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

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# Class SplitFeaturewiseMeasure

source code

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.ClassWithCollections`: `__metaclass__`

Instance Methods | [hide private]

__init__(self, sensana, splitter=NoneSplitter, combiner=FirstAxisMean, **kwargs) Cheap initialization. | source code

_call(self, dataset) Compute sensitivity maps for all dataset splits and run the postprocessing functions afterward (if any). | source code

Inherited from `base.FeaturewiseDatasetMeasure`: `__repr__`, `combiner`

Inherited from `base.FeaturewiseDatasetMeasure` (private): `_postcall`

Inherited from `base.DatasetMeasure`: `__call__`, `null_dist`, `transformer`, `untrain`

Inherited from `misc.state.ClassWithCollections`: `__getattribute__`, `__new__`, `__setattr__`, `__str__`, `reset`

Inherited from `object`: `__delattr__`, `__format__`, `__hash__`, `__reduce__`, `__reduce_ex__`, `__sizeof__`, `__subclasshook__`

Class Variables | [hide private]

Inherited from `base.FeaturewiseDatasetMeasure`: `base_sensitivities` Inherited from `base.DatasetMeasure`: `__doc__`, `null_prob`, `null_t`, `raw_results` Inherited from `misc.state.ClassWithCollections`: `_DEV__doc__`, `descr`

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 Store the maps across splits

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, sensana, splitter=NoneSplitter, combiner=FirstAxisMean, **kwargs)
(Constructor)

source code

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)

source code

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