Installing ANTARESS#

Latest stable release#

ANTARESS is available on the PyPI repository. You can install the latest version available with:

pip install antaress

Current version#

ANTARESS is hosted on gitlab. To download the repository containing the current version, you can use:

git clone https://gitlab.unige.ch/spice_dune/antaress.git

This version is being developed and may not be stable.

The pipeline runs on Mac, Linux, and Windows (pySME is however not available on the latter).

Manual installation#

If you intend to develop or get the latest (unreleased) developments, get the current version as described above, move in the downloaded directory, and install ANTARESS with:

pip install -e .

If you want to test updates to the documentation as well, you will need to install the packages sphinx, myst-nb, and sphinx-book-theme with pip. You can then generate the documentation by moving to the /Docs folder and executing:

./Make_doc

The documentation will be generated in the /Docs/build/html/ folder, and can be checked by opening the index.html file.

Secondary packages#

A number of packages are required to run ANTARESS. They should be installed automatically, but if you encounter some trouble you can install them manually as described below.

  • Standard packages

    Install arviz, astropy, batman-package, dace_query, emcee, dynesty, lmfit, pandas, pathos, PyAstronomy, scipy, statsmodels using:

    pip install package
    
  • Resampling package
    • bindensity documentation

    • install as a standard package:

      pip install bindensity
      
    • do not use bindensity with non-continuous grids, as it will mess up with banded covariance matrices.

    • beware when masking spectral ranges with ANTARESS, as undefined pixels (set to nan values) are propagated by bindensity when resampling and will spread throughout the workflow.

  • Package pySME
    • follow these instructions to install PySME on M1/M2 Macs.
      • install rosetta by running:

        softwareupdate --install-rosetta
        
      • install Homebrew under rosetta by running:

        $ arch -x86_64 /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
        

        This installs Homebrew under /usr/local/bin/brew instead of the default for arm64 /opt/homebrew/bin/brew

      • install gcc@9 by running:

        $ arch -x86_64 /usr/local/bin/brew install gcc@9
        
      • create a Conda environment to run under the intel x64_86 architecture and install PySME in this environment:

        CONDA_SUBDIR=osx-64 conda create -n envname python=3.11
        

        then:

        pip install pysme-astro
        
    • follow these instructions to install PySME on older Macs
      • install gcc9 by running:

        brew install gcc@9
        
      • then PySME by running:

        pip install pysme-astro
        
  • Package KitCat
    • install gsl by running:

      brew install gsl
      
    • set up the path to your local python installation in the setup_lbl_fit.py and run:

      python setup_lbl_fit.py build
      

      Then copy the compiled file calculate_RV_line_by_line3.cpython-XX-darwin.so into your KitCat/ directory.