Dataset

sekupy.utils.dataset.ds_to_dataframe(ds, keys=None, melt=False)

[summary]

Parameters:

• ds ([type]) – [description]

• keys (list, optional) – [description] (the default is [‘band’, ‘targets’, ‘subjects’], which [default_description])

• melt (bool, optional) – [description] (the default is False, which [default_description])

Returns:

[description]

Return type:

[type]

sekupy.utils.dataset.get_ds_data(ds, target_attribute='targets')

This function simpy returns X and y for scikit-learn analyses starting from a pymvpa dataset.

Parameters:

• ds (dataset sekupy.dataset.base.Dataset) – The dataset in pymvpa format

• target_attribute (str, optional) –

  The sample attribute to be used to extract labels

  (the default is ‘targets’, which [default_description])

Returns:

A tuple with the X data matrix (samples x features) and the y array of labels.

Return type:

X, y

sekupy.utils.dataset.temporal_attribute_reshaping(attribute_list, time_attribute)

[summary]

Parameters:

• attribute_list ([type]) – [description]

• time_attribute ([type]) – [description]

Returns:

[description]

Return type:

[type]

sekupy.utils.dataset.temporal_transformation(X, y, time_attr)

[summary]

Parameters:

• X ([type]) – [description]

• y ([type]) – [description]

• time_attr ([type]) – [description]

Returns:

[description]

Return type:

[type]