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Break out of saturation computation early when top/bottom are found
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parent
bed3d09f4a
commit
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2 changed files with 46 additions and 3 deletions
36
model.py
36
model.py
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@ -219,15 +219,18 @@ def satisfiable(logic: Logic, model: Model, interpretation: Dict[Operation, Mode
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def model_closure(initial_set: Set[ModelValue], mfunctions: Set[ModelFunction]):
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def model_closure(initial_set: Set[ModelValue], mfunctions: Set[ModelFunction], top: Optional[ModelValue], bottom: Optional[ModelValue]) -> Set[ModelValue]:
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"""
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Given an initial set of model values and a set of model functions,
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compute the complete set of model values that are closed
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under the operations.
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If top or bottom is encountered, then we end the saturation procedure early.
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"""
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closure_set: Set[ModelValue] = initial_set
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last_new: Set[ModelValue] = initial_set
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changed: bool = True
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topbottom_found = False
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while changed:
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changed = False
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@ -251,6 +254,18 @@ def model_closure(initial_set: Set[ModelValue], mfunctions: Set[ModelFunction]):
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if element not in closure_set:
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new_elements.add(element)
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# Optimization: Break out of computation
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# early when top or bottom element is foun
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if top is not None and element == top:
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topbottom_found = True
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if bottom is not None and element == bottom:
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topbottom_found = True
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if topbottom_found:
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break
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if topbottom_found:
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break
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# We don't need to compute the arguments
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# thanks to the cache, so move onto the
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# next function.
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@ -274,8 +289,27 @@ def model_closure(initial_set: Set[ModelValue], mfunctions: Set[ModelFunction]):
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if element not in closure_set:
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new_elements.add(element)
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# Optimization: Break out of computation
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# early when top or bottom element is foun
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if top is not None and element == top:
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topbottom_found = True
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if bottom is not None and element == bottom:
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topbottom_found = True
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if topbottom_found:
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break
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if topbottom_found:
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break
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if topbottom_found:
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break
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closure_set.update(new_elements)
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changed = len(new_elements) > 0
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last_new = new_elements
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if topbottom_found:
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break
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return closure_set
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13
vsp.py
13
vsp.py
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@ -149,21 +149,30 @@ def has_vsp(model: Model, interpretation: Dict[Operation, ModelFunction]) -> VSP
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# Compute the closure of all operations
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# with just the xs
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carrier_set_left: Set[ModelValue] = model_closure(xs, model.logical_operations)
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carrier_set_left: Set[ModelValue] = model_closure(xs, model.logical_operations, top, bottom)
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# Save to cache
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if cached_xs[0] is not None and not cached_ys[1]:
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closure_cache.append((orig_xs, carrier_set_left))
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if top is not None and top in carrier_set_left:
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continue
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if bottom is not None and bottom in carrier_set_left:
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continue
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# Compute the closure of all operations
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# with just the ys
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carrier_set_right: Set[ModelValue] = model_closure(ys, model.logical_operations)
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carrier_set_right: Set[ModelValue] = model_closure(ys, model.logical_operations, top, bottom)
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# Save to cache
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if cached_ys[0] is not None and not cached_ys[1]:
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closure_cache.append((orig_ys, carrier_set_right))
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if top is not None and top in carrier_set_right:
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continue
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if bottom is not None and bottom in carrier_set_right:
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continue
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# If the carrier set intersects, then move on to the next
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# subalgebra
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