| Multivariate Pattern Analysis in Python

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This content refers to the previous stable release of PyMVPA. Please visit www.pymvpa.org for the most recent version of PyMVPA and its documentation.

# datasets.masked

## Module: `datasets.masked`

Inheritance diagram for `mvpa.datasets.masked`:

Dataset with applied mask

## `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.

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