README.md

CosmoStat

Software developed at the CosmoStat lab at CEA Paris-Saclay.

Basic installation

The package can be installed with pip as follows.

python -m pip install .

Requirements

This package installs Sparse2D as a backend, which requires the follow dependencies.

• Armadillo
• BigMac (macOS only)
• CFITSIO
• CMake
• FFTW
• GSL
• HEALPix
• OpenMP
• Python

macOS Set Up

To install the package requirements on macOS, it is recommended to use Homebrew.

brew tap sfarrens/sf
brew install armadillo bigmac cfitsio fftw gsl healpix libomp

Docker installation

Pull the Docker image

If you have Docker installed, you can pull the latest build of the CosmoStat image as follows:

docker pull ghcr.io/cosmostat/cosmostat:master

No further installation is required.

Run a Docker container

To run a container on data in your current working directory, simply run:

docker run -v ${PWD}:/workdir --rm ghcr.io/cosmostat/cosmostat:master

The reference to ${PWD} can be replaced by the path to any directory on your system.

Additionally, you can run a Sparse2D executables dirextly from the image. For example, to run a bspline wavelet transform on a FITS image called myfile.fits you would run:

docker run -v ${PWD}:/workdir --rm ghcr.io/cosmostat/cosmostat:master mr_transform -t 2 myfile.fits myoutput.mr

Tip: If you don't want to constantly write the full Docker run command you can create an alias e.g.:

alias cosmostat="docker run -v ${PWD}:/workdir --rm ghcr.io/cosmostat/cosmostat:master"

then you can simply run e.g.:

cosmostat mr_transform -h

Launch a Jupyter notebook

You can also run a Jupyter notebook with a Docker container as the backend in order to use the cosmostat package.

docker run -p 8888:8888 -v ${PWD}:/workdir --rm ghcr.io/cosmostat/cosmostat:master notebook