Implementing optimization #14

Discard subalgebras which are order-dependent

vsp.py

@@ -6,7 +6,7 @@ from itertools import chain, combinations, product
 from typing import Dict, List, Optional, Set, Tuple
 from common import set_to_str
 from model import (
-    Model, model_closure, ModelFunction, ModelValue
+    Model, model_closure, ModelFunction, ModelValue, OrderTable
 )
 from logic import Conjunction, Disjunction, Implication, Operation
 
@@ -79,6 +79,15 @@ def find_bottom(algebra: Set[ModelValue], mconjunction: Optional[ModelFunction],
     print("[Warning] Failed to find the bottom of the lattice")
     return None
 
+def order_dependent(subalgebra1: Set[ModelValue], subalegbra2: Set[ModelValue], ordering: OrderTable):
+    """
+    Returns true if there exists a value in subalgebra1 that's less than a value in subalgebra2
+    """
+    for x in subalgebra1:
+        for y in subalegbra2:
+            if ordering.is_lt(x, y):
+                return True
+    return False
 
 class VSP_Result:
     def __init__(
@@ -111,6 +120,8 @@ def has_vsp(model: Model, impfunction: ModelFunction, mconjunction: Optional[Mod
     if len(model.designated_values) == 1:
         return VSP_Result(False, model.name)
 
+    assert model.ordering is not None, "Expected ordering table in model"
+
     # Compute I the set of tuples (x, y) where
     # x -> y does not take a designiated value
     I: Set[Tuple[ModelValue, ModelValue]] = set()
@@ -158,6 +169,11 @@ def has_vsp(model: Model, impfunction: ModelFunction, mconjunction: Optional[Mod
         if bottom is not None and bottom in xs:
             continue
 
+        # NOTE: Optimization
+        # If the subalgebras are order-dependent, skip this pair
+        if order_dependent(xs, ys, model.ordering):
+            continue
+
         # Compute the closure of all operations
         # with just the xs
         carrier_set_left: Set[ModelValue] = model_closure(xs, model.logical_operations, bottom)