stack_stare

sofia_redux.instruments.forcast.stack.stack_stare(data, header, variance=None)[source]

Run the stacking algorithm on STARE data

result = median of all frames

The variance is approximated as (pi/2) times the variance of a mean operation.

Parameters:
datanumpy.ndarray

(nframes, nrow, ncol)

headerastropy.io.fits.header.Header

FITS header to update with HISTORY messages

variancenumpy.ndarray, optional

variance array to propagate (nframes, nrow, ncol)

Returns:
2-tuple

numpy.ndarray : The stacked data array (nrow, ncol) numpy.ndarray : The propagated variance array (nrow, ncol)