mvpa2.mappers.projection.ProjectionMapper

Inheritance diagram of ProjectionMapper

class mvpa2.mappers.projection.ProjectionMapper(demean=True)

Linear mapping between multidimensional spaces.

This class cannot be used directly. Sub-classes have to implement the _train() method, which has to compute the projection matrix _proj and optionally offset vectors _offset_in and _offset_out (if initialized with demean=True, which is default) given a dataset (see _train() docstring for more information).

Once the projection matrix is available, this class provides functionality to perform forward and backwards linear mapping of data, the latter by default using pseudo-inverse (but could be altered in subclasses, like hermitian (conjugate) transpose in case of SVD). Additionally, ProjectionMapper supports optional selection of arbitrary component (i.e. columns of the projection matrix) of the projection.

Forward and back-projection matrices (a.k.a. projection and reconstruction) are available via the proj and recon properties.

Notes

Available conditional attributes:

  • calling_time+: Time (in seconds) it took to call the node
  • raw_results: Computed results before invoking postproc. Stored only if postproc is not None.
  • training_time+: Time (in seconds) it took to train the learner

(Conditional attributes enabled by default suffixed with +)

Initialize the ProjectionMapper

Parameters :

demean : bool

Either data should be demeaned while computing projections and applied back while doing reverse()

enable_ca : None or list of str

Names of the conditional attributes which should be enabled in addition to the default ones

disable_ca : None or list of str

Names of the conditional attributes which should be disabled

proj

Projection matrix

recon

Backprojection matrix

NeuroDebian

NITRC-listed