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mappers.samplegroup

Module: mappers.samplegroup

Inheritance diagram for mvpa.mappers.samplegroup:

Data mapper

SampleGroupMapper

class mvpa.mappers.samplegroup.SampleGroupMapper(fx=<function FirstAxisMean at 0x4892de8>)

Bases: mvpa.mappers.base.Mapper

Mapper to apply a mapping function to samples of the same type.

A customimzable function is applied individually to all samples with the same unique label from the same chunk. This mapper is somewhat unconventional since it doesn’t preserve number of samples (ie the size of 0-th dimension...)

See also

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

Mapper

Initialize the PCAMapper

Parameters:

• startpoints (A sequence of index value along the first axis of) – ‘data’.
• boxlength (The number of elements after ‘startpoint’ along the) – first axis of ‘data’ to be considered for averaging.
• offset (The offset between the starting point and the) – averaging window (boxcar).
• collision_resolution (string) – if a sample belonged to multiple output samples, then on reverse, how to resolve the value (choices: ‘mean’)

forward(data)

getInSize()

Returns the number of original samples which were combined.

getOutSize()

Returns the number of output samples.

reverse(data)

This is not implemented.

selectOut(outIds)

Just complain for now

train(dataset)