edges_analysis.filters.filters.chunked_iterative_model_filter

edges_analysis.filters.filters.chunked_iterative_model_filter(*, x: ndarray, data: ndarray, flags: ndarray | None = None, init_flags: ndarray | None = None, chunk_size: float = inf, **kwargs) → tuple[ndarray, ndarray, ndarray]

Perform a chunk-wise iterative model filter.

This breaks the given data into smaller chunks and then calls edges_cal.xrfi.model_filter() on each chunk, returning the full 1D array of flags after all the chunks have been processed.

Parameters:

• chunk_size – The size of the chunks to process, in units of the input coordinates, x.

• **kwargs – Everything else is passed to edges_cal.xrfi.model_filter().

Returns:

• flags – The 1D array of flags corresponding to the data. Note that input flags are not modified in the course of this function, but the output does already contain those flags.

• resid – Residuals to the model

• std – Estimates of the standard deviation of the data at each data point.