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YT rendering on clusters[edit]

To install YT for CPU rendering on a cluster in your own directory, please do

$ module load python mpi4py
$ virtualenv astro    # install Python tools in your $HOME/astro
$ source ~/astro/bin/activate
$ pip install cython
$ pip install numpy
$ pip install yt

Then, in normal use, simply load the environment and start python

$ source ~/astro/bin/activate   # load the environment
$ python
$ deactivate

We assume that you have downloaded the sample dataset Enzo_64 from Start with the following script `` to render 90 frames rotating the dataset around the vertical axis

import yt
from numpy import pi
yt.enable_parallelism()   # turn on MPI parallelism via mpi4py
ds = yt.load("Enzo_64/DD0043/data0043")
sc = yt.create_scene(ds, ('gas', 'density'))
cam =
cam.resolution = (1024, 1024)   # resolution of each frame
sc.annotate_domain(ds, color=[1, 1, 1, 0.005])   # draw the domain boundary [r,g,b,alpha]
sc.annotate_grids(ds, alpha=0.005)   # draw the grid boundaries'frame0000.png', sigma_clip=4)
nspin = 90
for i in cam.iter_rotate(pi, nspin):   # rotate by 180 degrees over nspin frames'frame%04d.png' % (i+1), sigma_clip=4)

and the job submission script ``

#SBATCH --time=0:30:00   # walltime in d-hh:mm or hh:mm:ss format
#SBATCH --ntasks=4       # number of MPI processes
#SBATCH --mem-per-cpu=3800
#SBATCH --account=...
source $HOME/astro/bin/activate
srun python

Then submit the job with `sbatch`, wait for it to finish, and then create a movie at 30fps

$ ffmpeg -r 30 -i frame%04d.png -c:v libx264 -pix_fmt yuv420p -vf "scale=trunc(iw/2)*2:trunc(ih/2)*2" grids.mp4