Creates a Searchlight to run a scalar Measure on all possible spheres of a certain size within a dataset.
The idea for a searchlight algorithm stems from a paper by Kriegeskorte et al. (2006).
Parameters : | datameasure : callable
radius : int
center_ids : list of int
space : str
add_center_fa : bool or str
queryengine : QueryEngine
nproc : None or int
null_dist : instance of distribution estimator
auto_train : bool
force_train : bool
enable_ca : None or list of str
disable_ca : None or list of str
postproc : Node instance, optional
descr : str
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Notes
If Searchlight is used as SensitivityAnalyzer one has to make sure that the specified scalar Measure returns large (absolute) values for high sensitivities and small (absolute) values for low sensitivities. Especially when using error functions usually low values imply high performance and therefore high sensitivity. This would in turn result in sensitivity maps that have low (absolute) values indicating high sensitivities and this conflicts with the intended behavior of a SensitivityAnalyzer.