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    Hi Matt, <br>
    <br>
    Thanks very much for your comments!<br>
    <br>
    <div class="moz-cite-prefix">On 16-05-06 11:58 AM, Matthew Turk
      wrote:<br>
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cite="mid:CALO3=5F-d0NQbF2YpMrWuf5b2KrR3GUhfv0d3PCpb8oQsYELsQ@mail.gmail.com"
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      <div dir="ltr">I think that the cost is likely dominated by the
        vertex-centering.  It may be possible to overload
        get_vertex_centered_data for your subclass of AMRPatchGrid to
        make this faster based on your data format.  I am not sure that
        it is a huge cost to do the ray casting itself; there are likely
        python operations like writing the image, etc, that are a
        non-negligible fraction of that time.</div>
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    <br>
    I see. Do you have any insight into how we might prepare the data to
    facilitate this? Or how we might prepare the data to minimize the
    cost here? For example, is yt more efficient with many small grids
    or with a few large grids? Since we perform a pre-processing step
    before feeding our data to yt, it may be possible to generate grids
    that are efficient for yt.<br>
    <br>
    Best,<br>
    Jonah<br>
    <br>
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cite="mid:CALO3=5F-d0NQbF2YpMrWuf5b2KrR3GUhfv0d3PCpb8oQsYELsQ@mail.gmail.com"
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                  <p> </p>
                  <p>I'd love to know other people's experience with
                    benchmarking. Do these costs seem normal, up to an
                    order of magnitude or so? Would you have any insight
                    into what contributes to the cost of generating the
                    first frame when volume rendering?<br>
                  </p>
                  <p>Thanks very much!<br>
                  </p>
                  <p>Best,<br>
                    Jonah Miller<br>
                  </p>
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