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docs: Finished the evaluation config docs. Added .js to custom behavior of external links (now open in a new tab). Added sphinx-design for expandable tables.
**floatCSEP** evaluate forecasts using the testing procedures from **pyCSEP** (See `Testing Theory <https://docs.cseptesting.org/getting_started/theory.html>`_). Depending on the forecast type (e.g., **GriddedForecasts** or **CatalogForecasts**), different evaluation functions can be used. T
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**floatCSEP** evaluate forecasts using the routines defined in **pyCSEP** (See `Testing Theory <https://docs.cseptesting.org/getting_started/theory.html>`_). Depending on the forecast types (e.g., **GriddedForecasts** or **CatalogForecasts**), different evaluation functions can be used.
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Each evaluation specifies a `func` parameter, representing the evaluation function to be applied, and a `plot_func` parameter for visualizing the results.
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Each evaluation specifies a ``func`` parameter, representing the evaluation function to be applied, a configuration of the function with ``func_kwargs`` (e.g., number of simulations, confidence intervals) and a ``plot_func`` parameter for visualizing the results. Evaluations for **GriddedForecasts** typically use functions from :mod:`csep.core.poisson_evaluations` or :mod:`csep.core.binomial_evaluations`, while evaluations for **CatalogForecasts** use functions from :mod:`csep.core.catalog_evaluations`.
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Evaluations for **GriddedForecasts** typically use functions from :mod:`csep.core.poisson_evaluations` or :mod:`csep.core.binomial_evaluations`, while evaluations for **CatalogForecasts** use functions from :mod:`csep.core.catalog_evaluations`.
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.. important::
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An evaluation in ``test_config`` points to a **pyCSEP** `evaluation function <https://docs.cseptesting.org/concepts/evaluations.html>`_, valid for the forecast class.
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The structure of the evaluation configuration file is similar to the model configuration, with multiple tests, each pointing to a specific evaluation function and plotting method.
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**Example Configuration**:
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.. code-block:: yaml
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:caption: test_config.yml
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- N-test:
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func: poisson_evaluations.number_test
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plot_func: plot_poisson_consistency_test
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- S-test:
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func: poisson_evaluations.spatial_test
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plot_func: plot_poisson_consistency_test
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Evaluation Parameters:
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----------------------
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Each evaluation listed in ``test_config`` accepts the following parameters:
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.. list-table::
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:widths:20 80
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:widths:30 80
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:header-rows: 1
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* - **Parameter**
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- **Description**
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* - **func** (required)
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- The evaluation function, specifying which test to run. Must be an available function from the pyCSEP evaluation suite (e.g., `poisson_evaluations.number_test`).
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- Specify which evaluation/test function to run. Must be a **pyCSEP** ``{module}.{function}`` suite \
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(e.g., :func:`poisson_evaluations.number_test <csep.core.poisson_evaluations.number_test>`) or
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**floatCSEP** function.
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* - **func_kwargs**
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- Any keyword argument to control the specific **func**. For example, :func:`poisson_evaluations.spatial_test <csep.core.poisson_evaluations.spatial_test>` may be configured with ``num_simulations: 2000``.
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* - **plot_func** (required)
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- The function to plot the evaluation results, specified from the available plotting functions (e.g., `plot_poisson_consistency_test`).
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- The function to plot the evaluation results, from either the :mod:`csep.utils.plots` module (e.g., :func:`plot_poisson_consistency_test <csep.utils.plots.plot_poisson_consistency_test>`) or **floatCSEP** :mod:`~floatcsep.utils.helpers` module.
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* - **plot_args**
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- Arguments passed to customize plot titles, labels, or font size.
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- Arguments passed to customize the plot function. Can be titles, labels, colors, font size, etc. Review the documentation of the respective function.
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* - **plot_kwargs**
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- Keyword arguments passed to the plotting function for fine-tuning plot appearance (e.g., `one_sided_lower: True`).
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- Keyword arguments to customize the plot function. Review the documentation of the respective function.
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* - **ref_model**
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- A reference model against which the current model is compared in comparative tests (e.g., `Model A`).
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* - **markdown**
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- A description of the test to be used as caption when reporting results
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Evaluations Functions:
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----------------------
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Depending on the type of forecast being evaluated, different evaluation functions are used:
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1. **GriddedForecasts**:
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.. list-table::
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* - **Function**
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- **Description**
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* - **poisson_evaluations.number_test**
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- Evaluates the forecast by comparing the total number of forecasted events with the observed events using a Poisson distribution.
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* - **poisson_evaluations.spatial_test**
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- Compares the spatial distribution of forecasted events to the observed events.
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* - **poisson_evaluations.magnitude_test**
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- Evaluates the forecast by comparing the magnitude distribution of forecasted events with observed events.
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`YAML` (Yet Another Markup Language) is a human-readable format used for configuration files. It uses **key: value** pairs to define settings, and indentation to represent nested structures. Lists are denoted by hyphens (`-`).
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