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20 changes: 19 additions & 1 deletion docs/index.rst
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Expand Up @@ -73,7 +73,19 @@ What is floatCSEP

The `Collaboratory for the Study of Earthquake Predictability <https://cseptesting.org>`_ (CSEP) has organized Earthquake Forecast Testing Experiments during the last decades and is now consolidating its research into open-software initiatives.

**floatCSEP** is an easy-to-use software application that contains the workflow to deploy Earthquake Forecasting Experiments. It is based on the code python library **pyCSEP** (`Github <https://github.com/sceccode/pycsep>`_), which itself contains the core routines to test earthquake forecasts.
**floatCSEP** is an easy-to-use software application that contains the workflow to deploy Earthquake Forecasting Experiments. It is based on the code python library **pyCSEP** (`Github <https://github.com/sceccode/pycsep>`_), which contains the core routines to test earthquake forecasts. While pyCSEP focuses on evaluation routines, floatCSEP provides the surrounding workflow needed to define, run, and update complete testing experiments.


Why floatCSEP?
--------------

**floatCSEP** fills the gap to set up a testing experiment by

* Standardizing experiment definitions, such as clear input/testing data partitions, spatial/magnitude domains, model parameters, tests, etc.
* Orchestrating the workflow by an automated execution of all experiment tasks (building source codes, querying input data, create and test forecasts, output visualizations , etc.), while maintaining a prospective testing philosophy when required.
* Assisting with containerizing the computational environment (using Docker).
* Automated reporting and result visualization tools.


Goals
-----
Expand All @@ -83,6 +95,12 @@ Goals
* Encapsulate the complete experiment's definition and rules in a couple of lines.
* Reproduce, reuse, and share forecasting experiments.

Target users
------------

**floatCSEP** is aimed at earthquake forecast model developers, Testing Center operators, and researchers in statistical seismology who want to evaluate forecasts and design experiments in a consistent way.


Running
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