mvpa2.mappers.mdp_adaptor.ICAMapper¶
-
class
mvpa2.mappers.mdp_adaptor.
ICAMapper
(alg='FastICA', nodeargs=None, **kwargs)¶ Convenience wrapper to perform ICA using MDP nodes.
Notes
Available conditional attributes:
calling_time+
: Noneraw_results
: Nonetrained_dataset
: Nonetrained_nsamples+
: Nonetrained_targets+
: Nonetraining_time+
: None
(Conditional attributes enabled by default suffixed with
+
)Attributes
auto_train
Whether the Learner performs automatic trainingwhen called untrained. descr
Description of the object if any force_train
Whether the Learner enforces training upon everycalled. is_trained
Whether the Learner is currently trained. pass_attr
Which attributes of the dataset or self.ca to pass into result dataset upon call postproc
Node to perform post-processing of results proj
Projection matrix (as an array) recon
Backprojection matrix (as an array) space
Processing space name of this node Methods
__call__
(ds)forward
(data)Map data from input to output space. forward1
(data)Wrapper method to map single samples. generate
(ds)Yield processing results. get_postproc
()Returns the post-processing node or None. get_space
()Query the processing space name of this node. reset
()reverse
(data)Reverse-map data from output back into input space. reverse1
(data)Wrapper method to map single samples. set_postproc
(node)Assigns a post-processing node set_space
(name)Set the processing space name of this node. train
(ds)The default implementation calls _pretrain()
,_train()
, and finally_posttrain()
.untrain
()Reverts changes in the state of this node caused by previous training Parameters: alg : {‘FastICA’, ‘CuBICA’}
Which MDP implementation of an ICA to use.
nodeargs : None or dict
Arguments passed to the MDP node in various stages of its lifetime. See the baseclass 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.
Attributes
auto_train
Whether the Learner performs automatic trainingwhen called untrained. descr
Description of the object if any force_train
Whether the Learner enforces training upon everycalled. is_trained
Whether the Learner is currently trained. pass_attr
Which attributes of the dataset or self.ca to pass into result dataset upon call postproc
Node to perform post-processing of results proj
Projection matrix (as an array) recon
Backprojection matrix (as an array) space
Processing space name of this node Methods
__call__
(ds)forward
(data)Map data from input to output space. forward1
(data)Wrapper method to map single samples. generate
(ds)Yield processing results. get_postproc
()Returns the post-processing node or None. get_space
()Query the processing space name of this node. reset
()reverse
(data)Reverse-map data from output back into input space. reverse1
(data)Wrapper method to map single samples. set_postproc
(node)Assigns a post-processing node set_space
(name)Set the processing space name of this node. train
(ds)The default implementation calls _pretrain()
,_train()
, and finally_posttrain()
.untrain
()Reverts changes in the state of this node caused by previous training -
proj
¶ Projection matrix (as an array)
-
recon
¶ Backprojection matrix (as an array)