dwavebinarycsp
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Map constraint satisfaction problems with binary variables to binary quadratic models.
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dwavebinarycsp
.. index-start-marker
Library to construct a binary quadratic model from a constraint satisfaction problem with small constraints over binary variables.
Below is an example usage:
.. code-block:: python
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)
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Installation
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To install:
.. code-block:: bash
pip install dwavebinarycsp
To build from source:
.. code-block:: bash
pip install -r requirements.txt
python setup.py install
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License
Released under the Apache License 2.0. See LICENSE file.
Contributing
Ocean's contributing guide <https://docs.ocean.dwavesys.com/en/stable/contributing.html>
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has guidelines for contributing to Ocean packages.