doin-plugins

Domain plugins for DOIN (Decentralized Optimization and Inference Network).

Included Plugins

Quadratic (Reference)

Simple quadratic function optimization — no ML frameworks needed. Used for testing the full DOIN pipeline.

• Optimizer: Hill-climbing on f(x) = Σ(x_i - target_i)²
• Inferencer: Evaluates parameters against target
• Synthetic Data: Generates noisy target variants for verification

Predictor (ML)

Wraps harveybc/predictor timeseries prediction system. Requires TensorFlow.

• Optimizer: Runs predictor training with genetic algorithm
• Inferencer: Evaluates model on test/synthetic data
• Synthetic Data: Wraps harveybc/timeseries-gan (SC-VAE-GAN) with block bootstrap fallback

Entry Points

doin.optimization/quadratic → QuadraticOptimizer
doin.optimization/predictor → PredictorOptimizer
doin.inference/quadratic → QuadraticInferencer
doin.inference/predictor → PredictorInferencer
doin.synthetic_data/quadratic → QuadraticSyntheticData
doin.synthetic_data/predictor → PredictorSyntheticData

Install

pip install git+https://github.com/harveybc/doin-core.git
pip install git+https://github.com/harveybc/doin-plugins.git

Tests

python -m pytest tests/ -v
# 43 tests (7 e2e lifecycle + unit + integration)

Key Tests

• test_e2e_lifecycle.py — Full optimae lifecycle: optimize → commit → reveal → quorum → verify → incentive → reputation (7 tests)
• test_plugins.py — Quadratic plugin unit tests
• test_network_integration.py — Multi-component integration

Part of DOIN

• doin-core — Consensus, models, crypto
• doin-node — Unified node
• doin-plugins — This package