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Solves constraints satisfaction problems with binary quadratic model samplers

Project description

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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


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This version
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0.0.2

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0.0.1

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Filename, size & hash SHA256 hash help File type Python version Upload date
dwavebinarycsp-0.0.2-py2.py3-none-any.whl (26.2 kB) Copy SHA256 hash SHA256 Wheel py2.py3 May 9, 2018
dwavebinarycsp-0.0.2.tar.gz (15.0 kB) Copy SHA256 hash SHA256 Source None May 9, 2018

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