Required
data| Type: | np.ndarray |
| Description: | The data to taper. Will be checked to ensure that it is of the correct shape (n_rec, n_cmp, n_samples). |
def taper(
data: np.ndarray,
filter_params: TaperingFilterParams = TaperingFilterParams(
max_percentage=0.05,
window=scipy.signal.windows._windows.hann,
side=both,
),
) -> npt.NDArray: ...| Type: | np.ndarray |
| Description: | The data to taper. Will be checked to ensure that it is of the correct shape (n_rec, n_cmp, n_samples). |
| Type: | TaperingFilterParams |
| Default value: | TaperingFilterParams(max_percentage=0.05, window=scipy.signal.windows._windows.hann, side=both) |
| Description: | The parameters controlling the tapering window. |
npt.NDArrayclass TaperingFilterParams(builtins.object):
def __init__(
self,
max_percentage: float = 0.05,
window: typing.Callable[
[int], np.ndarray
] = scipy.signal.windows._windows.hann,
side: str = "both",
) -> None: ...| Type: | float |
| Default value: | 0.05 |
| Description: | The maximum percentage of the trace length over which to apply the taper. The window will ramp from its endpoint values to its midpoints value over this length. Note that this means that the filter sizes are may be double of what you may expect, as each individual side of 2-sided filter should cover the requested length. |
| Type: | typing.Callable[[int], np.ndarray] |
| Default value: | scipy.signal.windows._windows.hann |
| Description: | The type of window used to perform the tapering. |
| Type: | str |
| Default value: | 'both' |
| Description: | Apply the taper to the "left" side of the trace (smaller time values), the "right" side (larger time values), or "both". |