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']))
