WFLFilter#
- class myoverse.datasets.filters.temporal.WFLFilter(input_is_chunked, is_output=False, name=None, run_checks=True, *, window_size, shift=1)[source]#
Filter that computes the waveform length [1] of the input array.
Waveform length is the sum of the absolute differences between consecutive samples. It is a measure of the total magnitude of the signal.
\[\text{WFL} = \sum_{i=1}^{N} |x_i - x_{i-1}|\]- Parameters:
input_is_chunked (bool) – Whether the input is chunked or not.
is_output (bool) – Whether the filter is an output filter. If True, the resulting signal will be outputted by and dataset pipeline.
name (str | None) – Name of the filter, by default None.
run_checks (bool) –
Whether to run the checks when filtering. By default, True. If False can potentially speed up performance.
Warning
If False, the user is responsible for ensuring that the input array is valid.
window_size (int) – The window size to use.
shift (int) – The shift to use. Default is 1.
References
Methods
__init__(input_is_chunked[, is_output, ...])