[yt-dev] Coordinate transformations and periodic boundaries

[Matthew Turk]

Hi John,


On Thu, Sep 8, 2016 at 10:22 AM, John ZuHone <jzuhone at gmail.com> wrote:

> Hi all,
>
> I’m working on some updates to my yt-based pyXSIM package and I’m stuck
> and I thought I would email this list for some guidance.
>
> I’m thinking of a situation where we have a data object (sphere, box,
> whatever) and it straddles a periodic boundary. I want to convert the
> coordinates such that the coordinates are translated with respect to some
> arbitrary origin (say, the center of a sphere but in theory it could be
> anywhere), but are also continuous, i.e, they do not wrap at the boundary.
>
> I’ve looked at the functions get_radius and get_periodic_rvec in
> yt/fields/field_functions.py, and based on that I have come up with the
> code below, but it doesn’t quite work for any arbitrary value of the “ctr”
> argument (the origin). I think it’s because the functions I mentioned only
> need to calculate absolute value differences in order to compute a radius.
>
> The x, y, and z arguments to the function below are the input coordinate
> arrays. Could anyone who is more familiar with this sort of thing point out
> what I should be doing?
>

I think that Doug implemented something in the region selector that does
exactly this; it computes whether or not something needs a coordinate
shift, and then if so, it applies that.  If you look through
selection_routines.pyx for anything with "shift" in the name, it should be
there.  If that doesn't do what you're looking for, we can try to figure
something else out.


>
> Best,
>
> John Z
>
> def get_periodic_coords(ds, ctr, x, y, z):
>     coords = ds.arr(np.zeros((3, x.size)), "kpc")
>     coords[0, :] = (x - ctr[0]).to("kpc")
>     coords[1, :] = (y - ctr[1]).to("kpc")
>     coords[2, :] = (z - ctr[2]).to("kpc")
>     if sum(ds.periodicity) == 0:
>         return coords
>     dw = ds.domain_width.to("kpc")
>     for i in range(3):
>         if ds.periodicity[i]:
>             c = coords[i, :]
>             cdw = c - dw[i]
>             mins = np.argmin([np.abs(c), np.abs(cdw)], axis=0)
>             ii = np.where(mins == 1)[0]
>             coords[i, ii] = coords[i, ii] - dw[i]
>     return coords
>
>
>
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