StreamAD

Anomaly detection for data streams/time series. Detectors process the univariate or multivariate data one by one to simulte a real-time scene.

Documentation

Installation

The stable version can be installed from PyPI:

pip install streamad

The development version can be installed from GitHub:

pip install git+https://github.com/Fengrui-Liu/StreamAD

Quick Start

Start once detection within 5 lines of code. You can find more example with visualization results here.

from streamad.util import StreamGenerator, UnivariateDS
from streamad.model import SpotDetector

ds = UnivariateDS()
stream = StreamGenerator(ds.data)
model = SpotDetector()

for x in stream.iter_item():
    score = model.fit_score(x)

Models

For univariate time series

If you want to detect multivarite time series with these models, you need to apply them on each feature separately.

For multivariate time series

These models are compatible with univariate time series.