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Don't rely on shared memory for logic operators

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Brandon Rozek 2024-12-10 17:17:14 -08:00
parent 29526dbec3
commit b06dd8ee01
2 changed files with 13 additions and 8 deletions
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5
vsp.py
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@ -98,14 +98,11 @@ Subalgebra 1: {set_to_str(self.subalgebra1)}
Subalgebra 2: {set_to_str(self.subalgebra2)} Subalgebra 2: {set_to_str(self.subalgebra2)}
""" """
def has_vsp(model: Model, interpretation: Dict[Operation, ModelFunction]) -> VSP_Result: def has_vsp(model: Model, impfunction: ModelFunction, mconjunction: Optional[ModelFunction] = None, mdisjunction: Optional[ModelFunction] = None) -> VSP_Result:
""" """
Checks whether a model has the variable Checks whether a model has the variable
sharing property. sharing property.
""" """
impfunction = interpretation[Implication]
mconjunction = interpretation.get(Conjunction)
mdisjunction = interpretation.get(Disjunction)
top = find_top(model.carrier_set, mconjunction, mdisjunction) top = find_top(model.carrier_set, mconjunction, mdisjunction)
bottom = find_bottom(model.carrier_set, mconjunction, mdisjunction) bottom = find_bottom(model.carrier_set, mconjunction, mdisjunction)

16
vspursuer.py
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@ -1,7 +1,8 @@
#!/usr/bin/env python3 #!/usr/bin/env python3
from os import cpu_count from os import cpu_count
import argparse import argparse
import multiprocessing import multiprocessing as mp
from logic import Implication, Conjunction, Disjunction
from parse_magic import ( from parse_magic import (
SourceFile, SourceFile,
@ -24,11 +25,18 @@ if __name__ == "__main__":
solutions = parse_matrices(SourceFile(data_file)) solutions = parse_matrices(SourceFile(data_file))
print(f"Parsed {len(solutions)} matrices") print(f"Parsed {len(solutions)} matrices")
solutions_prep = []
for model, interpretation in solutions:
impfunction = interpretation[Implication]
mconjunction = interpretation.get(Conjunction)
mdisjunction = interpretation.get(Disjunction)
solutions_prep.append((model, impfunction, mconjunction, mdisjunction))
num_has_vsp = 0 num_has_vsp = 0
with multiprocessing.Pool(processes=max(cpu_count() - 2, 1)) as pool: with mp.Pool(processes=max(cpu_count() - 2, 1)) as pool:
results = [ results = [
pool.apply_async(has_vsp, (model, interpretation,)) pool.apply_async(has_vsp, (model, impfunction, mconjunction, mdisjunction,))
for model, interpretation in solutions for model, impfunction, mconjunction, mdisjunction in solutions_prep
] ]
for i, result in enumerate(results): for i, result in enumerate(results):