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mvpa.datasets.masked

Dataset with applied mask

The comprehensive API documentation for this module, including all technical details, is available in the Epydoc-generated API reference for mvpa.datasets.masked (for developers).

MaskedDataset

class mvpa.datasets.masked.MaskedDataset(samples=None, mask=None, **kwargs)

Bases: mvpa.datasets.mapped.MappedDataset

Helper class which is MappedDataset with using MaskMapper.

TODO: since what it does is simply some checkes/data_mangling in the constructor, it might be absorbed inside generic MappedDataset

Parameters:
  • mask (ndarray) – the chosen features equal the non-zero mask elements.
selectFeaturesByMask(mask, plain=False)

Use a mask array to select features from the current set.

Parameters:
  • mask (ndarray) – input mask
  • plain (bool) – True directs to return a simple Dataset, False – a new MaskedDataset object

Returns a new MaskedDataset object with a view of the original pattern array (no copying is performed). The final selection mask only contains features that are present in the current feature mask AND the selection mask passed to this method.

See also

Derived classes might provide additional methods via their base classes. Please refer to the list of base classes (if it exists) at the begining of the MaskedDataset documentation.

Full API documentation of MaskedDataset in module mvpa.datasets.masked.