🚀 go-pugleaf

In article <9211101358.AA01257@primate.cv.nrao.edu>
  egreisen@primate.CV.NRAO.EDU (Eric Greisen) writes:
>The method that has been used since day 1 in FITS is to specify 3 axes with
>only 1 pixel on the third axis.

Yes, but in some situations this has proved an unfortunate choice.  I've
never been happy with the practice of stuffing additional information about
the image into 1 pixel pseudo-axes.  In the case of a spectral instrument,
one might plausibly make the argument that the fundamental data is really
an M x N x 1 cube, but to stuff things like Fourier transform axis
conjugation information in as pseudo-axes is really deplorable.  To make
things more concrete, suppose that I have a set of matrix routines in my
favorite imaging package, and that I'd like it to operate on the arbitrary
contents of a FITS image.  In such a case, it really does make a difference
whether there are 1 or 2 "real" dimensions.  Is it a one dimensional image
that should be treated as a vector, (but with some number of pseudo axes
following it), or is it a two dimensional image that merely happens to have
one pixel in the second dimension?  As it stands now, there is really no
way to tell, without building in a list of recognized axis types.  I've
always felt that in an ideal world NAXIS would represent the true
dimensionality of the data, not simply the number of entries in the
coordinate arrays.  Or perhaps the other way around, and we could have an
RNAXIS keyword to hold the real number of axes.  It's not a major problem,
and I'm not seriously suggesting the above as a fix, but in a few cases I
have had to make some real kludges to get around this problem.

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| Daniel Briggs  (dbriggs@nrao.edu)                      |  USPA B-14993
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