def __init__(self, queryengine, roi_ids=None, nproc=None, **kwargs):
"""
Parameters
----------
queryengine : QueryEngine
Engine to use to discover the "neighborhood" of each feature.
See :class:`~mvpa.misc.neighborhood.QueryEngine`.
roi_ids : None or list(int) or str
List of feature ids (not coordinates) the shall serve as ROI seeds
(e.g. sphere centers). Alternatively, this can be the name of a
feature attribute of the input dataset, whose non-zero values
determine the feature ids. 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.
**kwargs
In addition this class supports all keyword arguments of its
base-class :class:`~mvpa.measures.base.Measure`.
"""
Measure.__init__(self, **kwargs)
if nproc > 1 and not externals.exists('pprocess'):
raise RuntimeError("The 'pprocess' module is required for "
"multiprocess searchlights. Please either "
"install python-pprocess, or reduce `nproc` "
"to 1 (got nproc=%i)" % nproc)
self._queryengine = queryengine
if roi_ids is not None and not isinstance(roi_ids, str) \
and not len(roi_ids):
raise ValueError, \
"Cannot run searchlight on an empty list of roi_ids"
self.__roi_ids = roi_ids
self.nproc = nproc
def __init__(self, dsmatrix, dset_metric, output_metric='spearman'):
Measure.__init__(self)
self.dsmatrix = dsmatrix
self.dset_metric = dset_metric
self.output_metric = output_metric
self.dset_dsm = []
