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, 112 insertions, 0 deletions

diff --git a/resources/libraries/python/MLRsearch/load_stats.py b/resources/libraries/python/MLRsearch/load_stats.py
new file mode 100644
index 0000000000..5f4757f488
--- /dev/null
+++ b/resources/libraries/python/MLRsearch/load_stats.py
@@ -0,0 +1,112 @@
+# 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 LoadStats class."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Dict, Tuple
+
+from .target_spec import TargetSpec
+from .target_stat import TargetStat
+from .discrete_load import DiscreteLoad
+from .discrete_result import DiscreteResult
+
+
+# The eq=False part is needed to make sure comparison is inherited properly.
+@dataclass(eq=False)
+class LoadStats(DiscreteLoad):
+    """An offered load together with stats for all possible targets.
+
+    As LoadStats is frequently passed instead of plan DiscreteLoad,
+    equality and ordering is dictated by the float load.
+    """
+
+    target_to_stat: Dict[TargetSpec, TargetStat] = None
+    """Mapping from target specification to its current stat for this load."""
+
+    def __post_init__(self) -> None:
+        """Initialize load value and check there are targets to track."""
+        super().__post_init__()
+        if not self.target_to_stat:
+            raise ValueError(f"No targets: {self.target_to_stat!r}")
+
+    def __str__(self) -> str:
+        """Convert into a short human-readable string.
+
+        This works well only for trimmed stats,
+        as only the stat for the first target present is shown.
+
+        :returns: The short string.
+        :rtype: str
+        """
+        return (
+            f"fl={self.float_load}"
+            f",s=({next(iter(self.target_to_stat.values()))})"
+        )
+
+    def __hash__(self) -> int:
+        """Raise as stats are mutable by definition.
+
+        :returns: Hash value for this instance if possible.
+        :rtype: int
+        :raises TypeError: Not immutable.
+        """
+        raise TypeError("Loadstats are mutable so constant hash is impossible.")
+
+    def add(self, result: DiscreteResult) -> None:
+        """Take into account one more trial measurement result.
+
+        :param result: The result to take into account.
+        :type result: DiscreteResult
+        :raises RuntimeError: If result load does is not equal to the self load.
+        """
+        if result.intended_load != float(self):
+            raise RuntimeError(
+                f"Attempting to add load {result.intended_load}"
+                f" to result set for {float(self)}"
+            )
+        for stat in self.target_to_stat.values():
+            stat.add(result)
+
+    @staticmethod
+    def new_empty(load: DiscreteLoad, targets: Tuple[TargetSpec]) -> LoadStats:
+        """Factory method to initialize mapping for given targets.
+
+        :param load: The intended load value for the new instance.
+        :param targets: The target specifications to track stats for.
+        :type load: DiscreteLoad
+        :type targets: Tuple[TargetSpec]
+        :returns: New instance with empty stats initialized.
+        :rtype: LoadStats
+        :raise ValueError: Is the load is not rounded.
+        """
+        if not load.is_round:
+            raise ValueError(f"Not round: {load!r}")
+        return LoadStats(
+            rounding=load.rounding,
+            int_load=int(load),
+            target_to_stat={target: TargetStat(target) for target in targets},
+        )
+
+    def estimates(self, target: TargetSpec) -> Tuple[bool, bool]:
+        """Classify this load according to given target.
+
+        :param target: According to which target this should be classified.
+        :type target: TargetSpec
+        :returns: Tuple of two estimates whether load can be lower bound.
+            (True, False) means target is not reached yet.
+        :rtype: Tuple[bool, bool]
+        """
+        return self.target_to_stat[target].estimates()