An Rserve-based server of data from files for the epiviz visualization tool.
See the wiki for more information
devtools::install_github("epiviz/epivizFileServer")
To start the Rserve backend run after installation (e.g.)
Rscript -e "epivizFileServer::startBackend()" --args metadata.yml
See wiki for information on the metadata.yml argument.
To start the python tornado frontend run
python `Rscript -e "epivizFileServer::frontendPath()"`
This requires python with tornado installed.
Start epiviz with websocket connection to tornado front end at http://epiviz.cbcb.umd.edu/?websocket-host[]=ws://localhost:8888/ws&settings=default&
This package defines a Docker image that may be used to run an instance of the file server. It is registered in DockerHub. You can run the server with data included in the package by using
docker run -d -p 8888:8888 epiviz/file_server
After the container starts running, you can run the epiviz app against the docker container:
http://epiviz.cbcb.umd.edu/?websocket-host[]=ws://192.168.99.100:8888/ws&settings=default&
You should use the result of docker-machine ip <machine> to get the fileserve address.
To use your own data with this container, there are a few options.
- Mount data from host machine into default directory used in container
# have to use absolute path
HOST_VOLUME=${PWD}/datadir
# assumes directory has a metadata.yml file
docker run -d -p 8888:8888 -v ${HOST_VOLUME}:/epivizfs_data epiviz/file_server
- Mount data from host machine into a different volume used in container
# have to use absolute paths
HOST_VOLUME=${PWD}/datadir
VM_VOLUME=/epivizfs_mydata
METADATA_FILE=metadata.yml
# environment variable overrides defaults
docker run -d -p 8888:8888 -v ${HOST_VOLUME}:${VM_VOLUME} -e "EPIVIZFS_BACKEND_PATH=${VM_VOLUME}/${METADATA_FILE}" epiviz/file_server
- Use a Dockerfile and copy data to container
All of these can be used in a new Dockerfile as well:
FROM epiviz/file_server
COPY ./datadir /epivizfs_data
docker build -t my_epivizfs .
docker run -d -p 8888:8888 my_epivizfs