Add De Morgan's to rules expression + comments

tests/unit/acquisition/test_rule.py

@@ -1816,7 +1816,7 @@ def test_multi_trust_region_box_acquire_filters() -> None:
 
     # Create a BatchTrustRegionBox instance with the mock base_rule.
     subspaces = [SingleObjectiveTrustRegionBox(search_space) for _ in range(2)]
-    rule = BatchTrustRegionBox(subspaces, mock_base_rule)  # type: ignore[var-annotated]
+    rule: BatchTrustRegionBox[ProbabilisticModel] = BatchTrustRegionBox(subspaces, mock_base_rule)
 
     rule.acquire(search_space, models, datasets)(None)
 

trieste/acquisition/rule.py

@@ -1234,8 +1234,8 @@ def acquire(
         # Otherwise, run the base rule as is (i.e as a batch), once with all models and datasets.
         # Note: this should only trigger on the first call to `acquire`, as after that we will
         # have a list of rules in `self._rules`.
-        if self._rules is None and (
-            _num_local_models > 0 or not isinstance(self._rule, EfficientGlobalOptimization)
+        if self._rules is None and not (
+            _num_local_models == 0 and isinstance(self._rule, EfficientGlobalOptimization)
         ):
             self._rules = [copy.deepcopy(self._rule) for _ in range(num_subspaces)]
 
@@ -1282,8 +1282,8 @@ def state_func(
                     _points.append(rule.acquire(subspace, _models, _datasets))
                 points = tf.stack(_points, axis=1)
             else:
-                # Filter out local datasets as this is the EGO rule with normal acquisition
-                # functions that don't expect local datasets.
+                # Filter out local datasets as this is a rule (currently only EGO) with normal
+                # acquisition functions that don't expect local datasets.
                 # Note: no need to filter out local models, as setups with local models
                 # are handled above (i.e. we run the base rule sequentially for each subspace).
                 if datasets is not None: