__init__(self,
datameasure,
radius=1.0,
center_ids=None,
**kwargs)
(Constructor)
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:Parameters:
datameasure: callable
Any object that takes a :class:`~mvpa.datasets.base.Dataset`
and returns some measure when called.
radius: float
All features within the radius around the center will be part
of a sphere. Provided dataset should have a metric assigned
(for NiftiDataset, voxel size is used to provide such a metric,
hence radius should be specified in mm).
center_ids: list(int)
List of feature ids (not coordinates) the shall serve as sphere
centers. By default all features will be used.
**kwargs
In additions this class supports all keyword arguments of its
base-class :class:`~mvpa.measures.base.DatasetMeasure`.
.. note::
If `Searchlight` is used as `SensitivityAnalyzer` one has to make
sure that the specified scalar `DatasetMeasure` 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 sensitivites and this conflicts
with the intended behavior of a `SensitivityAnalyzer`.
- Parameters:
transformer , Functor - This functor is called in __call__() to perform a final
processing step on the to be returned dataset measure. If None,
nothing is called
null_dist , instance , of , distribution , estimator - The estimated distribution is used to assign a probability for a
certain value of the computed measure.
- Overrides:
object.__init__
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