optimize propagators related functions

nucs/propagators/propagators.py

@@ -132,8 +132,8 @@ def pop_propagator(triggered_propagators: NDArray, previous_prop_idx: int) -> in
     :param previous_prop_idx: the index of the previous propagator which has been selected
     :return: an index
     """
-    for prop_idx, triggered_prop in enumerate(triggered_propagators):
-        if triggered_prop and prop_idx != previous_prop_idx:
+    for prop_idx in range(len(triggered_propagators)):
+        if triggered_propagators[prop_idx] and prop_idx != previous_prop_idx:
             triggered_propagators[prop_idx] = False
             return prop_idx
     return -1
@@ -147,5 +147,8 @@ def add_propagators(
     dom_idx: int,
     bound: int,
 ) -> None:
-    np.logical_or(triggered_propagators, shr_domains_propagators[dom_idx, bound], triggered_propagators)
-    np.logical_and(triggered_propagators, not_entailed_propagators, triggered_propagators)
+    for prop_idx in range(len(triggered_propagators)):
+        if shr_domains_propagators[dom_idx, bound, prop_idx] and not_entailed_propagators[prop_idx]:
+            triggered_propagators[prop_idx] = True
+    # np.logical_or(triggered_propagators, shr_domains_propagators[dom_idx, bound], triggered_propagators)
+    # np.logical_and(triggered_propagators, not_entailed_propagators, triggered_propagators)

nucs/solvers/bound_consistency_algorithm.py

@@ -112,7 +112,7 @@ def bound_consistency_algorithm(
         shr_domains_changes = False
         for var_idx in range(prop_var_nb):
             shr_domain_idx = prop_indices[var_idx]
-            prop_offset = prop_offsets[var_idx, 0]
+            prop_offset = prop_offsets[var_idx, 0]  # because of vertical shape
             for bound in [MIN, MAX]:
                 shr_domain_bound = prop_domains[var_idx, bound] - prop_offset
                 if shr_domains_stack[0, shr_domain_idx, bound] != shr_domain_bound: