This repo contain experiments investigating how a deconvolution method performs on data relevant for climate simulation output.
The project is developed using pixi. To install, clone the repo and let pixi do the rest.
git clone https://github.com/engeir/gpu-deconv
cd gpu-deconv || exit
pixi install
Pixi is similar to conda, and is able to produce environment files that conda can use to install the exact same project environment. To install this project using conda rather than pixi:
pixi project export conda-environment environment.yml
conda env create -n new-env-name -f environment.yml
Run the scripts as usual as python src/<file>.py
, or in some cases pixi tasks are
available: pixi run script1
.
Some issues may arise when running this code.
-
Path to the GPU libraries
The default path used to look for libraries is not necessarily the correct one, and can be overridden with the
LD_LIBRARY_PATH
environment variable. When using pixi, this is set in the tasks in the pyproject.toml file. See the fpp-analysis-tools README for how to find your path. -
Plotting on a remote server
The scripts in this repo do some plotting, and its nice to be able to view them interactively, not just save the image files and inspect those. This need an
ssh
connection that uses the-X
flag (ssh -X user@servername
) or that it is set in thessh
configuration at$HOME/.ssh.config
:Host somecustomname ForwardX11 yes ForwardX11Timeout 0 Hostname 1.2.3.4 User user
Note that there might be a timeout on the X11 forwarding, so setting this to zero (no timeout) in the configuration is the simplest solution.
Further, the
DISPLAY
environment variable must be set once you are logged into the server. Try firstecho "$DISPLAY"
, and if it is empty doexport DISPLAY=localhost:10.0
. In this repo, this value is set in the .mise.toml file, but this depend on having mise installed to work.