Metadata-Version: 2.4
Name: adaptivepy-sampling
Version: 0.1.1
Summary: Adaptive sampling on MD trajectories via clustering and policy-driven seed selection
Author: AdaptivePy Contributors
License: MIT
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: numpy>=1.20
Requires-Dist: scikit-learn>=1.0
Requires-Dist: pyyaml>=6.0
Requires-Dist: click>=8.0
Requires-Dist: joblib>=1.0
Requires-Dist: mdtraj>=1.9
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"

# AdaptivePy

Adaptive sampling on molecular dynamics trajectories using clustering-based state space partitioning and policy-driven seed selection.

## Installation

```bash
pip install adaptivepy-sampling
```

## Quick start

1. Prepare feature files (`features/traj_0.npy`, ...) with shape `(n_frames, n_features)`.
2. Optionally add matching coordinate trajectories (`trajectories/traj_0.xtc`, ...) and a topology file.
3. Edit `examples/config.yaml` and run:

```bash
adaptivepy run examples/config.yaml
```

## CLI

```bash
adaptivepy run config.yaml
adaptivepy validate config.yaml
adaptivepy list-policies
```

## Python API

```python
from adaptivepy import run_adaptive_sampling

results = run_adaptive_sampling("config.yaml")
```
