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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.

measures.pls

Module: measures.pls

Inheritance diagram for mvpa.measures.pls:

Classes

PLS

class mvpa.measures.pls.PLS(num_permutations=200, num_bootstraps=100, **kwargs)

Bases: mvpa.measures.base.FeaturewiseDatasetMeasure

No documentation found. Sorry!

Note

Available state variables:

  • base_sensitivities: Stores basic sensitivities if the sensitivity relies on combining multiple ones
  • null_prob+: State variable
  • null_t: State variable
  • raw_results: Computed results before applying any transformation algorithm

(States enabled by default are listed with +)

See also

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

FeaturewiseDatasetMeasure

Initialize instance of PLS

Parameters:
  • enable_states (None or list of basestring) – Names of the state variables which should be enabled additionally to default ones
  • disable_states (None or list of basestring) – Names of the state variables which should be disabled
  • combiner (Functor) – The combiner is only applied if the computed featurewise dataset measure is more than one-dimensional. This is different from a transformer, which is always applied. By default, the sum of absolute values along the second axis is computed.
  • transformer (Functor) – This functor is called in __call__() to perform a final processing step on the to be returned dataset measure. If None, nothing is called
  • null_dist (instance of distribution estimator) – The estimated distribution is used to assign a probability for a certain value of the computed measure.

TaskPLS

class mvpa.measures.pls.TaskPLS(num_permutations=200, num_bootstraps=100, **kwargs)

Bases: mvpa.measures.pls.PLS

No documentation found. Sorry!

Note

Available state variables:

  • base_sensitivities: Stores basic sensitivities if the sensitivity relies on combining multiple ones
  • null_prob+: State variable
  • null_t: State variable
  • raw_results: Computed results before applying any transformation algorithm

(States enabled by default are listed with +)

See also

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

PLS

Initialize instance of PLS

Parameters:
  • enable_states (None or list of basestring) – Names of the state variables which should be enabled additionally to default ones
  • disable_states (None or list of basestring) – Names of the state variables which should be disabled
  • combiner (Functor) – The combiner is only applied if the computed featurewise dataset measure is more than one-dimensional. This is different from a transformer, which is always applied. By default, the sum of absolute values along the second axis is computed.
  • transformer (Functor) – This functor is called in __call__() to perform a final processing step on the to be returned dataset measure. If None, nothing is called
  • null_dist (instance of distribution estimator) – The estimated distribution is used to assign a probability for a certain value of the computed measure.