def __repr__(self, prefixes=[]): return super(GNBSearchlight, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['gnb', 'generator']) + _repr_attrs(self, ['errorfx'], default=mean_mismatch_error) + _repr_attrs(self, ['indexsum']) )
def __repr__(self, prefixes=[]): return super(CrossValidation, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['learner', 'splitter']) + _repr_attrs(self, ['errorfx'], default=mean_mismatch_error) + _repr_attrs(self, ['space'], default='sa.cvfolds') )
def __repr__(self, prefixes=[]): return super(FxMapper, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['axis', 'fx', 'uattrs']) + _repr_attrs(self, ['fxargs'], default=()) + _repr_attrs(self, ['attrfx'], default='merge') )
def __repr__(self): """String representation of `SKLLearnerWrapper` """ prefixes = [repr(self._skl_learner)] if self.__tags__ != ['skl']: prefixes += ['tags=%r' % [t for t in self.__tags__ if t != 'skl']] prefixes += _repr_attrs(self, ['enforce_dim']) return Classifier.__repr__(self, prefixes=prefixes)
def __repr__(self, prefixes=[]): """String representation of a `Measure` Includes only arguments which differ from default ones """ return super(Measure, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['null_dist']))
def __repr__(self, prefixes=[]): """String representation of a `Measure` Includes only arguments which differ from default ones """ return super(BaseSearchlight, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['queryengine', 'roi_ids', 'nproc']))
def __repr__(self, prefixes=None, fullname=False): """String definition of the object of ClassWithCollections object Parameters ---------- prefixes : list of str What other prefixes to prepend to list of arguments fullname : bool Either to include full name of the module """ prefixes = prefixes or [] prefixes = prefixes[:] # copy list id_str = "" module_str = "" if __debug__: if 'MODULE_IN_REPR' in debug.active: fullname = True if 'ID_IN_REPR' in debug.active: id_str = '#%r' % id(self) if fullname: modulename = '%s' % self.__class__.__module__ if modulename != "__main__": module_str = "%s." % modulename # Collections' attributes collections = self._collections # we want them in this particular order for col in _COLLECTIONS_ORDER: collection = collections.get(col, None) if collection is None: continue prefixes += collection._cls_repr() # Description if present prefixes += _repr_attrs(self, ['descr']) out = "%s%s(%s)%s" % (module_str, self.__class__.__name__, ', '.join(prefixes), id_str) # To possibly debug mass repr/str-fication # print str(self), ' REPR: ', out return out
def __repr__(self, prefixes=[]): return super(CombinedFeaturewiseMeasure, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['analyzers']) + _repr_attrs(self, ['sa_attr'], default='combinations') )
def __repr__(self, prefixes=[]): return super(Sensitivity, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['clf']) + _repr_attrs(self, ['force_train'], default=True) )
def __repr__(self, prefixes=[]): return super(StaticMeasure, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['measure', 'bias']) )
def __repr__(self, prefixes=[]): return super(TransferMeasure, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['measure', 'splitter']) )
def __repr__(self, prefixes=[]): return super(SliceMapper, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['slicearg']))
def __repr__(self, prefixes=[]): return super(RepeatedMeasure, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['node', 'generator', 'callback']) + _repr_attrs(self, ['concat_as'], default='samples') )
def __repr__(self, prefixes=[]): return super(IndexQueryEngine, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['sorted'], default=True))
def __repr__(self, prefixes=[]): return super(FeatureSelection, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['dshape', 'oshape']))
def __repr__(self, prefixes=[]): return super(Searchlight, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['datameasure']) + _repr_attrs(self, ['add_center_fa'], default=False) )
def __repr__(self, prefixes=[]): return super(ZScoreMapper, self).__repr__( prefixes=prefixes + _repr_attrs(self, ["params", "param_est", "chunks_attr"]) + _repr_attrs(self, ["dtype"], default="float64") )
def __repr__(self, prefixes=[]): return super(Learner, self).__repr__( prefixes=prefixes + _repr_attrs(self, ["auto_train", "force_train"], default=False) )
def __repr__(self, prefixes=[]): return super(FlattenMapper, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['shape', 'maxdims']))
def __repr__(self, prefixes=[]): """String representation of a `ProxyMeasure` """ return super(ProxyMeasure, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['measure']))
def __repr__(self, prefixes=[]): return super(Node, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['space', 'postproc']))
def __repr__(self, prefixes=[]): return super(CachedQueryEngine, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['qe']))
def __repr__(self, prefixes=[]): return super(FeatureSelection, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['filler'], default=0))
def __repr__(self, prefixes=[]): return super(ChainNode, self).__repr__( prefixes=prefixes + _repr_attrs(self, ['nodes']))