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docs: corrected api reference layout. Now explicited the modules instead of relying too much in autosummary. The latter is only used to create summary tables in the APi landing page. Renamed case_f to case_g. Fixed link to matplotlib docs. Added catch for floatcsep logger, to detect if sphinx is being used and relay to the general logger instead of floatlogger
docs: corrected api reference layout. Now explicited the modules instead of relying too much in autosummary. The latter is only used to create summary tables in the APi landing page. Renamed case_f to case_g. Fixed link to matplotlib docs. Added catch for floatcsep logger, to detect if sphinx is being used and relay to the general logger instead of floatlogger
@@ -8,7 +8,7 @@ A - Simple(st) Time-Dependent, Catalog-based Model
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.. admonition:: **TL; DR**
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In a terminal, navigate to ``floatcsep/examples/case_f`` and type:
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In a terminal, navigate to ``floatcsep/examples/case_g`` and type:
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.. code-block:: console
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@@ -23,7 +23,7 @@ Artifacts
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This example shows how a time-dependent model should be set up for a time-dependent experiment
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::
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case_f
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case_g
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└── pymock
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├── input
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├── args.txt (model arguments)
@@ -49,7 +49,7 @@ The experiment's complexity increases from time-independent to dependent, since
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1. The input data is, at the least, a catalog filtered until the forecast beginning, which is automatically allocated by ``fecsep`` in the `{model}/input` prior to each model's run. It is stored inside the model in ``csep.ascii`` format for simplicity's sake (see :doc:`pycsep:concepts/catalogs`).
2. The input arguments controls how the source code works. The minimum arguments to run a model (which should be modified dynamically during an experiment) are the forecast ``start_date`` and ``end_date``. The experiment will read `{model}/input/args.txt` and change the values of ``start_date = {datetime}`` and ``end_date = {datetime}`' before the model is run. Additional arguments can be set by convenience, such as ``catalog`` (the input catalog name), ``n_sims`` (number of synthetic catalogs) and random ``seed`` for reproducibility.
@@ -80,7 +80,7 @@ Time
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The configuration is identical to time-independent models, with the exception that now a ``horizon`` can be defined instead of ``intervals``, which is the forecast time-window length. The experiment's class should now be explicited as ``exp_class: td``
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@@ -13,7 +13,7 @@ A Floating Testing Experiment encapsulates each experiment into its own runnable
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evaluations.
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``floatCSEP`` goals
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----------------
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-------------------
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This is an application to deploy reproducible and prospective experiments of earthquake forecasting, namely a Floating Eperiment, that can operate independent of a particular testing server. With this application, researchers, institutions and users can
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