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PyMVPA: Python MultiVariate Pattern Analysis
Package mvpa :: Package mappers :: Module samplegroup :: Class SampleGroupMapper
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Class SampleGroupMapper

source code

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...)

Instance Methods [hide private]
 
__init__(self, fx=FirstAxisMean)
Initialize the PCAMapper		 source code
 
train(self, dataset)
Perform training of the mapper.		 source code
 
forward(self, data)
Map data from the IN dataspace into OUT space.		 source code
 
reverse(self, data)
This is not implemented.		 source code
 
getInSize(self)
Returns the number of original samples which were combined.		 source code
 
getOutSize(self)
Returns the number of output samples.		 source code
 
selectOut(self, outIds)
Just complain for now		 source code

Inherited from base.Mapper: __call__, __repr__, getInId, getMetric, getNeighbor, getNeighborIn, getNeighbors, isValidInId, isValidOutId, setMetric

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __str__, __subclasshook__

Class Variables [hide private]
  __doc__ = enhancedDocString('SampleGroupMapper', locals(), Map...

Inherited from base.Mapper: metric, nfeatures

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, fx=FirstAxisMean)
(Constructor)

source code 

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')
Parameters:
  • metric - Optional metric
Overrides: object.__init__

train(self, dataset)

source code 

Perform training of the mapper.

This method is called to put the mapper in a state that allows it to perform to intended mapping.

The default behavior of this method is to do nothing.
Overrides: base.Mapper.train

forward(self, data)

source code 
Map data from the IN dataspace into OUT space.
Overrides: base.Mapper.forward

reverse(self, data)

source code 
This is not implemented.
Overrides: base.Mapper.reverse

getInSize(self)

source code 
Returns the number of original samples which were combined.
Overrides: base.Mapper.getInSize

getOutSize(self)

source code 
Returns the number of output samples.
Overrides: base.Mapper.getOutSize

selectOut(self, outIds)

source code 
Just complain for now
Parameters:
  • outIds, sequence - Subset of ids of the current feature in OUT space to keep.
Overrides: base.Mapper.selectOut

Class Variable Details [hide private]

__doc__

Value:
enhancedDocString('SampleGroupMapper', locals(), Mapper)

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PyMVPA: Python MultiVariate Pattern Analysis
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