Solves constraints satisfaction problems with binary quadratic model samplers
Project description
dwavebinarycsp
Library to construct a binary quadratic model from a constraint satisfaction problem with small constraints over binary variables.
Below is an example usage:
import dwavebinarycsp
import dimod
csp = dwavebinarycsp.factories.random_2in4sat(8, 4) # 8 variables, 4 clauses
bqm = dwavebinarycsp.stitch(csp)
resp = dimod.ExactSolver().sample(bqm)
for sample, energy in resp.data(['sample', 'energy']):
print(sample, csp.check(sample), energy)Installation
To install:
pip install dwavebinarycspTo build from source:
pip install -r requirements.txt
python setup.py installLicense
Released under the Apache License 2.0. See LICENSE file.
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