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Note: If you have trouble during installation, is a Stack Overflow-like forum for all things LSST.  We are doing our best to answer all of the questions posted there as helpfully as possible.  You might consider searching for your bug or, if you have discovered a new one, creating a post there so that others can benefit from your experience.

Stack requirements:

There are some general LSST software stack requirements before installation: please check that your system has these the pre-requisites installed installed.

There are some additional requirements for the simulations packages, mostly python dependencies that are so ubiquitous in scientific computing environments that it is more difficult for users for us to provide new versions than it is to supply them with the stack. These requirements are (there is some overlap here with the basic stack requirements):


  • python 23.7
  • numpy
  • scipy
  • astropy
  • matplotlib
  • sqlalchemy
  • Cython (note: even if using the stack-supplied Anaconda distribution, you should run conda install cython to install the Sims stack)
  • cmake


  • 6
  • cmake - available from conda if required
  • gfortran (which is necessary to build the ephemeris-generating software package oorb – this is ONLY needed if you are installing sims_movingObjects in addition to lsst_sims)  

Installing from Source


The recommended (simplest) approach is to use the newest LSST software stack, and use the LSST-provided version miniconda python. (See here if you want to use your own python). 


In these instructions we assume you are installing in ~/lsst, however the install directory can be any place in the file system, including a place visible to all users.  To install in another location, replace ~/lsst with the desired path in the following instructions.  For multi user stacks, permissions are typically restricted to read only for the main stack so packages are not accidentally installed in the main stack.

For the basic install of lsst_apps, please follow the directions installation of the basic LSST packages, please check for additional requirements or known problems here:  and then from there, install lsst_sims following the directions below.follow a similar process to start the installation of the LSST build system. 

Note: In the past we have warned you against running with the `-t` flag, which enables installation of the DM binary builds.  That is no longer a concern.  `lsst_sims` will build against DM binaries.  Feel free to run with `-t` enabled.

Code Block
cd ~/lsst
curl -OL
bash -ct

You do not need to do "eups distrib install lsst_distrib", as described on the pipelines page, as we will install the required simulations packages below.  

Note that the pages go on to describe LSST Data Management packages (lsst_apps and lsst_distrib) that include additional software not necessary for simulations (although it may be very useful for you!). This includes the LSST data management demo package. You may find it interesting for image processing and catalog purposes, but it is not directly related to installation and use of the simulations packages.

 2. Set up the environment and install the simulations code and data.


Code Block
source ~/lsst/loadLSST.csh

eups distrib install lsst_sims -t sims_weekly_tag
curl -sSL | python

This will install all packages currently in the catalogs simulations framework (CatSim) and metrics analysis framework (MAF) and all dependencies.  The installation should take on the order of 2 hours1 hour, with a final required installation size of 10GB. 

Currently the complete list of installed packages is:

  • base – LSST import utilities
  • boost– Third party C++ package
  • cfitsio– FITSIO I/O library
  • daf_base – LSST data access framework 
  • doxygen– Documentation suite
  • freetds– OpenSource implementation for Tabular Data Streams (needed by pymssql)
  • healpy– Python bindings for HealPix 
  • palpy– Python binidings for PAL (Positional Astronomy Library)
  • pex_config – LSST configuration package
  • pex_exceptions – LSST exception handling package.
  • pex_policy – Another LSST configuration package
  • pyephem– Ephemeris generation code
  • pyfits– Python bindings for interacting with FITS files
  • pykg_config– Pure python implementation of pkg_config needed to install healpy on Mac OSX
  • pymssql– Python bindings for talking to MS-SqlServer databases (needed to access UW base catalogs)
  • scons– Software construction  tool
  • sconsUtils – LSST utilities for scons
  • sims_catalogs_generation – Code for querying databases for catalog data
  • sims_catalogs_measures – Code for constructing observed catalogs 
  • sims_catUtils – Package containing example code and definitions of base catalogs hosted at UW.
  • sims_photUtils – Utilities for calculating photometry including variability
  • sims_coordUtils – Utilities for calculating coordinate corrections (proper motion, parallax, refraction, etc.)
  • sims_dustmaps – SFD dust maps
  • sims_maf – Metrics Analysis Framework
  • sims_sed_library – Library of SED data for simulated catalogs
  • swig– Library for auto-generating python bindings for C++ code
  • throughputs – Nominal throughput curves for SDSS and LSST systems
  • utils – LSST utilities package

Any of the above    Note that sims_weekly_tag will change depending on which weekly you want to install.  Sims weekly tags are of the form sims_w_YYYY_WW.  There is no good place to find what weekly has been most recently published, unfortunately.  If you look at the release tab on the lsst/afw repository you should see what the latest release is.  If, for example, the latest release is w.2019.14, then sims_weekly_tag will be sims_w_2019_14.

The `shebangtron` command is there to correct the paths to installed binaries of Data Management software packages.  Every time you install new binary packages, you will need to run the `shebangtron` command.

Any of the individual packages and all their dependencies can be installed by replacing lsst_sims with the appropriate package name in the above code snippet (e.g. sims_maf).  Installation is now complete.  See package specific pages for documentation.


You have now downloaded and built all of the packages in lsst_sims, with the command "eups distrib install <packagename> -t <tag>".  These packages are designed to be totally self-contained.  They have been built in the directories


where yourOperatingSystem is 'DarwinX86' for Mac users and 'Linux64' for Linux users.  In order to use the packages you installed, you must add 'activate' them in your environment, which is essentially adding these directories to your $PYTHONPATH.  This is done using

Code Block
setup your_package_name -t your_package_tag

"setup <packagename> -t <tag>" is an eups command that activates the packages and their dependencies.  your_package_name is the name of one of the packages you have installed (e.g. sims_maf or sims_catUtils).  your_package_tag is a tag eups uses to keep track of the versions of each package you have built on your machine.  This corresponds to the argument of '-t' in the 'eups distrib install' command above.  So, if you wanted to setup the version of MAF you just downloaded, you would use

Code Block
setup sims_maf -t sims_weekly_tag

When you setup a package, eups inspects it and determines what other packages it depends on.  Eups will also setup those prerequisite packages, preferring versions tagged with the tag you specified and defaulting to versions with the tag 'current'.  If you do not want to default to 'current', you can specify more than one tag.

Code Block
setup sims_maf -t $USER -t sims_weekly_tag

will setup sims_maf and all of its dependencies, and then using versions matching the tags (resolved from left to right).  This system of eups tags allows you to have multiple versions of the stack built on your system simultaneously.  You will only ever be using the one that eups has setup.  To see which versions of a package exist on your system (and which has been setup) use



Code Block
eups list -s



WARNING: as of July 2016, the conda binary installation is no longer supported.  We strongly recommend that, if at all possible, you use the "install from source" instructions above.  Installing the conda binary will give you a very out-of-date LSST Simulations stack.  We are working on a new framework for distributing binary installations and will post to the sims-announce category at when that is available.

These installation instructions are very similar to those on the page, but note that we point to a different conda channel. 

1) Install the Anaconda Scientific Python Distribution (or the stripped-down Miniconda, for a quicker install).  

1a) If you didn't just install anaconda or miniconda, or even if you did:

Code Block
conda update conda

2) Add the LSST simulations software channel (note that this is DIFFERENT than the standard 'DM stack' channel! This is because of versioning issues between DM and Sims and is related to simulations having a more frequent release schedule. You can also get an older version of sims from the 'stack' channel). 

Current version of simulations from the sims conda channel is: sims_2.2.6, built against DM lsst_apps v12.0. The version of sims available on the stack channel is v12.0 (equivalent to sims_2.2.5), built against DM lsst_apps v12.0. 

Code Block
conda config --add channels

Note: if you have installed sims conda binaries in the past, you may have an '' channel in your ~/.condarc file. This channel no longer exists and should be removed from your ~/.condarc file. 

3) Install the desired sims and apps packages

Code Block
conda install lsst-apps
conda install lsst-sims

or just a single package .. (e.g. for just MAF)

Code Block
conda install lsst-sims-maf

Then, every time you open a new shell, you can setup the sims packages using the following code. Note that the file `` is in `$ROOT/bin` where `$ROOT` is the conda environment that you installed into or if you did not specifically setup an environment (following the above method) it points to the conda installation. However, the location of the file does not matter, as the `ROOT/bin` directory should be in your path if you are using conda, and then you can launch the following commands from any working directory.

Code Block
setup lsst_sims (or setup sims_maf)

to later update use

Code Block
conda update lsst-sims

Known issues: 

  • If you have issues with installation, first check that your system meets the minimum requirements listed here:, including having git-lfs set up. Note that you need cmake – if installation of 'mariadb' fails, you probably do not have cmake installed ('conda install cmake' is an easy way to get it).
  • Check for other known issues here: 
  • You can also search for similar problems on 
  • If you are having issues specifically with pyephem or healpy on a Mac, check for the existence of a /Developer directory. This directory is obsolete after upgrading to newer versions of XCode, but not removed by the XCode installer. Rename the /Developer directory and pyephem will install. 
  • If you are using your own python, be sure to check the Using Your Own Python page. In particular, on Linux, some lsst_apps packages will currently fail to build if the "nomkl" package is not installed in anaconda.
  • On a Mac, make sure you have accepted the terms on XCode.  You can do this by opening the (should be in your Applications folder).
  • git can fail, complaining about not having an https helper.  If your native git version is > 1.7, you can probably use that rather than the LSST installed git.
  • If all else fails, it's usually an issue with some environment variables interfering with the installation.  You can create a new user  and install the stack there.  You can quickly login/out of a new user account as follows:  First make a new admin-level user in System Preferences->Users and Groups, and then click on your name in the top right hand corner of the screen. A drop-down menu should appear, offering you a choice of other users to log in as. You might have to toggle the check box in System Preferences->Users and Groups->Login Options first though.


Code reviews should be handled by branching the repository and issuing a pull request through stashgithub.