Repository Map
This page gives a quick path through the repository for contributors and power users.
Top-level areas
| Path | Purpose |
|---|---|
README.md | GitHub landing page |
docs/.vitepress/config.js | Navigation and site structure for the /docs/ site |
web/ | Static landing page assets for the published site root |
docs/ | VitePress source for the versioned documentation site |
examples/ | Notebooks and runnable examples |
foreblocks/ | Main forecasting library |
foretools/ | Companion tooling |
foreblocks/
| Path | Purpose |
|---|---|
foreblocks/__init__.py | Top-level public exports |
foreblocks/config.py | Public configuration dataclasses (ModelConfig, TrainingConfig) |
foreblocks/models/ | Model-level composition APIs (ForecastingModel, GraphForecastingModel) |
foreblocks/layers/ | Reusable layer families, including graph convolutions and graph construction |
foreblocks/core/ | Core forecasting internals and heads |
foreblocks/training/ | Trainer and training support |
foreblocks/evaluation/ | Evaluation and metrics |
foreblocks/data/ | Dataset and dataloader helpers |
foreblocks/ts_handler/ | Preprocessing and sequence construction |
foreblocks/tf/ | Transformer stack and advanced attention |
foreblocks/darts/ | Neural architecture search |
foreblocks/mltracker/ | Experiment tracking |
foreblocks/hybrid_mamba/ | Hybrid Mamba SSM blocks (HybridMambaBlock, HybridMamba2Block, SSD) |
foreblocks/mamba/ | Original Mamba backbone with MoE, positional encoding, and eval tools |
foreblocks/kan/ | Kolmogorov-Arnold Network backbone |
foretools/
| Path | Purpose |
|---|---|
foretools/tsgen/ | Synthetic time-series generation |
foretools/bohb/ | BOHB, TPE configuration, pruning, and optimization plots |
foretools/foreminer/ | Exploratory analysis and diagnostics |
foretools/fengineer/ | Feature engineering utilities |
foretools/emd_like/ | Decomposition tools |
foretools/tsaug/ | AutoDA-Timeseries: automated data augmentation with adaptive policy |
Recommended entry points by task
| Task | Entry point |
|---|---|
| Training a baseline model | README.md, Getting Started |
| Understanding architecture composition | foreblocks/models/ |
| Working with graph forecasting | foreblocks/models/graph_forecasting.py, foreblocks/layers/graph/ |
| Configuring runs | foreblocks/config.py |
| Building dataloaders | foreblocks/data/dataset.py |
| Adding preprocessing logic | foreblocks/ts_handler/preprocessing.py |
| Exploring transformer internals | foreblocks/tf/transformer.py |
| Working on architecture search | foreblocks/darts/ |
| Using SSM / Mamba-style blocks | foreblocks/hybrid_mamba/layers.py |
| Generating synthetic data | foretools/tsgen/ |
| Running hyperparameter search | foretools/bohb/ |
| Augmenting training data adaptively | foretools/tsaug/ |