https://github.com/openedi/pnnl-dsse-ekf
Distribution system state estimation (DSSE) using the Extended Kalman Filter (EKF) algorithm
https://github.com/openedi/pnnl-dsse-ekf
Last synced: 4 months ago
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Distribution system state estimation (DSSE) using the Extended Kalman Filter (EKF) algorithm
- Host: GitHub
- URL: https://github.com/openedi/pnnl-dsse-ekf
- Owner: openEDI
- License: mit
- Created: 2026-02-19T21:38:40.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2026-03-18T20:49:28.000Z (5 months ago)
- Last Synced: 2026-03-19T09:49:30.768Z (5 months ago)
- Language: Python
- Homepage:
- Size: 7.81 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ekf
Component context:
> ekf
This component is scaffolded following the OEDISI best practice guide.
## Layout
- `component/` — main Python package (`ekf`) with an entry point.
- `tests/unit/` — unit tests for core logic.
- `tests/integration/` — integration/system tests.
- `examples/` — example configs, `component_definition.json`, sample data.
- `Dockerfile` / `docker-compose.yml` — for replicable integration test runs.
## Quick Start
Create and activate a virtual environment, then run:
```bash
pip install -e .
pytest tests/unit
```
To run integration tests (once implemented):
```bash
docker-compose -f docker-compose.yml up --build
```
## Updating Docs
- Keep this `README.md` up to date with usage and configuration examples.
- Keep `best_practice_guide.md` in sync with lessons learned.
- Maintain `component_definition.json` to reflect inputs/outputs and configuration.