ertk.preprocessing.kmeans.KMeansExtractor

class ertk.preprocessing.kmeans.KMeansExtractor(config: KMeansExtractorConfig)

Bases: FeatureExtractor

KMeans vector quantiser.

__init__(config: KMeansExtractorConfig) → None

Methods

__init__(config)
process_instance(x, **kwargs)	Process a single audio clip.

Inherited Methods

finish()	Perform any cleanup necesasry (e.g.
friendly_name()	Get the friendly name for this processor.
get_config_type()	Get the configuration type for this processor.
get_default_config()	Get the default configuration for this processor.
get_processor_class(name)	Get the class for the named processor.
make_processor(name, config)	Create an instance of the named processor.
process_all(xs, batch_size, **kwargs)	Process all instances in batches.
process_batch(batch, **kwargs)	Process a batch of instances.
valid_processors()	Get a list of all registered processor names.

Attributes

dim	The dimensionality of the extracted features.
feature_names	The names of the features produced by this processor.
is_sequence	Whether this FeatureExtractor yields sequence features.
config	The configuration for this processor.

config: KMeansExtractorConfig

The configuration for this processor.

property feature_names: list[str]

The names of the features produced by this processor.

property is_sequence: bool

Whether this FeatureExtractor yields sequence features.

process_instance(x: ndarray, **kwargs) → ndarray

Process a single audio clip.

Parameters:

x: np.ndarray

The audio data to process.

Returns:

result: np.ndarray

The processed instance.