`salvus.project.tools.processing.block_processing.adjust_length`

Blockwise length adjustment.

Functions

`adjust_length()`

def adjust_length(
    data: np.ndarray, t_in: np.ndarray, filter_params: LengthAdjustmentParams
) -> tuple[np.ndarray, np.ndarray]: ...

Adjust the length of receivers along the time axis (-1).

Useful for both padding data and/or trimming data. See the documentation of LengthAdjustmentParams for an explanation of the adjustment settings.

Parameters

data np.ndarray — The data to resample. Will be checked to ensure that it is of the correct shape (n_rec, n_cmp, n_samples).
t_in np.ndarray — The time axis of the input samples. Must be strictly increasing.
filter_params LengthAdjustmentParams — Parameters controlling the padding / trimming of the input receiver traces.

Returns tuple[np.ndarray, np.ndarray] — A tuple of the (new_time_axis, trimmed / padded receivers).

Classes

`LengthAdjustmentParams`

class LengthAdjustmentParams(builtins.object):
    def __init__(
        self, start_time: float, end_time: float, fill_value: float = 0.0
    ) -> None: ...

Parameters controlling padding and / or trimming of receiver arrays.

Start and end times which are not a multiple of the receiver array’s constant time step will be truncated to the nearest multiple of the time step. This is similar to “nearest_sample = True” in Obspy’s trim function. Receiver values outside the domain of the input time axis will be filled with fill_value.

Parameters

start_time float — The desired start time of the trace.
end_time float — The desired end time of the trace.
fill_value float — The value to fill with when the new length is greater than the old length.