Glimpse is a sparsity based mass-mapping algorithm. See the Glimpse page on the CosmoStat website for more information.

Note, the Glimpse version corresponding to (Lanusse et al. 2016) is v1.0

Glimpse depends on the following software:

• Armadillo
• Boost
• FFTW version 3.3 or later
• NFFT version 3.2 or later
• cfitsio and CCFits
• GSL
• CMake version 2.8 or later

These dependencies can easily be installed using a package manager:

• Setting up requirements on Linux: Simply use the package manager provided by your Linux distribution, for instance on Ubuntu Linux:

    $ sudo apt-get install cmake libgsl0-dev libfftw3-3  libccfits-dev libnfft3-dev libarmadillo-dev libboost-all-dev
  

• Setting up requirements on MacOS X: The preferred installation method for the dependencies is through Homebrew:

    $ brew tap brewsci/science
    $ brew install libomp cmake nfft gsl fftw ccfits armadillo boost
  

  Note that when using brew to install dependencies, compiling with gcc is not supported, please use the default AppleClang instead.

Once the requirements are installed, Glimpse can be compiled by running the following commands:

  $ cd Glimpse
  $ mkdir build
  $ cd build
  $ cmake ..
  $ make

This will create a Glimpse executable in the build directory.

Glimpse expects input shear and/or flexion data as columns in a FITS file. A simple python script for converting .txt files to FITS is provided in the utils folder.

All the options of the reconstruction algorithm can be specified in a config.ini file such as the one provided in the example directory.

Glimpse can be run with the following command line:

  $ glimpse config.ini cat_3_0.fits kappa.fits

Where kappa.fits is the reconstructed convergence map (scaled for sources at infinite redshift) and cat_3_0.fits is the input data file.

Glimpse can be used to recontruct a 3D field using the same command line:

  $ glimpse config3d.ini cat_3_0.fits delta.fits

An example of config3d.ini can be found in the example directory.

Reconstructing a 3D field is very computationally demanding, and using a GPU is higly recommended to speed up the reconstruction. If an installation of CUDA can be detected on your system, CMake will automatically compile GPU specific code to replace the CPU implementation.

Glimpse uses peer-to-peer memory transfer between GPUs on a multi-gpu system. You may choose at runtime which GPUs to use in your system by providing the -g option:

  $ glimpse -g 1,2 config3d.ini cat_3_0.fits delta.fits

This option will use only GPUs 1 and 2 even if more are installed on the system. To get a list of CUDA capable devices on your system, use the deviceQuery command provided with CUDA.