Installation

3ML brings together multiple instrument and fitting software packages into a common framework. Thus, installing all the pieces can be a bit of a task for the user. In order to make this a less painless process, we have packaged most of the external dependencies into conda (see below). However, if you want more control over your install, 3ML is available on PyPI via pip. If you have issues with the installs, first check that you have properly installed all the external dependencies that you plan on using. Are their libraries accessible on you system’s standard paths? If you think that you have everything setup properly and the install does not work for you, please submit an issue and we will do our best to find a solution.

Conda installation (suggested)

Conda is a platform independent package manager. It allows to install 3ML (and a lot of other software) without the need to compile anything, and in a completely separate environment from your system and your system python.

If you don’t know Conda

If you are not familiar with conda, install 3ML with the automatic script which will take care of everything:

  1. Download the script from here

  2. Run the script with bash install_3ML.sh. If you plan to use XSPEC models use bash install_3ML.sh --with-xspec.

  3. The script will install 3ML and then create a threeML_init.sh script and a threeML_init.csh script. Source the former if you are using Bash (source threeML_init.sh) and the second one if you are using Csh/Tcsh (source threeML_init.csh).

If you already know Conda

If you are familiar with Conda and you already have it installed, you can install 3ML by creating an environment with:

conda create --name threeML -c conda-forge python=3.7 numpy scipy matplotlib

then activating your environment and installing 3ML as:

conda activate threeML
conda install -c conda-forge -c threeml astromodels threeml

Finally, if you also need XSPEC models you can install them by running:

conda install -c xspecmodels xspec-modelsonly

pip

If you would like to install 3ML and astromodels on their own and have more control over which dependencies you would like to use. Please to the following

  1. It is highly recommended you work within a python virtual environment to keep you base python clean

  2. install astromodels

pip install astromodels
  1. install 3ML

pip install threeml

If you need to build other dependencies such as pagmo, multinest, XSPEC, etc., it is recommended you do this before installing astromodels!

Other dependencies

You need to set up packages such as AERIE (for HAWC), or the Fermi Science Tools, before running the script, otherwise some of the functionalities will not work.

  • AERIE for HAWC: make sure that this works before running the script:

    > liff-PointSourceExpectation --version
    INFO [CommandLineConfigurator.cc, ParseCommandLine:137]:
    
     liff-PointSourceExpectation
     Aerie version: 2.04.00
     Build type: Debug
    

    If it doesn’t, you need to set up the HAWC environment (refer to the appropriate documentation)

  • Fermi Science Tools for Fermi/LAT analysis: make sure that this works:

    > gtirfs
    ...
    P8R2_TRANSIENT100_V6::EDISP0
    P8R2_TRANSIENT100_V6::EDISP1
    ...
    

    If it doesn’t, you need to configure and set up the Fermi Science Tools.

  • ROOT: ROOT is not required by 3ML, but it provides the Minuit2 minimizer which can be used in 3ML. If you have ROOT, make sure that this works before running the script:

    > root-config --version
    5.34/36
    

Install from source (advanced)

Remove any previous installation you might have with:

> pip uninstall threeML
> pip uninstall astromodels
> pip uninstall cthreeML

then:

> pip install numpy scipy ipython astropy numba cython
> pip install git+https://github.com/threeML/threeml.git
> pip install git+https://github.com/threeML/astromodels.git --upgrade

In order to use the HAWC plugin, you will also need to install cthreeML (run this after setting up the HAWC environment):

> pip install git+https://github.com/threeML/cthreeML.git
  • NOTE: If you do not have permission to install packages in your current python environment, you can still install the packages by adding the --user option at the end of each pip command.

Tips for Mac users

The following paths need to be added to you DYLD_LIBRARY path if you have FORTRAN installed via these package managers:

  • Homebrew: DYLD_LIBRARY_PATH=/usr/local/lib/gcc/<version number>:$DYLD_LIBRARY_PATH

  • Fink: DYLD_LIBRARY_PATH=/sw/lib/gcc<version number>/lib:$DYLD_LIBRARY_PATH

Please inform us if you have problems related to your FORTRAN distribution.