Bindings to Ganak, a high-performance exact model counter
Project description
pyganak — Python bindings for Ganak
pyganak provides Python bindings for Ganak,
a high-performance exact model counter for CNF formulas. It exposes two
classes:
Counter— unweighted (and projected) model counting. Returns an arbitrary-precision Pythonint.WeightedCounter— weighted model counting with per-literal float weights. Uses MPFR internally; returns a Pythonfloat.
Arjun preprocessing is applied automatically before each count, just as the command-line tool does.
Installation
pip install pyganak
Pre-built wheels are available for Linux (x86-64, ARM64) and macOS (Apple Silicon, Intel).
Quick start
Unweighted counting
from pyganak import Counter
c = Counter()
c.add_clause([1, 2]) # x1 OR x2
c.add_clause([-1, 2]) # NOT x1 OR x2
print(c.count()) # → 2 (exact Python int)
Weighted counting
from pyganak import WeightedCounter
c = WeightedCounter()
c.add_clause([1, 2]) # x1 OR x2
# Set weights for both polarities of each variable.
c.set_lit_weight( 1, 0.3) # P(x1 = True) = 0.3
c.set_lit_weight(-1, 0.7) # P(x1 = False) = 0.7
c.set_lit_weight( 2, 0.4) # P(x2 = True) = 0.4
c.set_lit_weight(-2, 0.6) # P(x2 = False) = 0.6
# Models: (T,T)=0.12 (T,F)=0.18 (F,T)=0.28 → total=0.58
print(c.count()) # → 0.58 (Python float)
Counter API
Counter(verbose=0, seed=0)
| Parameter | Type | Default | Description |
|---|---|---|---|
verbose |
int |
0 |
Verbosity level (0 = silent) |
seed |
int |
0 |
Random seed for the solver |
add_clause(clause)
Add a single clause — iterable of nonzero signed integers (1-indexed variables; positive = positive literal, negative = negated literal).
c.add_clause([1, -2, 3]) # x1 OR NOT x2 OR x3
add_clauses(clauses)
Add multiple clauses at once.
c.add_clauses([[1, 2], [-1, 3]])
set_sampling_set(vars)
Set the projection set (independent support). Only the given variables are counted; all others are existentially quantified out. If never called, all variables are included.
c.add_clause([1, 2, 3])
c.set_sampling_set([1, 2])
print(c.count()) # → 4
count() → int
Run Arjun preprocessing + Ganak and return the exact model count as a Python
int. May only be called once per instance.
new_vars(n) / nof_vars() → int / nof_clauses() → int
Declare extra variables, or query the current variable / clause count.
WeightedCounter API
WeightedCounter(verbose=0, seed=0, prec=128)
| Parameter | Type | Default | Description |
|---|---|---|---|
verbose |
int |
0 |
Verbosity level |
seed |
int |
0 |
Random seed |
prec |
int |
128 |
MPFR precision in bits (≥ 2) |
The internal arithmetic is performed with MPFR at prec bits of precision
(default 128 ≈ 38 significant decimal digits). The final result is returned
as a Python float (double).
Floating-point caveat: Because floating-point arithmetic is not associative, the result is a high-precision approximation rather than an exact value — the order in which partial sums are accumulated can affect the last few bits. For exact rational weighted counting, use the command-line tool with
--mode 1(GMPmpqrationals).
set_lit_weight(lit, weight)
Set the weight of a literal.
lit— nonzero signed integer (1-indexed; positive = positive literal).weight— Pythonfloat(double). Stored internally as an MPFR value at the precision given to the constructor.
Always set weights for both a literal and its negation to get
well-defined weighted counting. Literals whose weights are not set default
to weight 1.0.
c.set_lit_weight( 1, 0.3) # weight of x1 = 0.3
c.set_lit_weight(-1, 0.7) # weight of ¬x1 = 0.7
add_clause(clause) / add_clauses(clauses) / set_sampling_set(vars) / new_vars(n) / nof_vars() / nof_clauses()
Identical to the Counter versions.
count() → float
Run Arjun preprocessing + Ganak weighted model counting. Returns the
weighted count as a Python float. The internal computation uses MPFR at
the configured precision. May only be called once per instance.
Examples
Plain model counting
from pyganak import Counter
# (x1 XOR x2): 2 models
c = Counter()
c.add_clause([1, 2])
c.add_clause([-1, -2])
print(c.count()) # 2
Projected model counting
from pyganak import Counter
# (x1 OR x2 OR x3) projected onto {x1, x2}: 4 models
c = Counter()
c.add_clause([1, 2, 3])
c.set_sampling_set([1, 2])
print(c.count()) # 4
Large count (arbitrary precision)
from pyganak import Counter
# 30 unconstrained variables → 2^30 models
c = Counter()
c.new_vars(30)
print(c.count()) # 1073741824
Weighted counting
from pyganak import WeightedCounter
# (x1 OR x2) with independent Bernoulli weights
c = WeightedCounter()
c.add_clause([1, 2])
c.set_lit_weight( 1, 0.3); c.set_lit_weight(-1, 0.7)
c.set_lit_weight( 2, 0.4); c.set_lit_weight(-2, 0.6)
print(c.count()) # 0.58
Weighted counting with higher MPFR precision
from pyganak import WeightedCounter
# Use 256-bit MPFR precision for the internal computation.
c = WeightedCounter(prec=256)
c.add_clause([1, 2, 3])
c.set_lit_weight( 1, 0.1); c.set_lit_weight(-1, 0.9)
c.set_lit_weight( 2, 0.2); c.set_lit_weight(-2, 0.8)
c.set_lit_weight( 3, 0.5); c.set_lit_weight(-3, 0.5)
print(c.count())
Building from source (venv)
If you have already built Ganak with CMake (see the top-level README.md
for instructions), the extension is in build/lib/pyganak*.so. Test it
without a full pip install using a venv:
python3 -m venv venv
venv/bin/pip install pytest
PYTHONPATH=build/lib venv/bin/pytest python/tests/ -v
To rebuild the extension after editing python/src/pyganak.cpp:
# If the build directory already exists:
cmake -DBUILD_PYTHON_EXTENSION=ON build # or cmake .. from inside build/
cmake --build build --target pyganak -j$(nproc)
# Then re-run tests as above.
To do a full pip install (builds everything from scratch):
pip install .
Requires: GMP ≥ 5, MPFR ≥ 3, FLINT ≥ 2. On Ubuntu/Debian:
sudo apt install libgmp-dev libmpfr-dev libflint-dev
On macOS:
brew install gmp mpfr flint
License
MIT — see LICENSE.txt in the repository root.
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