matmod/parse_magic.py

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"""
Parses the Magic Ugly Data File Format
Assumes the base logic is R with no extra connectives
"""
import sys
from typing import TextIO, List, Optional, Tuple, Set, Dict
from model import Model, ModelValue, ModelFunction
from logic import (
Implication,
Conjunction,
Negation,
Disjunction
)
from vsp import has_vsp
def parse_matrices(infile: TextIO) -> List[Tuple[Model, Dict]]:
next(infile) # Skip header line
solutions: List[Tuple[Model, Dict]] = []
while True:
size = parse_size(infile)
if size is None:
break
carrier_set = carrier_set_from_size(size)
while True:
mnegation = parse_negation(infile, size)
if mnegation is None:
break
while True:
result = parse_order(infile, size)
if result is None:
break
mconjunction, mdisjunction = result
while True:
designated_values = parse_designated(infile, size)
if designated_values is None:
break
results = parse_implication(infile, size)
if result is None:
break
for mimplication in results:
logical_operations = {
mnegation, mimplication
}
model = Model(carrier_set, logical_operations, designated_values, name=str(len(solutions)))
interpretation = {
Negation: mnegation,
Implication: mimplication
}
if mconjunction is not None:
logical_operations.add(mconjunction)
interpretation[Conjunction] = mconjunction
if mdisjunction is not None:
logical_operations.add(mdisjunction)
interpretation[Disjunction] = mdisjunction
solutions.append((model, interpretation))
print(f"Parsed Matrix {model.name}")
return solutions
def carrier_set_from_size(size: int):
"""
Construct a carrier set of model values
based on the desired size.
"""
return {
mvalue_from_index(i) for i in range(size + 1)
}
def parse_size(infile: TextIO) -> Optional[int]:
"""
Parse the line representing the matrix size.
NOTE: Elements are represented in hexidecimal.
"""
size = int(next(infile), 16)
if size == -1:
return None
assert size > 0, "Unexpected size"
return size
def parse_negation(infile: TextIO, size: int) -> Optional[ModelFunction]:
"""
Parse the line representing the negation table.
"""
line = next(infile).strip()
if line == '-1':
return None
row = line.split(" ")
assert len(row) == size + 1, "Negation table doesn't match size"
mapping = {}
for i, j in zip(range(size + 1), row):
x = mvalue_from_index(i)
y = parse_mvalue(j)
mapping[(x, )] = y
return ModelFunction(1, mapping, "¬")
def mvalue_from_index(i: int):
"""
Given an index, return the hexidecimal
representation of the model value.
"""
return ModelValue(f"a{hex(i)[-1]}")
def parse_mvalue(x: str) -> ModelValue:
"""
Parse an element and return the model value.
"""
return mvalue_from_index(int(x, 16))
def determine_cresult(size: int, ordering: Dict[ModelValue, ModelValue], a: ModelValue, b: ModelValue) -> ModelValue:
"""
Determine what a b should be given the ordering table.
"""
for i in range(size + 1):
c = mvalue_from_index(i)
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if not ordering[(c, a)]:
continue
if not ordering[(c, b)]:
continue
invalid = False
for j in range(size + 1):
d = mvalue_from_index(j)
if c == d:
continue
if ordering[(c, d)]:
if ordering[(d, a)] and ordering [(d, b)]:
invalid = True
if not invalid:
return c
def determine_dresult(size: int, ordering: Dict[ModelValue, ModelValue], a: ModelValue, b: ModelValue) -> ModelValue:
"""
Determine what a b should be given the ordering table.
"""
for i in range(size + 1):
c = mvalue_from_index(i)
if not ordering[(a, c)]:
continue
if not ordering[(b, c)]:
continue
invalid = False
for j in range(size + 1):
d = mvalue_from_index(j)
if d == c:
continue
if ordering[(d, c)]:
if ordering[(a, d)] and ordering[(b, d)]:
invalid = True
if not invalid:
return c
def parse_order(infile: TextIO, size: int) -> Optional[Tuple[ModelFunction, ModelFunction]]:
"""
Parse the line representing the ordering table
"""
line = next(infile).strip()
if line == '-1':
return None
table = line.split(" ")
assert len(table) == (size + 1)**2
omapping = {}
table_i = 0
for i in range(size + 1):
x = mvalue_from_index(i)
for j in range(size + 1):
y = mvalue_from_index(j)
omapping[(x, y)] = table[table_i] == '1'
table_i += 1
cmapping = {}
dmapping = {}
for i in range(size + 1):
x = mvalue_from_index(i)
for j in range(size + 1):
y = mvalue_from_index(j)
cresult = determine_cresult(size, omapping, x, y)
if cresult is None:
print("[Warning] Conjunction and Disjunction are not well-defined")
print(f"{x}{y} = ??")
return None, None
cmapping[(x, y)] = cresult
dresult = determine_dresult(size, omapping, x, y)
if dresult is None:
print("[Warning] Conjunction and Disjunction are not well-defined")
print(f"{x} {y} = ??")
return None, None
dmapping[(x, y)] = dresult
mconjunction = ModelFunction(2, cmapping, "")
mdisjunction = ModelFunction(2, dmapping, "")
return mconjunction, mdisjunction
def parse_designated(infile: TextIO, size: int) -> Optional[Set[ModelValue]]:
"""
Parse the line representing which model values are designated.
"""
line = next(infile).strip()
if line == '-1':
return None
row = line.split(" ")
assert len(row) == size + 1, "Designated table doesn't match size"
designated_values = set()
for i, j in zip(range(size + 1), row):
if j == '1':
x = mvalue_from_index(i)
designated_values.add(x)
return designated_values
def parse_implication(infile: TextIO, size: int) -> Optional[List[ModelFunction]]:
"""
Parse the line representing the list of implication
tables.
"""
line = next(infile).strip()
if line == '-1':
return None
# Split and remove the last '-1' character
table = line.split(" ")[:-1]
assert len(table) % (size + 1)**2 == 0
table_i = 0
mimplications: List[ModelFunction] = []
for _ in range(len(table) // (size + 1)**2):
mapping = {}
for i in range(size + 1):
x = mvalue_from_index(i)
for j in range(size + 1):
y = mvalue_from_index(j)
r = parse_mvalue(table[table_i])
table_i += 1
mapping[(x, y)] = r
mimplication = ModelFunction(2, mapping, "")
mimplications.append(mimplication)
return mimplications
if __name__ == "__main__":
solutions: List[Model] = parse_matrices(sys.stdin)
print(f"Parsed {len(solutions)} matrices")
for i, (model, interpretation) in enumerate(solutions):
print(model)
print(has_vsp(model, interpretation))