Installation & Setup¶

FastSpecFit is simple to install and has a relatively small number of standard dependencies. Here, we describe three different ways of setting up FastSpecFit:

at NERSC (for DESI collaborators);

on a laptop; or

using the Docker container.

1. NERSC Installation¶

At NERSC, FastSpecFit can be loaded trivially on top of the standard DESI software stack. In a login or interactive Perlmutter node, run the following commands to load a stable version of FastSpecFit and its dependencies:

source /global/cfs/cdirs/desi/software/desi_environment.sh 23.1
module swap desispec/0.59.2
module load fastspecfit/2.4.0

Alternatively, the following commands will load the development version of FastSpecFit, which is updated nightly and not guaranteed to be stable:

source /global/cfs/cdirs/desi/software/desi_environment.sh main
module load fastspecfit/main

Finally, some users may want to access FastSpecFit through NERSC’s JupyterHub notebook server. To set up the kernel first do:

mkdir -p ${HOME}/.local/share/jupyter/kernels/fastspecfit
wget -O ${HOME}/.local/share/jupyter/kernels/fastspecfit/kernel.json \
  https://raw.githubusercontent.com/desihub/fastspecfit/main/etc/jupyter-kernel.json

Then, in JupyterHub, simply select the FastSpecFit kernel and you are all set!

2. Laptop Installation¶

To install FastSpecFit and all its dependencies on a laptop we recommend a dedicated Miniforge environment. For example, to install the latest stable version transparently into an environment called, e.g., fastspec one would do:

conda create -y --name fastspec python=3.10
conda activate fastspec
pip install fastspecfit

Note that if you are planning to write documentation you will also need to install the following dependencies:

pip install sphinx sphinx-toolbox sphinx-rtd-theme sphinxcontrib-napoleon

Alternatively, some users may want FastSpecFit and its dependencies to be installed in a more accessible location (e.g., /path/to/desi/code), in which case one would do:

conda create -y --name fastspec python=3.10 numpy scipy numba astropy matplotlib seaborn
conda activate fastspec
pip install fitsio healpy speclite

export DESI_CODE=/path/to/desi/code
mkdir -p $DESI_CODE

pushd $DESI_CODE
for package in desiutil desimodel desitarget desispec fastspecfit; do
  git clone https://github.com/desihub/$package.git
  export PATH=$DESI_CODE/$package/bin:$PATH
  export PYTHONPATH=$DESI_CODE/$package/py:$PYTHONPATH
done
popd

Finally, FastSpecFit has four more data dependencies, each specified with their own environment variable:

DESI_ROOT, which specifies the top-level location of the DESI data;

DUST_DIR, which specifies the location of the Schlegel, Finkbeiner, & Davis dust maps;

DR9_DIR, which specifies the location of the DESI Legacy Imaging Surveys Data Release 9 (DR9) data; and

FTEMPLATES_DIR, which indicates the location of the stellar population synthesis models used by FastSpecFit.

Note

Currently, the DESI data are only available to DESI collaborators; however, the Early Data Release (EDR) is expected to be publicly available in Spring 2023 and other data releases will be announced in the DESI Data Release page, after which point the instructions here will be updated.

With the preceding caveat in mind, one can set up the remaining dependencies with the following commands:

export DESI_ROOT=/path/to/desi/data
export DUST_DIR=/path/to/dustmaps
export DR9_DIR=/path/to/dr9/data
export FTEMPLATES_DIR=/path/to/templates/fastspecfit

wget -r -np -nH --cut-dirs 5 -A fits -P $DUST_DIR \
  https://portal.nersc.gov/project/cosmo/data/dust/v0_1/maps
wget -O $FTEMPLATES_DIR/ftemplates-chabrier-1.0.0.fits \
  https://data.desi.lbl.gov/public/external/templates/fastspecfit/1.0.0/ftemplates-chabrier-1.0.0.fits

3. Using Docker¶

Finally, for production runs and for expert users, FastSpecFit is also available as a Docker container which is served publicly in the DockerHub/desihub repository.

For example, on a laptop one would retrieve (or update) and enter the 2.1.1 version of the container with:

docker pull desihub/fastspecfit:2.1.1
docker run -it desihub/fastspecfit:2.1.1

Alternatively, at NERSC one would need to use shifter:

shifterimg pull docker:desihub/fastspecfit:2.1.1
shifter --image docker:desihub/fastspecfit:2.1.1 bash

However, neither of the preceding commands define the required environment variables, although we provide a simple setup script which does. For simple interactive work at NERSC (e.g., in a login node) do:

mkdir -p /path/to/fastspecfit/setup/script
wget https://raw.githubusercontent.com/desihub/fastspecfit/main/bin/fastspecfit-setup.sh \
  -O /path/to/fastspecfit/setup/script/fastspecfit-setup.sh

/path/to/fastspecfit/setup/script/fastspecfit-setup.sh shifter
source /path/to/fastspecfit/setup/script/fastspecfit-setup.sh env

Note

To run FastSpecFit on a large sample of objects (or for a full production or data release), please do not use a login node; instead, see the Running FastSpecFit documentation for instructions and best practices.