Reshaping mapper that flattens multidimensional arrays into 1D vectors.
This mapper performs relatively cheap reshaping of arrays from ND into 1D and back upon reverse-mapping. The mapper has to be trained with a data array or dataset that has the first axis as the samples-separating dimension. Mapper training will set the particular multidimensional shape the mapper is transforming into 1D vector samples. The setting remains in place until the mapper is retrained.
Notes
At present this mapper is only designed (and tested) to work with C-ordered arrays.
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 |
Parameters: | shape : tuple
maxdims : int or None
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 |