rose
is a framework to visualize gravitational-wave radiation using ParaView.
It is based on gwpv
written by Nils Vu. Check it out!
The name rose
comes from the flower shapes of gravitaional emission of compact binary coalescences.
Detrás de los zarzales salvajes de tu pecho
Hay una rosa que deslumbrará todo el jardín
Ruido - La Prohibida
- Create and activate Mamba/Conda environment with the Python version matching the one in ParaView
- Install the dependencies
- Start ParaView using
rose-pv
script to automatically load the plugins - Open the waveform files and setup the scene, and export the frames
- Run the overplotting script to add legends, text, logos, and other data
- Combine the frames into a video
- Enjoy the results!
- Install MambaForge using the command below:
curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh"
bash Mambaforge-$(uname)-$(uname -m).sh
In case you don't have internet access on the remote: use mitten
instead of ssh
to pass your internet connection to the remote.
-
Find the exact Python version your ParaView has. Go to ParaView->About ParaView and note down the "Python Library Version". For example, my ParaView 5.13.1 has Python 3.10.13.
-
Create and activate the Mamba environment for
rose
with the matching Python version and dependencies:
mamba create -y -n rose python=3.10.13 numpy scipy psutil astropy h5py spherical scri spherical_functions
mamba activate rose
- From the
rose
directory root, start ParaView viarose-pv
script by specifying path to your ParaView binary,
./rose-pv /path/to/paraview
or the application in case of macOS:
./rose-pv /Applications/ParaView-5.13.1.app
That will start the ParaView and load all rose
plugins.
- Now you are ready to open your waveform files using the appropriate reader. For example,
rhOverM_Asymptotic_GeometricUnits_CoM.h5
usingEnergyFluxVolumeReader
. Note that at the momementrose
supports only extrapolated waveforms in SXS catalog format, cf. Appendix A.3.1 of Boyle:2019kee.
Running locally on your machine might be too slow or not fitting into RAM for high resolution. For that reason, you might want to run it on a more powerful cluster.
The idea here is to create the scene in ParaView locally, save it to a state file, and then render it on a remote cluster. As the paths to the data files might be different locally and on the cluster, one has to readjust them by editing the state file. As I didn't write yet the script to automatically swap the path, one has has to do it manually.
The below instructions are currently outdated.
-
Copy
render/render.begin
and your state file (.pvsm
) to the cluster. -
Adjust the number of nodes, path to
rose.sif
container, and other parameters inrender.begin
. -
Begin the rendering job on your state using
spanner
:
spanner begin -f /path/to/render.begin state.pvsm
- Check the status of the job:
spanner list
- Track the process:
spanner logs -f rose_job_name
-
The job will create a directory with the same name as the state file, and output the frames there.
-
Create a video named
output.mp4
from the frames in the run directory, adding dark background:
apptainer exec --bind /scratch:/scratch --bind /work:/work ~/apptainers/rose-v2.0.0.sif \
create_video.py --frames-dir rendered --background-color 0x161616 --output output.mp4
-
Copy
render/overplot/overplot.begin
to the cluster. -
Adjust the number of nodes, path to
rose.sif
container, and other parameters inoverplot.begin
. -
Begin the rendering job on your state:
spanner begin -f /path/to/overplot.begin state.pvsm
-
The job will plot legends and a colorbar on top of the frames in the frame directory, and save postprocessed frames into
overplotted
subdirectory. -
Create a video from these frames:
apptainer exec --bind /scratch:/scratch --bind /work:/work ~/apptainers/rose-v2.0.0.sif \
create_video.py --frames-dir overplotted --output output-overplotted.mp4
This is your final movie, enjoy! 💫
Aquí y ahora puede comenzar tu viaje.