1 files changed, 53 insertions, 0 deletions
diff --git a/resources/libraries/python/MLRsearch/strategy/refine_lo.py b/resources/libraries/python/MLRsearch/strategy/refine_lo.py
new file mode 100644
index 0000000000..7927798505
--- /dev/null
+++ b/resources/libraries/python/MLRsearch/strategy/refine_lo.py
@@ -0,0 +1,53 @@
+# 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 RefineLoStrategy class."""
+
+
+from dataclasses import dataclass
+from typing import Optional, Tuple
+
+from ..discrete_load import DiscreteLoad
+from ..discrete_width import DiscreteWidth
+from ..relevant_bounds import RelevantBounds
+from .base import StrategyBase
+
+
+@dataclass
+class RefineLoStrategy(StrategyBase):
+    """If initial lower bound is still worth it, nominate it.
+
+    This usually happens when halving resulted in relevant upper bound,
+    or if there was no halving.
+    This ensures a relevant bound (upper or lower) for the current target
+    exists.
+    """
+
+    def nominate(
+        self, bounds: RelevantBounds
+    ) -> Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]:
+        """Nominate the initial lower bound.
+
+        :param bounds: Freshly updated bounds relevant for current target.
+        :type bounds: RelevantBounds
+        :returns: Two nones or candidate intended load and duration.
+        :rtype: Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]
+        """
+        if not (load := self.initial_lower_load):
+            return None, None
+        if self.not_worth(bounds=bounds, load=load):
+            return None, None
+        self.debug(f"Lowerbound refinement available: {load}")
+        # TODO: Limit to possibly smaller than target width?
+        self.expander.limit(self.target.discrete_width)
+        return load, self.target.discrete_width