seiz_eeg.transforms

Transformations functions and classes to use in pipelines

class seiz_eeg.transforms.Concatenate(func_list: List[Callable[[Any], Any]])

Apply list of functions one after the other

class seiz_eeg.transforms.ExtractFromAxis(axis: int, extremes: Tuple[int | None, int | None])

Extract slice of tensor from given axis

class seiz_eeg.transforms.OldTransform(window_size: int | None = None, fft_coeffs: Tuple[int, int] | None = None, mean: ndarray | None = None, std: ndarray | None = None)

Sequence of transforms from previous code version

class seiz_eeg.transforms.SplitWindows(window_size: int)

Split windows

seiz_eeg.transforms.get_diff_signals(signals: DataFrame[SignalsDF], label_channels: List[str]) → DataFrame[SignalsDiffDF]

Take as input a signals dataframe and return the columm differences specified in label_channels