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N.B. Before starting to use brainmapper on the SWC, you should familiarise yourself with the job scheduler system (SLURM).
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This information refers to using brainmapper for cell detection and registration, but any of the BrainGlobe command-line tools (e.g. training brainmapper, or running only registration with brainreg) can be used similarly.
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Interactive use
On the SWC cluster, no software needs to be installed, as brainmapper can be loaded with module load brainglobe.
brainmapper can be used interactively, by starting an interactive job:
And then running brainmapper as per the User guide.
Batch processing
It is recommended to use brainmapper by using the batch submission system.
This has many advantages:
Your analysis is reproducible: you have a script showing exactly what you did.
You don't need to wait for computing resources to become available: once submitted, the job will wait until it can be run.
If for any reason the analysis is interrupted, you can easily restart.
You don't need to keep a connection to the cluster open.
You can easily receive email updates when the job starts and finishes.
An example batch script is given below, but it is recommended to familiarise yourself with the batch submission system before trying to optimise brainmapper.
#!/bin/bash#SBATCH -p gpu # partition (queue)#SBATCH -N 1 # number of nodes#SBATCH --mem 120G # memory pool for all cores#SBATCH --gres=gpu:1#SBATCH -n 10#SBATCH -t 1-0:0 # time (D-HH:MM)#SBATCH -o brainmapper.out#SBATCH -e brainmapper.err#SBATCH --mail-type=ALL#SBATCH [email protected]
cell_file='/path/to/signal/channel'
background_file='path/to/background/channel'
output_dir='/path/to/output/directory'echo"Loading brainglobe environment"
module load brainglobe
echo"Running brainmapper"# Just an example. See the user guide for the specific parameters
brainmapper -s $cell_file -b $background_file -o $output_dir -v 5 2 2 --orientation psl
Linked to brainglobe/brainglobe.github.io#130
The HPC module will also need to be updated to BG v1 too.
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