Mapper using IIR filters for data transformation.
This mapper is able to perform any IIR-based low-pass, high-pass, or band-pass frequency filtering. This is a front-end for SciPy’s filtfilt(), hence its usage looks almost exactly identical, and any of SciPy’s IIR filters can be used with this mapper:
>>> from scipy import signal
>>> b, a = signal.butter(8, 0.125)
>>> mapper = IIRFilterMapper(b, a, padlen=150)
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 |
All constructor parameters are analogs of filtfilt() or are passed on to the Mapper base class.
Parameters: | b : (N,) array_like
a : (N,) array_like
axis :
padtype :
padlen :
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
|
---|
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 |