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.
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 dwavebinarycsp
To build from source:
pip install -r requirements.txt
python setup.py install
License
Released under the Apache License 2.0. See LICENSE file.
Contribution
See CONTRIBUTING.rst file.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
dwavebinarycsp-0.0.12.tar.gz
(20.2 kB
view hashes)
Built Distribution
Close
Hashes for dwavebinarycsp-0.0.12-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7369794983d7b7f7a0652a5f693e582378729b7ecc78364d2202c0e7433585a3 |
|
MD5 | f2626731140a2d49257f4e7f01a2d1fa |
|
BLAKE2b-256 | 54cb3c6ed88ca888abfe62bd5f064b992831c65294904589e6ac357ea78ac492 |