mvpa2.mappers.wavelet.WaveletTransformationMapper¶
-
class
mvpa2.mappers.wavelet.
WaveletTransformationMapper
(dim=1, wavelet='sym4', mode='per', maxlevel=None)¶ Convert signal into wavelet representaion
Notes
Available conditional attributes:
calling_time+
: Noneraw_results
: Nonetrained_dataset
: Nonetrained_nsamples+
: Nonetrained_targets+
: Nonetraining_time+
: None
(Conditional attributes enabled by default suffixed with
+
)Attributes
auto_train
Whether the Learner performs automatic trainingwhen called untrained. descr
Description of the object if any force_train
Whether the Learner enforces training upon everycalled. is_trained
Whether the Learner is currently trained. pass_attr
Which attributes of the dataset or self.ca to pass into result dataset upon call postproc
Node to perform post-processing of results space
Processing space name of this node Methods
__call__
(ds)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 _WaveletMapper mapper
Parameters: dim : int or tuple of int
dimensions to work across (for now just scalar value, ie 1D transformation) is supported
wavelet : str
one from the families available withing pywt package
mode : str
periodization mode
maxlevel : int or None
number of levels to use. If None - automatically selected by pywt
enable_ca : None or list of str
Names of the conditional attributes which should be enabled in addition to the default ones
disable_ca : None or list of str
Names of the conditional attributes which should be disabled
Attributes
auto_train
Whether the Learner performs automatic trainingwhen called untrained. descr
Description of the object if any force_train
Whether the Learner enforces training upon everycalled. is_trained
Whether the Learner is currently trained. pass_attr
Which attributes of the dataset or self.ca to pass into result dataset upon call postproc
Node to perform post-processing of results space
Processing space name of this node Methods
__call__
(ds)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