Package mvpa :: Package measures :: Module splitmeasure :: Class SplitFeaturewiseMeasure
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Class SplitFeaturewiseMeasure

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This is a FeaturewiseDatasetMeasure that uses another FeaturewiseDatasetMeasure and runs it multiple times on differents splits of a Dataset.

When called with a Dataset it returns the mean sensitivity maps of all data splits.

Additonally this class supports the State interface. Several postprocessing functions can be specififed to the constructor. The results of the functions specified in the postproc dictionary will be available via their respective keywords.

Nested Classes [hide private]

Inherited from misc.state.Stateful: __metaclass__

Instance Methods [hide private]
 
__init__(self, sensana, splitter=<class 'mvpa.datasets.splitter.NoneSplitter'>, combiner=<function FirstAxisMean at 0x874a994>, **kwargs)
Cheap initialization.
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_call(self, dataset)
Compute sensitivity maps for all dataset splits and run the postprocessing functions afterward (if any).
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Inherited from base.FeaturewiseDatasetMeasure (private): _postcall

Inherited from base.DatasetMeasure: __call__, __str__

Inherited from misc.state.Stateful: __getattribute__, __repr__, __setattr__, reset

Inherited from object: __delattr__, __hash__, __new__, __reduce__, __reduce_ex__

Class Variables [hide private]
  _collections_template = {'states': <mvpa.misc.state.StateColle...

Inherited from base.FeaturewiseDatasetMeasure: base_sensitivities

Inherited from base.DatasetMeasure: __doc__, null_prob, raw_result

Inherited from misc.state.Stateful (private): _initargs

Instance Variables [hide private]
  __sensana
Sensitivity analyzer used to compute the sensitivity maps.
  __splitter
Splitter instance used to split the datasets.
  __combiner
Function to combine sensitivities to serve a result of __call__()
  maps = <mvpa.misc.state.StateVariable object at 0x8c68eac>
Store the maps across splits
Properties [hide private]

Inherited from misc.state.Stateful: descr

Inherited from object: __class__

Method Details [hide private]

__init__(self, sensana, splitter=<class 'mvpa.datasets.splitter.NoneSplitter'>, combiner=<function FirstAxisMean at 0x874a994>, **kwargs)
(Constructor)

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Cheap initialization.
Parameters:
  • sensana (FeaturewiseDatasetMeasure) - that shall be run on the Dataset splits.
  • splitter (Splitter) - used to split the Dataset. By convention the first dataset in the tuple returned by the splitter on each iteration is used to compute the sensitivity map.
  • combiner - This functor will be called on an array of sensitivity maps and the result will be returned by __call__(). The result of a combiner must be an 1d ndarray.
Overrides: object.__init__

_call(self, dataset)

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Compute sensitivity maps for all dataset splits and run the postprocessing functions afterward (if any).

Returns a list of all computed sensitivity maps. Postprocessing results are available via the objects State interface.

Overrides: base.DatasetMeasure._call

Class Variable Details [hide private]

_collections_template

Value:
{'states': <mvpa.misc.state.StateCollection object at 0x8c68e8c>}