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Hi Matt,<br>
<br>
The data can certainly be arranged so that there's either full
overlap or no overlap between the datasets. But I'm not sure what
you mean by dynamic/computed masking.<br>
<br>
Best,<br>
Jonah<br>
<br>
<div class="moz-cite-prefix">On 15-08-21 10:59 PM, Matthew Turk
wrote:<br>
</div>
<blockquote
cite="mid:CALO3=5Gq6qGVqzUhwZJFqqj4m3uv6onQTfDhxVAPedPAdhrdEg@mail.gmail.com"
type="cite">Hi Jonah,
<div><br>
</div>
<div>I've been thinking about this, and I wonder if it's possible
to identify which sections overlap. Is there partial overlap
between two given cells, or do cells either overlap or *not*
overlap? If there's only full overlap in cells (i.e., a cell in
one section totally overlaps with a cell in a different section)
then I think we can do dynamic or computed masking and create a
single unified dataset. Does that make sense?</div>
<div><br>
</div>
<div>-Matt<br>
<br>
On Thursday, August 20, 2015, Jonah Miller <<a
moz-do-not-send="true"
href="mailto:jonah.maxwell.miller@gmail.com">jonah.maxwell.miller@gmail.com</a>>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">
<div text="#000000" bgcolor="#FFFFFF"> Hi Matt,<br>
<br>
Thanks for the reply. The datasets are a six patches
coordinate system. I've attached some images of the six data
sets, and how they should stitch together. From that, it
would be nice to be able to do analysis on them---i.e., make
an arbitrary slice plot. <br>
<br>
It's straightforward to stitch <i>four of</i> the actual
arrays together and leave out the top and bottom patches.
The problem is getting all six to work together.<br>
<br>
Best,<br>
Jonah<br>
<br>
<div>On 15-08-20 09:21 AM, Matthew Turk wrote:<br>
</div>
<blockquote type="cite">
<div dir="ltr">Hi Jonah,
<div><br>
</div>
<div>Right now, I think this would be tricky. I'm
trying to figure out precisely how it could be done
without compositing the datasets themselves, and I'm
not sure it's terribly feasible at the time being
without some trickery. One possibility, since the
data is spherical, is to get fixed res buffers for
each section of the plot you want, then utilize
matplotlib to stitch those together into a single
plot. It might help if you had a little sketch so
that your desired outcome could be a bit more visual?</div>
<div><br>
</div>
<div>-Matt</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Wed, Aug 19, 2015 at 2:31
PM, Jonah Miller <span dir="ltr"><<a
moz-do-not-send="true"
href="javascript:_e(%7B%7D,'cvml','jonah.maxwell.miller@gmail.com');"
target="_blank">jonah.maxwell.miller@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">Hi
Everyone,<br>
<br>
I have data for a simulation in spherical
coordinates that I wish to input into yt and
visualize using the generic reader tools. However,
the simulation is broken up into six volumes, each
of which is a solid angle that makes up part of a
sphere. Unfortunately, stitching together the arrays
of data produces a lot of redundancies, there's no
easy way to include all of it in a single array
without including the same data points several
times. So what I'd like is a way to feed in each
solid angle as an individual data set, but visualize
all six datasets on a single plot. Is this possible?<br>
<br>
Thanks in advance for your help!<br>
<br>
Best,<br>
Jonah MIller<br>
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