gripa 0.1.3

Time series anomaly detection

Welcome to Gripa

Introduction

Gripa is a python package for time series anomaly detection. The name of Gripa is taken from Scandinavian languages, which means grab or catch or seize, and not meant as Flu in Spanish :smile:.

Why Gripa?

• Gripa is light-weight. Try Gripa before you build LSTM or Transformer for your time series anomaly detection.
• Gripa is accurate. Gripa has two available algorithms that perform very well in detecting anomalies on your time series data.
• Gripa is comprehensive. Gripa can detect three types of anomaly: global anomaly, contextual anomaly, and level-shift.

Quick Start

Installation

Python 3.9 or higher is required.

python -m pip install gripa

Usage

# Load data
from gripa import Gripa

detector = Gripa()
anomalies = detector.fit_predict(data)

API Reference

There is only one module, gripa.Gripa, that can be used for detecting anomalies in time series.

class gripa.Gripa(window_size=11, algorithm="hpf", threshold=3)

Parameters

• window_size: int or float, default=11
• algorithm: {"hpf", "ssa"}, default="hpf"
• threshold: float, default=3

Attributes

• anomaly_score: score for labelling anomaly

Methods

• fit(X): train the Gripa model, which can generate attribute anomaly_score
• fit_predict(X): train and generate anomaly labels (True or False)

Contact

Hamid Dimyati - [e-mail]