before_hook_normalize

class torcheeg.transforms.before_hook_normalize(data: ndarray, eps: float = 1e-06, axis=0)

A common hook function used to normalize the signal of the whole trial/session/subject before dividing it into chunks.

It is used as follows:

from functools import partial
from torcheeg.datasets import SEEDFeatureDataset
from torcheeg.transforms import before_hook_normalize

dataset = SEEDFeatureDataset(root_path='./ExtractedFeatures',
                             feature=['de_movingAve'],
                             offline_transform=transforms.ToGrid       (SEED_CHANNEL_LOCATION_DICT),
                             online_transform=transforms.ToTensor(),
                             before_trial=before_hook_normalize,
                             label_transform=transforms.Compose([
                                 transforms.Select('emotion'),
                                 transforms.Lambda(lambda x: x + 1)
                             ]))

If you want to pass in parameters, use partial to generate a new function:

from functools import partial
from torcheeg.datasets import SEEDFeatureDataset
from torcheeg.transforms import before_hook_normalize

dataset = SEEDFeatureDataset(root_path='./ExtractedFeatures',
                             feature=['de_movingAve'],
                             offline_transform=transforms.ToGrid       (SEED_CHANNEL_LOCATION_DICT),
                             online_transform=transforms.ToTensor(),
                             before_trial=partial(before_hook_normalize, eps=1e-5),
                             label_transform=transforms.Compose([
                                 transforms.Select('emotion'),
                                 transforms.Lambda(lambda x: x + 1)
                             ]))

Parameters:

• data (np.ndarray) – The input EEG signals or features of a trial.

• axis (int) – The axis along which to normalize the data (default: 0)

• eps (float) – The term added to the denominator to improve numerical stability (default: 1e-6)

Returns:

The normalized results of a trial.

Return type:

np.ndarray