mne.decoding.
Scaler
(info, with_mean=True, with_std=True)¶Standardizes data across channels
Parameters: | info : instance of Info
with_mean : boolean, True by default
with_std : boolean, True by default
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Attributes: | info : instance of Info
ch_mean_ : dict
std_ : dict
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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)
y : array, shape (n_epochs,)
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Returns: | self : instance of Scaler
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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]
y : numpy array of shape [n_samples]
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Returns: | X_new : numpy array of shape [n_samples, n_features_new]
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inverse_transform
(epochs_data, y=None)¶Inverse standardization of data across channels
Parameters: | epochs_data : array, shape (n_epochs, n_channels, n_times)
y : None | array, shape (n_epochs,)
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Returns: | X : array, shape (n_epochs, n_channels, n_times)
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transform
(epochs_data, y=None)¶Standardizes data across channels
Parameters: | epochs_data : array, shape (n_epochs, n_channels, n_times)
y : None | array, shape (n_epochs,)
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Returns: | X : array, shape (n_epochs, n_channels, n_times)
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