mne.decoding.Scaler¶

class mne.decoding.Scaler(info, with_mean=True, with_std=True)¶

Standardizes data across channels

Parameters:	info : instance of Info The measurement info with_mean : boolean, True by default If True, center the data before scaling. with_std : boolean, True by default If True, scale the data to unit variance (or equivalently, unit standard deviation).
Attributes:	info : instance of Info The measurement info ch_mean_ : dict The mean value for each channel type std_ : dict The standard deviation for each channel type

Methods

fit(epochs_data, y)	Standardizes data across channels
fit_transform(X[, y])	Fit to data, then transform it
inverse_transform(epochs_data[, y])	Inverse standardization of data across channels
transform(epochs_data[, y])	Standardizes data across channels

__init__(info, with_mean=True, with_std=True)¶

fit(epochs_data, y)¶

Standardizes data across channels

Parameters:	epochs_data : array, shape (n_epochs, n_channels, n_times) The data to concatenate channels. y : array, shape (n_epochs,) The label for each epoch.
Returns:	self : instance of Scaler Returns the modified instance.

fit_transform(X, y=None, **fit_params)¶

Fit to data, then transform it

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters:	X : numpy array of shape [n_samples, n_features] Training set. y : numpy array of shape [n_samples] Target values.
Returns:	X_new : numpy array of shape [n_samples, n_features_new] Transformed array.

inverse_transform(epochs_data, y=None)¶

Inverse standardization of data across channels

Parameters:	epochs_data : array, shape (n_epochs, n_channels, n_times) The data. y : None | array, shape (n_epochs,) The label for each epoch. If None not used. Defaults to None.
Returns:	X : array, shape (n_epochs, n_channels, n_times) The data concatenated over channels.

transform(epochs_data, y=None)¶

Standardizes data across channels

Parameters:	epochs_data : array, shape (n_epochs, n_channels, n_times) The data. y : None | array, shape (n_epochs,) The label for each epoch. If None not used. Defaults to None.
Returns:	X : array, shape (n_epochs, n_channels, n_times) The data concatenated over channels.