pyapproxmc: Python bindings to ApproxMC
Python bindings to ApproxMC, an approximate model counter with PAC (Probably Approximately Correct) guarantees. ApproxMC counts the number of satisfying assignments of CNF formulas.
Installing
pip install pyapproxmc
Building from source
# Install build tools
pip install scikit-build-core build
# Clone the repository
git clone --recurse-submodules https://github.com/meelgroup/approxmc
cd approxmc
# Build and install into a virtual environment
python -m venv .venv && source .venv/bin/activate
pip install .
The build system uses scikit-build-core and CMake. All C++ dependencies
(CryptoMiniSat, Arjun, and their sub-dependencies) are fetched and built
automatically by CMake during the pip install step. The only system library
required is GMP:
- Linux:
sudo apt-get install libgmp-dev(ordnf install gmp-devel) - macOS:
brew install gmp
Usage
import pyapproxmc
c = pyapproxmc.Counter()
c.add_clause([1, 2, 3])
c.add_clause([3, 20])
count = c.count()
print("Approximate count is: %d*2**%d" % (count[0], count[1]))
count() may only be called once per Counter instance; create a new
Counter if you need to count a different formula.
The above prints Approximate count is: 11*2**16. Since the largest variable
in the clauses is 20, the formula has at most 2**20 models; the two clauses
restrict this to approximately 11*2**16 ≈ 720896 models.
Counting over a projection set
Pass a projection set (sampling set) to count() to count models projected
onto a subset of variables:
import pyapproxmc
c = pyapproxmc.Counter()
c.add_clause([1, 2, 3])
c.add_clause([3, 20])
count = c.count(range(1, 10))
print("Approximate count is: %d*2**%d" % (count[0], count[1]))
This prints Approximate count is: 7*2**6, the approximate count projected
over variables 1–9.
Adding clauses from arrays
For performance-critical code, multiple clauses can be added in one call via
add_clauses() with a flat, zero-terminated array.array. This uses the
buffer protocol and avoids per-element Python overhead:
import pyapproxmc
from array import array
c = pyapproxmc.Counter()
# Clauses [1,2,3] and [3,20], each terminated by 0
c.add_clauses(array('i', [1, 2, 3, 0, 3, 20, 0]))
count = c.count()
Note: add_clause() (singular) also accepts any iterable including arrays,
but iterates element by element and does not use the buffer protocol.
Counter constructor parameters
| Parameter | Default | Description |
|---|---|---|
seed |
1 | Random seed for reproducibility |
verbosity |
0 | Output verbosity (0 = silent) |
epsilon |
0.8 | Tolerance: how approximate the count is |
delta |
0.2 | Confidence: probability the count is within tolerance |
Example:
c = pyapproxmc.Counter(seed=42, epsilon=0.5, delta=0.1)
Version
import pyapproxmc
print(pyapproxmc.__version__)
1 maintainer
Metadata
1 maintainer
Release files for pyapproxmc 4.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 54.9 MB
Release files / pyapproxmc-4.4.0-cp313-cp313-manylinux_2_34_x86_64.whl
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