| Name | pycmsgen JSON |
| Version |
6.1.0
JSON |
| download |
| home_page | https://github.com/meelgroup/cmsgen |
| Summary | Bindings to CMSGen, uniform-like sampler |
| upload_time | 2024-02-07 23:12:51 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.5 |
| license | CryptoMiniSat Copyright (c) Mate Soos 2009-2018 All rights reserved. MIT License =================== Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
sat
sampling
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# pycmsgen uniform-like sampler
This directory provides Python bindings to the CMSGen unform-like sampler,
## Installing
```
pip install pycmsgen
```
## Compiling
If you don't want to use the pip package, you can compile it as:
```
apt-get install python-dev
python -m build
```
## Usage
The `pycmsgen` module has one object, `Solver` that has three main functions
`solve`, `add_clause`, and `get_model`.
The function `add_clause()` takes an iterable list of literals such as
`[1, 2]` which represents the truth `1 or 2 = True`. For example,
`add_clause([1])` sets variable `1` to `True`.
The function `solve()` solves the system of equations that have been added
with `add_clause()`:
```
>>> from pycmsgen import Solver
>>> s = Solver()
>>> s.add_clause([1, 2])
>>> sat = s.solve()
True
>>> print(s.get_model())
[1, 2]
```
The `solve()` method optionally takes an argument `assumptions` that
allows the user to set values to specific variables in the solver in a temporary
fashion. This means that in case the problem is satisfiable but e.g it's
unsatisfiable if variable 2 is FALSE, then `solve([-2])` will return
UNSAT. However, a subsequent call to `solve()` will still return a solution.
If instead of an assumption `add_clause()` would have been used, subsequent
`solve()` calls would have returned unsatisfiable.
`Solver` takes the following keyword arguments:
* `time_limit`: the time limit (integer)
* `confl_limit`: the propagation limit (integer)
* `verbose`: the verbosity level (integer)
Both `time_limit` and `confl_limit` set a budget to the solver. The former is based on time elapsed while the former is based on number of conflicts met during search. If the solver runs out of budget, it returns with `(None, None)`. If both limits are used, the solver will terminate whenever one of the limits are hit (whichever first). Warning: Results from `time_limit` may differ from run to run, depending on compute load, etc. Use `confl_limit` for more reproducible runs.
Raw data
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"description": "# pycmsgen uniform-like sampler\n\nThis directory provides Python bindings to the CMSGen unform-like sampler,\n\n## Installing\n\n```\npip install pycmsgen\n```\n\n## Compiling\nIf you don't want to use the pip package, you can compile it as:\n\n```\napt-get install python-dev\npython -m build\n```\n\n## Usage\n\nThe `pycmsgen` module has one object, `Solver` that has three main functions\n`solve`, `add_clause`, and `get_model`.\n\nThe function `add_clause()` takes an iterable list of literals such as\n`[1, 2]` which represents the truth `1 or 2 = True`. For example,\n`add_clause([1])` sets variable `1` to `True`.\n\nThe function `solve()` solves the system of equations that have been added\nwith `add_clause()`:\n\n```\n>>> from pycmsgen import Solver\n>>> s = Solver()\n>>> s.add_clause([1, 2])\n>>> sat = s.solve()\nTrue\n>>> print(s.get_model())\n[1, 2]\n```\n\nThe `solve()` method optionally takes an argument `assumptions` that\nallows the user to set values to specific variables in the solver in a temporary\nfashion. This means that in case the problem is satisfiable but e.g it's\nunsatisfiable if variable 2 is FALSE, then `solve([-2])` will return\nUNSAT. However, a subsequent call to `solve()` will still return a solution.\nIf instead of an assumption `add_clause()` would have been used, subsequent\n`solve()` calls would have returned unsatisfiable.\n\n`Solver` takes the following keyword arguments:\n * `time_limit`: the time limit (integer)\n * `confl_limit`: the propagation limit (integer)\n * `verbose`: the verbosity level (integer)\n\nBoth `time_limit` and `confl_limit` set a budget to the solver. The former is based on time elapsed while the former is based on number of conflicts met during search. If the solver runs out of budget, it returns with `(None, None)`. If both limits are used, the solver will terminate whenever one of the limits are hit (whichever first). Warning: Results from `time_limit` may differ from run to run, depending on compute load, etc. Use `confl_limit` for more reproducible runs.\n",
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