https://github.com/norskregnesentral/streamchange
A package for segmenting streaming time series data into homogenous segments. The segmentation is based on statistical change-point detection (aka online/sequential/iterative change-point detection).
https://github.com/norskregnesentral/streamchange
Last synced: 6 months ago
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A package for segmenting streaming time series data into homogenous segments. The segmentation is based on statistical change-point detection (aka online/sequential/iterative change-point detection).
- Host: GitHub
- URL: https://github.com/norskregnesentral/streamchange
- Owner: NorskRegnesentral
- License: bsd-3-clause
- Created: 2022-11-08T15:37:11.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-12-07T14:00:47.000Z (almost 2 years ago)
- Last Synced: 2025-04-05T20:04:25.008Z (6 months ago)
- Language: Python
- Size: 402 KB
- Stars: 7
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# streamchange
A package for segmenting streaming time series data into homogenous segments. The segmentation is based on statistical change-point detection (aka online/sequential/iterative change-point detection). Inspired by [river](https://riverml.xyz/0.14.0/) and follows its API.
# OBS
The functionality in this package is about to be moved into `skchange`: https://github.com/NorskRegnesentral/skchange.
## Quickstart
```python
>>> from river.stream import iter_pandas
>>>
>>> from streamchange.amoc import UnivariateCUSUM, WindowSegmentor
>>> from streamchange.data import simulate
>>>
>>> df = simulate([0, 10, 0], [100], p=1)
>>> test = UnivariateCUSUM(minsl=1).set_default_threshold(10 * df.size)
>>> detector = WindowSegmentor(test, min_window=4, max_window=100)
>>> cpts = []
>>> for t, (x, _) in enumerate(iter_pandas(df)):
... detector.update(x)
... if detector.change_detected:
... cpts.append((t, detector.changepoints))
print(cpts)
[(100, [1]), (200, [1])]
```
Throughout this package, a change-point is defined as the end of a segment,
and it is stored relative to the time of detection by its index backwards in time.
For example, if t is the index of the current observation, the changepoint in the
external data set is given by t - changepoint.
In the example above, 100 and 200 are the times of detection, and the changepoints
are located at indices 99 and 199.
## Installation
```sh
pip install git+https://github.com/NorskRegnesentral/streamchange
```
## Dependencies
- `pandas` >= 1.3
- `numpy` >= 1.19
- `numba` >= 0.56
You also need Python >= 3.8.
Optional dependencies:
- Online estimation of segment parameters: `river` >= 0.14
- Penalty tuning: `optuna` >= 3.1.1
## License
Streamchange is a free and open-source software licensed under the [BSD 3-clause license](https://github.com/NorskRegnesentral/streamchange/blob/main/LICENSE).