To provide the most recent news and documentation
www.pymvpa.org reflects the
development 2.0 series (renamed 0.6 series) of PyMVPA. If you are interested in the
documentation of the previous stable 0.4 series of PyMVPA, please
visit
v04.pymvpa.org .
mvpa2.mappers.mdp_adaptor.PCAMapper
class mvpa2.mappers.mdp_adaptor. PCAMapper ( alg='PCA' , nodeargs=None , **kwargs )
Convenience wrapper to perform PCA using MDP’s Mapper
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 + )
Parameters : alg : {‘PCA’, ‘NIPALS’}
Which MDP implementation of a PCA to use.
nodeargs : None or dict
Arguments passed to the MDP node in various stages of its lifetime.
See the MDPNodeMapper for more details.
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
node : mdp.Node instance
This node instance is taken as the pristine source of which a
copy is made for actual processing upon each training attempt.
centroid
Mean of the traiing data
proj
Projection matrix (as an array)
recon
Backprojection matrix (as an array)
var
Variances per component
View the discussion thread.