mvpa2.mappers.mdp_adaptor.MDPNodeMapper

Inheritance diagram of MDPNodeMapper

class mvpa2.mappers.mdp_adaptor.MDPNodeMapper(node, nodeargs=None, **kwargs)

Mapper encapsulating an arbitray MDP node.

This mapper wraps an MDP node and uses it for forward and reverse data mapping (reverse is only available if the underlying MDP node supports it). It is possible to specify arbitrary arguments for all processing steps of an MDP node (training, training stop, execution, and inverse).

Because MDP does not allow to ‘reset’ a node and (re)train it from scratch the mapper uses a copy of the initially wrapped node for the actual processing. Upon subsequent training attempts a new copy of the original node is made and replaces the previous one.

Notes

MDP nodes requiring multiple training phases are not supported. Use a MDPFlowWrapper for that. Moreover, it is not possible to perform incremental training of a node.

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 +)

Methods

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 to None to disable postprocessing.
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:

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.

nodeargs : dict

Dictionary for additional arguments for all calls to the MDP node. The dictionary key’s meaning is as follows:

‘train’

Arguments for calls to Node.train()

‘stoptrain’

Arguments for calls to Node.stop_training()

‘exec’

Arguments for calls to Node.execute()

‘inv’

Arguments for calls to Node.inverse()

The value for each item is always a 2-tuple, consisting of a tuple (for the arguments), and a dictionary (for keyword arguments), i.e. ((), {}). Both, tuple and dictionary have to be provided even if they are empty.

space : see base class

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

auto_train : bool

Flag whether the learner will automatically train itself on the input dataset when called untrained.

force_train : bool

Flag whether the learner will enforce training on the input dataset upon every call.

postproc : Node instance, optional

Node to perform post-processing of results. This node is applied in __call__() to perform a final processing step on the to be result dataset. If None, nothing is done.

descr : str

Description of the instance

Methods

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 to None to disable postprocessing.
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

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NITRC-listed