Files
cvc5/examples/api/python/floating_point.py
2022-04-05 20:38:57 +00:00

118 lines
4.0 KiB
Python

#!/usr/bin/env python
###############################################################################
# Top contributors (to current version):
# Aina Niemetz, Makai Mann, Mathias Preiner
#
# This file is part of the cvc5 project.
#
# Copyright (c) 2009-2022 by the authors listed in the file AUTHORS
# in the top-level source directory and their institutional affiliations.
# All rights reserved. See the file COPYING in the top-level source
# directory for licensing information.
# #############################################################################
#
# A simple demonstration of the solving capabilities of the cvc5
# floating point solver through the Python API contributed by Eva
# Darulova. This requires building cvc5 with symfpu.
##
import cvc5
from cvc5 import Kind, RoundingMode
if __name__ == "__main__":
slv = cvc5.Solver()
slv.setOption("produce-models", "true")
slv.setLogic("QF_FP")
# single 32-bit precision
fp32 = slv.mkFloatingPointSort(8, 24)
# the standard rounding mode
rm = slv.mkRoundingMode(RoundingMode.ROUND_NEAREST_TIES_TO_EVEN)
# create a few single-precision variables
x = slv.mkConst(fp32, 'x')
y = slv.mkConst(fp32, 'y')
z = slv.mkConst(fp32, 'z')
# check floating-point arithmetic is commutative, i.e. x + y == y + x
commutative = slv.mkTerm(
Kind.FLOATINGPOINT_EQ,
slv.mkTerm(Kind.FLOATINGPOINT_ADD, rm, x, y),
slv.mkTerm(Kind.FLOATINGPOINT_ADD, rm, y, x))
slv.push()
slv.assertFormula(slv.mkTerm(Kind.NOT, commutative))
print("Checking floating-point commutativity")
print("Expect SAT (property does not hold for NaN and Infinities).")
print("cvc5:", slv.checkSat())
print("Model for x:", slv.getValue(x))
print("Model for y:", slv.getValue(y))
# disallow NaNs and Infinities
slv.assertFormula(slv.mkTerm(
Kind.NOT, slv.mkTerm(Kind.FLOATINGPOINT_IS_NAN, x)))
slv.assertFormula(slv.mkTerm(
Kind.NOT, slv.mkTerm(Kind.FLOATINGPOINT_IS_INF, x)))
slv.assertFormula(slv.mkTerm(
Kind.NOT, slv.mkTerm(Kind.FLOATINGPOINT_IS_NAN, y)))
slv.assertFormula(slv.mkTerm(
Kind.NOT, slv.mkTerm(Kind.FLOATINGPOINT_IS_INF, y)))
print("Checking floating-point commutativity assuming x and y are not NaN or Infinity")
print("Expect UNSAT.")
print("cvc5:", slv.checkSat())
# check floating-point arithmetic is not associative
slv.pop()
# constrain x, y, z between -3.14 and 3.14 (also disallows NaN and infinity)
a = slv.mkFloatingPoint(
8,
24,
slv.mkBitVector(32, "11000000010010001111010111000011", 2)) # -3.14
b = slv.mkFloatingPoint(
8,
24,
slv.mkBitVector(32, "01000000010010001111010111000011", 2)) # 3.14
bounds_x = slv.mkTerm(
Kind.AND,
slv.mkTerm(Kind.FLOATINGPOINT_LEQ, a, x),
slv.mkTerm(Kind.FLOATINGPOINT_LEQ, x, b))
bounds_y = slv.mkTerm(
Kind.AND,
slv.mkTerm(Kind.FLOATINGPOINT_LEQ, a, y),
slv.mkTerm(Kind.FLOATINGPOINT_LEQ, y, b))
bounds_z = slv.mkTerm(
Kind.AND,
slv.mkTerm(Kind.FLOATINGPOINT_LEQ, a, z),
slv.mkTerm(Kind.FLOATINGPOINT_LEQ, z, b))
slv.assertFormula(slv.mkTerm(
Kind.AND, slv.mkTerm(Kind.AND, bounds_x, bounds_y), bounds_z))
# (x + y) + z == x + (y + z)
lhs = slv.mkTerm(
Kind.FLOATINGPOINT_ADD,
rm,
slv.mkTerm(Kind.FLOATINGPOINT_ADD, rm, x, y),
z)
rhs = slv.mkTerm(
Kind.FLOATINGPOINT_ADD,
rm,
x,
slv.mkTerm(Kind.FLOATINGPOINT_ADD, rm, y, z))
associative = slv.mkTerm(
Kind.NOT,
slv.mkTerm(Kind.FLOATINGPOINT_EQ, lhs, rhs))
slv.assertFormula(associative)
print("Checking floating-point associativity")
print("Expect SAT.")
print("cvc5:", slv.checkSat())
print("Model for x:", slv.getValue(x))
print("Model for y:", slv.getValue(y))
print("Model for z:", slv.getValue(z))