stack_c2nc2

sofia_redux.instruments.forcast.stack.stack_c2nc2(data, header, variance=None, bglevel=None, extra=None)

Run the stacking algorithm on C2NC2 data

Calculates the chop-subtracted frames. For frame i (in steps of 2), the resulting chop-subtracted frame would be:

chop = frame[i] - (frame[i+1] * bgscale[i]/bgscale[i+1])

chop frames are then summed

Parameters:

datanumpy.ndarray

(npos, nrow, ncol)

headerastropy.io.fits.header.Header

FITS header to update with HISTORY messages

variancenumpy.ndarray, optional

variance array to propagate (npos, nrow, ncol)

bglevelarray_like, optional

should be of length npos

extradict, optional

If set will be updated with:

chopsub -> numpy.ndarray (npos / 2, nrow, ncol)

chop-subtracted data

chopsub_var -> numpy.ndarray (npos / 2, nrow, ncol)

propagated chop-subtracted variance

Returns:

2-tuple

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