At the risk of putting this thread back on-topic, my original question was not "should I just lossfully compress my images and throw away the originals". My question was:

 "would you download the compressed images first?"

So far, noone has really answered it.

I think it is obvious that of course we would RATHER have the original data, but if access to the original data is "slow" (by a factor of 30 at best) then can the "mp3 version" of diffraction data play a useful role in YOUR work?

Taking Graeme's request from a different thread as an example, he would like to see stuff in P21 with a 90 degree beta angle. There are currently ~609 examples of this in the PDB. So, I ask again: "which one would you download first?". 1aip? (It is first alphabetically). Then again, if you just email the corresponding authors of all 609 papers, the response rate alone might whittle the number of datasets to deal with down to less than 10. Perhaps even less than 1.

-James Holton
MAD Scientist


On 11/8/2011 5:17 AM, Graeme Winter wrote:
Dear Herbert,

Sorry, the point I was getting at was that the process is one way, but
if it is also *destructive* i.e. the original "master" is not
available then I would not be happy. If the master copy of what was
actually recorded is available from a tape someplace perhaps not all
that quickly then to my mind that's fine.

When we go from images to intensities, the images still exist. And by
and large the intensities are useful enough that you don't go back to
the images again. This is worth investigating I believe, which is why
I made that proposal.

Mostly I listen to mp3's as they're convenient, but I still buy CD's
not direct off e.g. itunes, and yes a H264 compressed video stream is
much nicer to watch than VHS.

Best wishes,

Graeme

On 8 November 2011 12:17, Herbert J. Bernstein
<y...@bernstein-plus-sons.com>  wrote:
Um, but isn't Crystallograpy based on a series of
one-way computational processes:
     photons ->  images
     images ->  {struture factors, symmetry}
  {structure factors, symmetry, chemistry} ->  solution
  {structure factors, symmetry, chemistry, solution}
      ->  refined solution

At each stage we tolerate a certain amount of noise
in "going backwards".  Certainly it is desirable to
have the "original data" to be able to go forwards,
but until the arrival of pixel array detectors, we
were very far from having the true original data,
and even pixel array detectors don't capture every
single photon.

I am not recommending lossy compressed images as
a perfect replacement for lossless compressed images,
any more than I would recommend structure factors
are a replacement for images.  It would be nice
if we all had large budgets, huge storage capacity
and high network speeds and if somebody would repeal
the speed of light and other physical constraints, so that
engineering compromises were never necessary, but as
James has noted, accepting such engineering compromises
has been of great value to our colleagues who work
with the massive image streams of the entertainment
industry.  Without lossy compression, we would not
have the _higher_ image quality we now enjoy in the
less-than-perfectly-faithful HDTV world that has replaced
the highly faithful, but lower capacity, NTSC/PAL world.

Please, in this, let us not allow the perfect to be
the enemy of the good.  James is proposing something
good.

Regards,
  Herbert
=====================================================
              Herbert J. Bernstein
    Professor of Mathematics and Computer Science
   Dowling College, Kramer Science Center, KSC 121
        Idle Hour Blvd, Oakdale, NY, 11769

                 +1-631-244-3035
                 y...@dowling.edu
=====================================================

On Tue, 8 Nov 2011, Harry Powell wrote:

Hi

I am not a fan
of one-way computational processes with unique data.

Thoughts anyone?

Cheerio,

Graeme

I agree.

Harry
--
Dr Harry Powell, MRC Laboratory of Molecular Biology, MRC Centre, Hills
Road, Cambridge, CB2 0QH


http://www.iucr.org/resources/commissions/crystallographic-computing/schools/mieres2011

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