FLARECAST API

Visualisation

Under the hood FLARECAST uses more than 20 machine learning algorithms each being executed with multiple configurations to compute predictions of flares of different GOES class (X, M, C) in different forecast windows.
The following tool shows predictions from a selected algorithm for all active regions at a given point in time.


Algorithm
Classification
Forecast base time h
h

Latency h
Window size h
Magnetic properties
Flare history

? predicts a ? probability for a ? flare (in active region ?) between ? and ?.


API access for expert users

Prediction Access

FLARECAST provides programmatic access to the extracted predictions through a REST API. The Swagger UI is intended to explore the data and create REST URLs that can be included in code. The links can be included in almost any programming language such as:

Property Access

FLARECAST provides programmatic access to the extracted properties through a REST API. The properties describe the Solar features which are used as input to the machine learning algorithms. The Swagger UI is intended to explore the data and create REST URLs that can be incorporated into code. This API is intended for developers of new machine learning techniques.