Mailman 3 July 2025 - yt-users

2025 Higgs Centre Workshop videos
by Matthew Turk July 29, 2025

July 29, 2025

Hi folks, The videos from the 2025 yt Workshop at the Higgs Centre have now been posted: https://www.youtube.com/playlist?list=PL8tPWjc5gBfQLLvTK1G_48o_D6RgaLC48 There may be one or two new ones added, as we had some technical difficulties with a couple that the presenters intend to re-record. Thanks to everyone who organized, presented and attended -- it was really a ton of fun, and, on a personal note, really helped me feel connected with the community again. -Matt

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Getting 2D Cylindrical Symmetry FLASH output onto a smooth, uniform 2D grid for analysis
by dsmont80＠gmail.com July 15, 2025

July 15, 2025

Hi All, I'm new to FLASH, and new to YT. We've been running 2D cylindrically symmetric laser-irradiated target simulations in FLASH. The computational domain is 1200e-4 cm (1200 microns) in R, and 2400e-4 cm (2400 microns) in Z. Nblockx =2, Nblocky=2 with lrefine_max = 5 (number of AMR refinement levels). We have been using We've been using the following Python to read in with YT: data = yt.load(filename) slc = data.slice(2,0) xmin, ymin, thetamin = data.domain_left_edge.d # minimum domain coordinates in cm xmax, ymax, thetamax = data.domain_right_edge.d # maximum domain coordinates in cm Lx = (xmax - xmin)*1e4 # length of x-axis (r-axis in R-Z cylindrical geometry) in microns Ly = (ymax - ymin)*1e4 # length of y-axis (z-axis in R-Z cylindrical geometry) in microns Nx = int(Lx + 1) #number of pixels in r-axis Ny = int(Ly + 1) #number of pixels in z-axis and using "FixedResolutionBuffer" to map the variables of choice to a 2D array with dimensions of our choosing (here Nx=1201 and Ny=2401, where each pixel is effectively 1-micron x 1-micron) with the following: frb = yt.FixedResolutionBuffer(slc,(xmin,xmax,ymin,ymax),(Ny,Nx), antialias=True) dens = np.nan_to_num(np.array(frb["flash","dens"])) eden = np.nan_to_num(np.array(frb["gas", "El_number_density"])) Te = np.nan_to_num(np.array(frb["flash", "tele"]))/11605.0 # convert to eV The images we get for dens, eden and Te look decent enough, but since we are trying to map to a uniform grid that is higher resolution than the actual simulation, we get "stair stepping" in some regions, especially where there's not much refinement occurring. We think that our solution somehow might be in using "smooth_covering_grid" because we want the data to be interpolated on a finer grid, but so far have been having troubles. Is there a way to use FixedResolutionBuffer so that it will interpolate to a finer resolution between the simulation grid cells, or how would be implement "smoothed_covering_grid" such that it will create 2D arrays with the desired number of rows and columns (Ny, Nx)?

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yt 4.4.1 out now!
by Chris Havlin July 8, 2025

July 8, 2025

Hello yt users! yt 4.4.1 is now available. It includes some important bug fixes and we recommend that you upgrade (particularly if you are attending the yt user workshop next week!). For a description of the changes, see the 4.4.1 Release Notes <https://github.com/yt-project/yt/releases/tag/yt-4.4.1>. To upgrade from PyPI (available now!), run python -m pip install --upgrade yt The conda feedstock will take some time to update, but in the next few days you should be able to use conda to update with: conda update --channel conda-forge yt Cheers, Chris

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Help with plotting 2D AMR HDF5 data
by bcurlee＠xcimer.net July 1, 2025

July 1, 2025

First, forgive me if this is an obvious question; I'm still pretty new to FLASH (the source of my hdf5 AMR data) and even newer to yt. I'm trying to find a good way to plot a 2-dimensional color-mapped plot of some of the data in the file (["flash","tele"],["flash","dens"],etc), and I've encountered a few methods but, as much as it annoys me to say it, none of them has been better (when weighted for end-user convenience) than VisIt so far. The yt-native SlicePlot command is... fine, but hindered by the need to re-run the script with an edited filename for each plot count increment. So I've been trying to get my data into an array form that MatPlotLib will accept (not that that fixes my file issue, but I know MatPlotLib better). Unfortunately, this means fighting with the imshow command if I want a colorbar at all. The meat of my question, then, is: what's the best way to rip all of a given data field from an hdf5 file in a way that will produce an nxn array of equal spacing? Currently, I've found I can brute-force a solution by defining a covering grid over my data (level 0) using data_dimensions, finding the shape of my desired field, finding the minimum array length of that field, and defining a new covering grid (also level 0) limited to that minimum length in both of my relevant dimensions (my FLASH sims are only 2D), and using np.squeeze to pull out the size-1 z-index, but the most I've ever seen that output is 32 data points, and commonly only 16, which yields terrible plot resolution. I assume there's a better way of doing this; does anyone more experienced than me have a good way of getting this to work? I'm in azimuthally-symmetric cylindrical geometry, to specify. Hence why I actively don't want the third data axis.

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