[yt-users] stitching data sets together

[Jonah Miller]

Hi Matt,

Yes, I've uploaded a tarball with a dataset and my preliminary attempts 
to stitch it together (in an ipython notebook). It also includes a graph 
showing the connectivity.

Here's the file: http://use.yt/upload/d4218c8d

Thanks for your help!

Best,
Jonah

On 15-08-30 04:11 PM, Matthew Turk wrote:
> Hi Jonah,
>
> Sorry, I should have been more explicit.  If we regard the dataset as 
> "AMR" where the "AMR" is all on the same level, cells should be able 
> to be overlapped.  Can you provide an example set of connectivity, 
> even with fake values, that could be experimented with?
>
> On Fri, Aug 21, 2015 at 10:47 PM, Jonah Miller 
> <jonah.maxwell.miller at gmail.com 
> <mailto:jonah.maxwell.miller at gmail.com>> wrote:
>
>     Hi Matt,
>
>     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.
>
>     Best,
>     Jonah
>
>
>     On 15-08-21 10:59 PM, Matthew Turk wrote:
>>     Hi Jonah,
>>
>>     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?
>>
>>     -Matt
>>
>>     On Thursday, August 20, 2015, Jonah Miller
>>     <jonah.maxwell.miller at gmail.com
>>     <mailto:jonah.maxwell.miller at gmail.com>> wrote:
>>
>>         Hi Matt,
>>
>>         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.
>>
>>         It's straightforward to stitch /four of/ the actual arrays
>>         together and leave out the top and bottom patches. The
>>         problem is getting all six to work together.
>>
>>         Best,
>>         Jonah
>>
>>         On 15-08-20 09:21 AM, Matthew Turk wrote:
>>>         Hi Jonah,
>>>
>>>         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?
>>>
>>>         -Matt
>>>
>>>         On Wed, Aug 19, 2015 at 2:31 PM, Jonah Miller
>>>         <jonah.maxwell.miller at gmail.com> wrote:
>>>
>>>             Hi Everyone,
>>>
>>>             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?
>>>
>>>             Thanks in advance for your help!
>>>
>>>             Best,
>>>             Jonah MIller
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>>>
>>>
>>>
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>>
>>
>>
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