tropea_clustering.OnionMulti

class tropea_clustering.OnionMulti(ndims=2, bins='auto', number_of_sigmas=2.0)[source]

Performs onion clustering on a data array.

Parameters:
state_list_

List of the identified states.

Type:

List[StateMulti]

labels_

Cluster labels for each point. Unclassified points are given the label -1.

Type:

ndarray of shape (n_particles * n_windows,)

Methods

fit

Performs onion clustering on the data array 'X'.

fit_predict

Computes clusters on the data array 'X' and returns labels.

get_params

Get parameters for this estimator.

set_params

Set the parameters of this estimator.

fit(X, y=None)[source]

Performs onion clustering on the data array ‘X’.

Parameters:

X (ndarray of shape (n_particles * n_windows, tau_window * n_features)) – The raw data. Notice that each signal window is considered as a single data point.

Returns:

self – A fitted instance of self.

Return type:

object

fit_predict(X, y=None)[source]

Computes clusters on the data array ‘X’ and returns labels.

Parameters:

X (ndarray of shape (n_particles * n_windows, tau_window * n_features)) – The raw data. Notice that each signal window is considered as a single data point.

Returns:

labels_ – Cluster labels for each point. Unclassified points are given the label -1.

Return type:

ndarray of shape (n_particles * n_windows,)

get_params(deep=True)[source]

Get parameters for this estimator.

Parameters:

deep (bool, default=True) – If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns:

params – Parameter names mapped to their values.

Return type:

dict

set_params(**params)[source]

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:

**params (dict) – Estimator parameters.

Returns:

self – Estimator instance.

Return type:

estimator instance