Thank you Brian, Nathan and Matt, I will test what you guys suggested soon and will report the progress. Thank you for your kind suggestions. Junhwan On Mon, Jun 15, 2015 at 7:57 PM, Brian O'Shea <bwoshea@gmail.com> wrote:
OK folks, after a quick offline chat with Matt, I realized that I was being overly constrained in my assumption that grid cells need to be cubes - they do not. To that end, the arbitrary_grid thing works *perfectly* to make dark matter projections. To deposit all of the particles to a 2D grid, the following script (with a few comments to clarify what's going on) works great and is a vastly better solution than mine. Thanks to Matt for pointing this out! :-)
import yt import numpy as np import matplotlib.pyplot as plt
ds = yt.load("RD0009/RD0009")
center = [0.5, 0.5, 0.5] left = [0.4, 0.4, 0.4] right = [0.6, 0.6, 0.6]
# creates 512 x 512 x 1 grid, so the 3rd dimension of the cell is very long. my_reg = ds.arbitrary_grid(left, right, dims=[512, 512, 1])
# ("deposit", "all_density") in enzo is equivalent to depositing all particles, so dm, star, etc. # the ".value" part at the end strips off the units (maybe not necessary) dens = my_reg[("deposit", "all_density")].value
# this reshapes the array from (512, 512, 1) to (512, 512), to make plt.imshow happy dens = dens.reshape( (512,512))
# sets a floor to the values which was chosen somewhat arbitrarily. dens += 1.0e-30
# plots the log of the density plt.imshow(np.log10(dens),cmap='algae')
On Mon, Jun 15, 2015 at 8:32 PM, Matthew Turk <matthewturk@gmail.com> wrote:
On Mon, Jun 15, 2015 at 7:30 PM, Brian O'Shea <bwoshea@gmail.com> wrote:
yt's "arbitrary_grid" feature might also be useful here.
http://yt-project.org/docs/dev/analyzing/objects.html?highlight=arbitrary_gr...
I concur, though if the size of the grid or number of particles is large (as in the simulation I've been working with) this can result in memory issues.
I'm hesitating to push us further into the weeds here when you've given a very thoughtful and helpful reply to Junhwan, but arbitrary_grid can be flat along one dimension (i.e., NxMx1) and was designed for this use case.
Oh, this is intriguing - I stumbled across this when I came up with my original (hacktacular) solution, but in my reading of the documentation (and, admittedly, a cursory skim of the source code) suggested that if I wanted to, say, project the density of *all* of the particles in a simulation onto a grid of [NxMx1] that it would not work - I'd only get particles that happened to intersect the one-cell-thick volume of that grid, which would give me a slice but not a projection. Did I misread that? If so, it is a much more elegant solution than mine. :-)
Yup, arbitrary_grid is more flexible than covering_grid. It accepts left edge, right edge, *and* dimensions.
-Matt
--Brian
_______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
_______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
_______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org