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A Docker image has been created that contains all of the LSST pipeline software as well as the simulation software. It is available from the Docker repository as jamespepcc/lsstsimulations:1.12. Please see the Docker Introduction page for more information about using Docker containers.

To run the image:

docker run -ti jamespepcc/lsstsimulations:1.12

(You may need to include additional command line options if you wish to make use of shared folders, port forwarding, or other Docker features).

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For more information on how to find out what packages are available, install more packages, etc., please see the EUPS documentation. The current version of the container (v1.2) is based on the LSST pipeline software v14 and Python 3.6. An older version based on v13 and Python 2.7 is available as jamespepcc/lsstsimulations:1.1.

MAF Tutorial Notebooks

A set of iPython tutorial notebooks for the MAF software is available from GitHub. After running the Docker image (or installing the LSST simulation software some other way), clone:

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The tutorial notebooks are in the tutorials directory within this repository. Please see the /wiki/spaces/COL/pages/52161514 wiki page for information about how to launch Jupyter notebooks within DockerA few additional steps are required in order to successfully run Jupyter notebooks from within Docker:

• You must pass "-p 8888:8888" to docker run in order to make the port accessible from outside the container
• Before running notebooks you must set a password by running:
  • mkdir ~/.jupyter
  • jupyter notebook password
• When running jupyter notebook you must pass the "--ip 0.0.0.0" option on the command line to make the server bind to the correct network address
• You must determine the correct network address to access the Docker container from the host system. On Windows this is usually 192.168.99.100; on Mac OS X it is localhost; on Linux it can be determined using the docker ps and docker inspect commands. More details are given on the Docker Introduction page

You should then be able to access the notebooks by opening a web browser on your local system, navigating to the address determined above (port 8888), and entering the password you set earlier.

Many of the notebooks require SQLite databases in order to run. These can be downloaded from:

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