| 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.

# mappers.ica

## Module: `mappers.ica`

Inheritance diagram for `mvpa.mappers.ica`:

Data mapper

## `ICAMapper`

class `mvpa.mappers.ica.``ICAMapper`(algorithm='cubica', transpose=False, **kwargs)

  Bases: `mvpa.mappers.base.ProjectionMapper`

  Mapper to project data onto ICA components estimated from some dataset.

  After the mapper has been instantiated, it has to be train first. The ICA mapper only handles 2D data matrices.

  See also

  Please refer to the documentation of the base class for more information:

  `ProjectionMapper`

  Initialize instance of ICAMapper

  Parameters:

  - selector (None | list) – Which components (i.e. columns of the projection matrix) should be used for mapping. If selector is None all components are used. If a list is provided, all list elements are treated as component ids and the respective components are selected (all others are discarded).
  - demean (bool) – Either data should be demeaned while computing projections and applied back while doing reverse()

### Navigation

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