated_receive_rate (for MRR) in result structure.

Change-Id: I03406f32d5c93f56b527cb3f93791b61955dfd74
Signed-off-by: Vratko Polak <vrpolak@cisco.com>

1 files changed, 103 insertions, 0 deletions

diff --git a/resources/libraries/python/MLRsearch/target_scaling.py b/resources/libraries/python/MLRsearch/target_scaling.py
new file mode 100644
index 0000000000..25114c311c
--- /dev/null
+++ b/resources/libraries/python/MLRsearch/target_scaling.py
@@ -0,0 +1,103 @@
+# Copyright (c) 2023 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 TargetScaling class."""
+
+from dataclasses import dataclass
+from typing import Dict, Tuple
+
+from .dataclass import secondary_field
+from .discrete_width import DiscreteWidth
+from .load_rounding import LoadRounding
+from .search_goal import SearchGoal
+from .search_goal_tuple import SearchGoalTuple
+from .target_spec import TargetSpec
+
+
+@dataclass
+class TargetScaling:
+    """Encapsulate targets derived from goals.
+
+    No default values for primaries, contructor call has to specify everything.
+    """
+
+    goals: SearchGoalTuple
+    """Set of goals to generate targets for."""
+    rounding: LoadRounding
+    """Rounding instance to use (targets have discrete width)."""
+    # Derived quantities.
+    targets: Tuple[TargetSpec] = secondary_field()
+    """The generated targets, linked into chains."""
+    goal_to_final_target: Dict[SearchGoal, TargetSpec] = secondary_field()
+    """Mapping from a goal to its corresponding final target."""
+
+    def __post_init__(self) -> None:
+        """For each goal create final, and non-final targets and link them."""
+        linked_targets = []
+        self.goal_to_final_target = {}
+        for goal in self.goals:
+            standalone_targets = []
+            # Final target.
+            width = DiscreteWidth(
+                rounding=self.rounding,
+                float_width=goal.relative_width,
+            ).rounded_down()
+            duration_sum = goal.duration_sum
+            target = TargetSpec(
+                loss_ratio=goal.loss_ratio,
+                exceed_ratio=goal.exceed_ratio,
+                discrete_width=width,
+                trial_duration=goal.final_trial_duration,
+                duration_sum=duration_sum,
+                expansion_coefficient=goal.expansion_coefficient,
+                fail_fast=goal.fail_fast,
+                preceding=None,
+            )
+            standalone_targets.append(target)
+            # Non-final targets.
+            preceding_targets = goal.preceding_targets
+            multiplier = (
+                pow(
+                    goal.initial_trial_duration / duration_sum,
+                    1.0 / preceding_targets,
+                )
+                if preceding_targets
+                else 1.0
+            )
+            for count in range(preceding_targets):
+                preceding_sum = duration_sum * pow(multiplier, count + 1)
+                if count + 1 >= preceding_targets:
+                    preceding_sum = goal.initial_trial_duration
+                trial_duration = min(goal.final_trial_duration, preceding_sum)
+                width *= 2
+                target = TargetSpec(
+                    loss_ratio=goal.loss_ratio,
+                    exceed_ratio=goal.exceed_ratio,
+                    discrete_width=width,
+                    trial_duration=trial_duration,
+                    duration_sum=preceding_sum,
+                    expansion_coefficient=goal.expansion_coefficient,
+                    fail_fast=False,
+                    preceding=None,
+                )
+                standalone_targets.append(target)
+            # Link preceding targets.
+            preceding_target = None
+            for target in reversed(standalone_targets):
+                linked_target = target.with_preceding(preceding_target)
+                linked_targets.append(linked_target)
+                preceding_target = linked_target
+            # Associate final target to the goal.
+            self.goal_to_final_target[goal] = linked_targets[-1]
+        # Store all targets as a tuple.
+        self.targets = tuple(linked_targets)