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 = []