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Quickstart

git clone https://github.com/Yuma-Ichikawa/QQA4CO.git
cd QQA4CO
uv sync --extra plotly --extra gui --extra dev

The first sync takes a couple of minutes (PyTorch wheel). Subsequent runs reuse the resolved lockfile.

With pip

pip install qqa                          # core (CPU torch + numpy/networkx)
pip install "qqa[plotly]"                # + interactive Plotly figures
pip install "qqa[gui]"                   # + Streamlit dashboard
pip install "qqa[all]"                   # everything (docs, dev, notebook, gui, plotly)

Quote the extras list — bare brackets are a glob pattern in zsh and Bash with noglob disabled.

Solve a first problem

import networkx as nx
import qqa

qqa.fix_seed(0)
g = nx.random_regular_graph(d=3, n=100, seed=0)
problem = qqa.MaximumIndependentSet(g, penalty=2)
result = qqa.anneal(problem, sol_size=100, num_epochs=1500)
print(f"MIS size: {-int(result.best_obj)}  in {result.runtime:.2f}s")

The same qqa.anneal(...) call works for every problem in the catalog.

Run the CLI

qqa version
qqa solve --problem sk --size 100 --sol-size 128 --epochs 1000
qqa bench --preset er-small --epochs 500

Launch the GUI

qqa gui              # opens http://localhost:8501

Browse example notebooks

  • examples/01_maximum_independent_set.ipynb
  • examples/04_edwards_anderson_3d.ipynb
  • examples/06_binary_perceptron.ipynb
  • …
  • notebooks/cra_pignn_example.ipynb — CRA-PI-GNN walkthrough across every supported graph problem
  • notebooks/cpra_pignn_example.ipynb — CPRA penalty / variation diversification

Run any of them with uv run jupyter lab.

Where to go next