def __init__(self, knn, generator, qe, **kwargs):
"""Initialize a M1NNSearchlight
TODO -- example? or just kill altogether
rethink providing knn sample vs specifying all parameters
explicitly
Parameters
----------
knn : `kNN`
Used to fetch space and dfx settings. TODO
"""
# verify that desired features are supported
if knn.dfx == squared_euclidean_distance:
self._distance = 'euclidean'
elif knn.dfx == one_minus_correlation:
self._distance = 'correlation'
# we rely on having simple indexes for ROI members ATM
if 'indexsum' in kwargs and kwargs['indexsum'] != 'fancy':
raise ValueError("Can only use indexsum='fancy' with correlation distance.")
kwargs['indexsum'] = 'fancy'
else:
raise ValueError(
"%s distance function is not yet supported by M1NNSearchlight"
% (knn.dfx,))
# init base class first
SimpleStatBaseSearchlight.__init__(self, generator, qe, **kwargs)
self._knn = knn
self.__pl_train = self.__pl_test = None
def __init__(self, knn, generator, qe, **kwargs):
"""Initialize a M1NNSearchlight
TODO -- example? or just kill altogether
rethink providing knn sample vs specifying all parameters
explicitly
Parameters
----------
knn : `kNN`
Used to fetch space and dfx settings. TODO
"""
# verify that desired features are supported
if knn.dfx == squared_euclidean_distance:
self._distance = 'euclidean'
elif knn.dfx == one_minus_correlation:
self._distance = 'correlation'
# we rely on having simple indexes for ROI members ATM
if 'indexsum' in kwargs and kwargs['indexsum'] != 'fancy':
raise ValueError(
"Can only use indexsum='fancy' with correlation distance.")
kwargs['indexsum'] = 'fancy'
else:
raise ValueError(
"%s distance function is not yet supported by M1NNSearchlight"
% (knn.dfx, ))
# init base class first
SimpleStatBaseSearchlight.__init__(self, generator, qe, **kwargs)
self._knn = knn
self.__pl_train = self.__pl_test = None
def __init__(self, gnb, generator, qe, **kwargs):
"""Initialize a GNBSearchlight
Parameters
----------
gnb : `GNB`
`GNB` classifier as the specification of what GNB parameters
to use. Instance itself isn't used.
"""
# init base class first
SimpleStatBaseSearchlight.__init__(self, generator, qe, **kwargs)
self._gnb = gnb
self.__pl_train = None
def __init__(self, gnb, generator, qe, **kwargs):
"""Initialize a GNBSearchlight
Parameters
----------
gnb : `GNB`
`GNB` classifier as the specification of what GNB parameters
to use. Instance itself isn't used.
"""
# init base class first
SimpleStatBaseSearchlight.__init__(self, generator, qe, **kwargs)
self._gnb = gnb
self.__pl_train = None
def __init__(self, knn, generator, qe, **kwargs):
"""Initialize a M1NNSearchlight
TODO -- example? or just kill altogether
rethink providing knn sample vs specifying all parameters
explicitly
Parameters
----------
knn : `kNN`
Used to fetch space and dfx settings. TODO
"""
# verify that desired features are supported
if knn.dfx != squared_euclidean_distance:
raise ValueError(
"%s distance function is not yet supported by M1NNSearchlight"
% (knn.dfx,))
# init base class first
SimpleStatBaseSearchlight.__init__(self, generator, qe, **kwargs)
self._knn = knn
self.__pl_train = self.__pl_test = None
def __init__(self, knn, generator, qe, **kwargs):
"""Initialize a M1NNSearchlight
TODO -- example? or just kill altogether
rethink providing knn sample vs specifying all parameters
explicitly
Parameters
----------
knn : `kNN`
Used to fetch space and dfx settings. TODO
"""
# verify that desired features are supported
if knn.dfx != squared_euclidean_distance:
raise ValueError(
"%s distance function is not yet supported by M1NNSearchlight"
% (knn.dfx, ))
# init base class first
SimpleStatBaseSearchlight.__init__(self, generator, qe, **kwargs)
self._knn = knn
self.__pl_train = self.__pl_test = None
