floatcsep.evaluation.Evaluation

class floatcsep.evaluation.Evaluation(name, func, func_kwargs=None, ref_model=None, plot_func=None, plot_args=None, plot_kwargs=None, markdown='')

Class representing a Scoring Test, which wraps the evaluation function, its arguments, parameters and hyper-parameters.

Parameters:

• name (str) – Name of the Test

• func (str, Callable) – Test function/callable

• func_kwargs (dict) – Keyword arguments of the test function

• ref_model (str) – String of the reference model, if any

• plot_func (str, Callable) – Test’s plotting function

• plot_args (list,dict) – Positional arguments of the plotting function

• plot_kwargs (list,dict) – Keyword arguments of the plotting function

__init__(name, func, func_kwargs=None, ref_model=None, plot_func=None, plot_args=None, plot_kwargs=None, markdown='')

Methods

__init__(name, func[, func_kwargs, ...])
as_dict()	Represents an Evaluation instance as a dictionary, which can be serialized and then parsed
compute(timewindow, catalog, model, path[, ...])	Runs the test, structuring the arguments according to the
from_dict(record)	Parses a dictionary and re-instantiate an Evaluation object
get_catalog(catalog_path, forecast)	Reads the catalog(s) from the given path(s).
parse_plots(plot_func, plot_args, plot_kwargs)
plot_results(timewindow, models, tree[, ...])	Plots all evaluation results
prepare_args(timewindow, catpath, model[, ...])	Prepares the positional argument for the Evaluation function.
read_results(window, models, tree)	Reads an Evaluation result for a given time window and returns a list of the results for all tested models.
write_result(result, path)	Dumps a test result into a json file.

Attributes

type	Returns the type of the test, mapped from the class attribute Evaluation._TYPES