Linear mapping between multidimensional spaces.
This class cannot be used directly. Sub-classes have to implement the _train() method, which has to compute the projection matrix _proj and optionally offset vectors _offset_in and _offset_out (if initialized with demean=True, which is default) given a dataset (see _train() docstring for more information).
Once the projection matrix is available, this class provides functionality to perform forward and backwards linear mapping of data, the latter by default using pseudo-inverse (but could be altered in subclasses, like hermitian (conjugate) transpose in case of SVD). Additionally, ProjectionMapper supports optional selection of arbitrary component (i.e. columns of the projection matrix) of the projection.
Forward and back-projection matrices (a.k.a. projection and reconstruction) are available via the proj and recon properties.
Notes
Available conditional attributes:
(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_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 |
Initialize the ProjectionMapper
Parameters: | demean : bool
enable_ca : None or list of str
disable_ca : None or list of str
auto_train : bool
force_train : bool
space : str, optional
pass_attr : str, list of str|tuple, optional
postproc : Node instance, optional
descr : str
|
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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_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 |
Projection matrix
Backprojection matrix