mvpa.measures.searchlight.BaseSearchlight¶
- class mvpa.measures.searchlight.BaseSearchlight(queryengine, roi_ids=None, nproc=None, **kwargs)¶
Base class for searchlights.
The idea for a searchlight algorithm stems from a paper by Kriegeskorte et al. (2006).
Notes
Available conditional attributes:
- null_prob+: None
- null_t: None
- raw_results: Computed results before applying any transformation algorithm
- roi_sizes: Number of features in each ROI.
(Conditional attributes enabled by default suffixed with +)
Parameters: queryengine : QueryEngine
Engine to use to discover the “neighborhood” of each feature. See QueryEngine.
roi_ids : None or list of int
List of feature ids (not coordinates) the shall serve as sphere centers. By default all features will be used.
nproc : None or int
How many processes to use for computation. Requires pprocess external module. If None – all available cores will be used.
postproc : Mapper instance
Mapper to perform post-processing of results. This mapper is applied in __call__() to perform a final processing step on the to be returned dataset measure. If None, nothing is done.
null_dist : instance of distribution estimator
The estimated distribution is used to assign a probability for a certain value of the computed measure.
descr : str
Description of the instance
enable_ca : None or list of str
Names of the conditional attributes which should be enabled in addition to the default ones
disable_ca : None or list of str
Names of the conditional attributes which should be disabled
