We often collect data through numerical simulation, observation, or experimentation, but the data is often not readily usable as is. This raw data has to be analyzed to enhance understanding of the underlying physical phenomena. Antares helps making this data processing by delivering a set of features.
Antares can be inserted in your python computation process at the preprocessing or postprocessing stages, but can also be used in a co-processing workflow.
You can get another insight of Antares capabilities by visiting the tutorial pages.
If you are convinced that antares can help you process your data, then you might visit the installation page to see how you can get the package and get started with it. You may also want to look at the tutorial and API reference pages.