This directory contains a Dockerfile to generate a fully configured SeisComP3 installation using a setup similar to the real-time system operated by the Swiss Seismological Service. To generate the docker image using the Dockerfile run:
docker build -t seiscomp3-ch .
The resulting image has two mount points, one for the directory containing the playback scripts and one for the waveform data and the database for the playback. The directory data contains a test database file with a SeisComP3 configuration, inventory, and a multiplexed MiniSEED file for one event.
Assuming that the playback script is in the directory
${HOME}/sc3-playback and the playback data is under ${PWD}/data you can
start the container as follows:
docker run -d --name sc3-ch -p 9999:22 -v ${PWD}/data:/home/sysop/data -v ${HOME}/sc3-playback/:/home/sysop/sc3-playback seiscomp3-ch
This will also start an ssh server that you can connect to with (password the same as the user name):
ssh -p 9999 sysop@localhost
First get a shell in your container by running:
docker exec -it --user sysop seiscomp3-ch /bin/bash
Once you have a shell in your container and assuming your waveform file is
called test-event.sorted-mseed and your sqlite3 database test.db you can
start a playback as follows:
cd sc3-playback
./playback.py ../data/test.db ../data/test-event.sorted-mseed
You can then use scolv to analyse the results from the playback. Note that you
have to start scolv on your host machine as no guis are installed in the
container.
scolv --offline --plugins dbsqlite3 -d sqlite3://${PWD}/data/test.db
By default the user sysop inside the container has USER_ID=1000 and
GROUP_ID=1000. If this doesn't match with the permissions of the playback
files on your host machine add the following options to your docker run
command:
-e USER_ID=`id -u` -e GROUP_ID=`id -g`