stack_cm

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

Run the stacking algorithm on CM data (multi-position chop)

result = frame1 - frame2 - frame3 - … - frameN

Parameters:
datanumpy.ndarray

(nframe, nrow, ncol)

headerastropy.io.fits.header.Header

FITS header to update with HISTORY messages

variancenumpy.ndarray, optional

variance array to propagate (nframe, nrow, ncol)

extradict, optional
If set will be updated with:
chopsub -> numpy.ndarray (nrow, ncol)

chop-subtracted data (same as output data in this case)

Returns:
2-tuple

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