Package mvpa :: Package mappers :: Module boxcar :: Class BoxcarMapper

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# Class BoxcarMapper

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Mapper to combine multiple samples into a single sample.

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, startpoints, boxlength, offset=0, collision_resolution='mean') x.__init__(...) initializes x; see help(type(x)) for signature | source code

__repr__(self) repr(x) | source code

forward(self, data) Project an ND matrix into N+1D matrix | source code

reverse(self, data) Uncombine features back into original space. | source code

getInSize(self) Returns the number of original samples which were combined. | source code

isValidOutId(self, outId) Validate if OutId is valid | source code

isValidInId(self, inId) Validate if InId is valid | 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__`, `getInId`, `getMetric`, `getNeighbor`, `getNeighborIn`, `getNeighbors`, `setMetric`, `train` Inherited from `object`: `__delattr__`, `__format__`, `__getattribute__`, `__hash__`, `__new__`, `__reduce__`, `__reduce_ex__`, `__setattr__`, `__sizeof__`, `__str__`, `__subclasshook__`

Class Variables | [hide private]

| _COLLISION_RESOLUTIONS = `['mean']`
| __doc__ = `enhancedDocString('BoxcarMapper', locals(), Mapper)`
Inherited from `base.Mapper`: `metric`, `nfeatures`

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, startpoints, boxlength, offset=0, collision_resolution='mean')
(Constructor)

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x.__init__(...) initializes x; see help(type(x)) for signature

Parameters:
  - `startpoints`, `sequence` - Index values along the first axis of 'data'.
  - `boxlength`, `int` - The number of elements after 'startpoint' along the first axis of 'data' to be considered for the boxcar.
  - `offset`, `int` - The offset between the provided starting point and the actual start of the boxcar.
  - `collision_resolution` ('mean') - if a sample belonged to multiple output samples, then on reverse, how to resolve the value
Overrides: object.__init__

### __repr__(self)
(Representation operator)

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repr(x)

Overrides: object.__repr__
  (inherited documentation)

### forward(self, data)

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Project an ND matrix into N+1D matrix

This method also handles the special of forward mapping a single 'raw' sample. Such a sample is extended (by concatenating clones of itself) to cover a full boxcar. This functionality is only availably after a full data array has been forward mapped once.

Returns:
  array: (#startpoint, ...)
Overrides: base.Mapper.forward

### reverse(self, data)

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Uncombine features back into original space.

Samples which were not touched by forward will get value 0 assigned

Overrides: base.Mapper.reverse

### getInSize(self)

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Returns the number of original samples which were combined.

Overrides: base.Mapper.getInSize

### isValidOutId(self, outId)

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Validate if OutId is valid

Overrides: base.Mapper.isValidOutId

### isValidInId(self, inId)

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Validate if InId is valid

Overrides: base.Mapper.isValidInId

### getOutSize(self)

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Returns the number of output samples.

Overrides: base.Mapper.getOutSize

### selectOut(self, outIds)

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Just complain for now

Parameters:
  - `outIds`, `sequence` - Subset of ids of the current feature in OUT space to keep.
Overrides: base.Mapper.selectOut