About

This repository contains the public portions of the analysis software developed by the SPT-3G collaboration. It includes the IO libraries, data acquisition code for McGill’s DfMux readout boards, pipeline glue code, a binned map-maker, and a sky mock-observer, as well as defining all the APIs used by the project. For more detail on the intended processing architecture, please see the Quick Start chapter of the documentation.

Except where otherwise noted, all files are distributed under the 2-clause BSD license. Acknowledgments and patches are appreciated.

Documentation

The main documentation for the software is in the docs folder. After building the software, you can build a pretty, searchable copy by running make docs.

Dependencies

This depends on pybind11 and cmake, as well as the usual Python packages. Some additional packages (NetCDF, in particular) will activate optional components of the code if installed. You also need a C++11 compiler. This software is designed to run and work on a variety of operating systems (all Linuxes, Mac OS X, and FreeBSD) and architectures (at least 64-bit x86 and POWER).

Minimum versions:

• GCC >= 5.0 or clang >= 3.4

• pybind11 >= 2.13

• cmake >= 3.12

• Python >= 3.7 (although pre-Python-3.8 support is best-effort)

On Ubuntu/Debian, you can install the non-Python dependencies, including the optional ones, by doing:

apt-get install cmake libz-dev libbz2-dev liblzma-dev libflac-dev libnetcdf-dev

On RHEL-type systems (SL, CentOS, etc.), do this:

yum install cmake netcdf-devel zlib-devel bz2-devel xz-devel flac-devel

If your system defaults to Python 2, but you wish to use Python 3, please do the following:

1. Install Python 3 from the system package manager

2. When you run cmake below, pass -DPython_EXECUTABLE=`which python3`

On any system, this software requires numpy and scipy (hard requirements), plus astropy and healpy (optional).

Setup on RHEL Systems with OASIS

If using RHEL8 or RHEL9 and you have OASIS set up on your local system, run this before anything else:

eval `/cvmfs/spt.opensciencegrid.org/py3-v5/setup.sh`

This will add a relatively new compiler and all necessary development packages (FLAC, GSL, etc) for compiling this software.

How to Build

To build:

cd spt3g_software
mkdir build
cd build
cmake ..
make

This will collect all of the necessary python tools into the build/spt3g directory, which can then be imported in python. To set the appropriate python environment without installing the python package, use the shell script in build/env_shell.sh to run commands that know where to find the spt3g package and libraries:

./env-shell.sh python my_script.py  # to run a python script
./env-shell.sh ipython  # to start an ipython session

Alternatively, for users that only use a single build environment, set the following environment variables (e.g. in your .bash_profile file):

export SPT3G_SOFTWARE_BUILD_PATH=path/to/spt3g_software/build
export PYTHONPATH=$SPT3G_SOFTWARE_BUILD_PATH:$PYTHONPATH
export LD_LIBRARY_PATH=$SPT3G_SOFTWARE_BUILD_PATH/lib:$LD_LIBRARY_PATH
export PATH=$SPT3G_SOFTWARE_BUILD_PATH/bin:$PATH

cd spt3g_software
pip install -r doc/requirements.txt

make docs

Installation

For various reasons it may be useful to install the software after building, instead of continuing to use it out of the build directory. Several CMake variables control how the software is installed:

• WITH_GZIP, which defaults to TRUE, is used to control whether the core library is built with support for gzip compression of G3 files. Use -DWITH_GZIP=FALSE when calling cmake to disable.

• WITH_BZIP2, which defaults to TRUE, is used to control whether the core library is built with support for bzip2 compression of G3 files. Use -DWITH_BZIP2=FALSE when calling cmake to disable.

• WITH_LZMA, which defaults to TRUE, is used to control whether the core library is built with support for lzma compression of G3 files. Use -DWITH_LZMA=FALSE when calling cmake to disable.

• CMAKE_INSTALL_PREFIX, which defaults to /usr/local is used as the root directory for installing all non-python components (header files, cmake export scripts, etc.). This variable is frequently useful when installing into a python virtual environment.

• CMAKE_BUILD_PARALLEL_LEVEL is an environment variable (not a cmake option) used to control how many parallel processes are used to compile the shared libraries. This option provides the same behavior as running make with the -j flag (e.g. make -j4).

An uninstall target is also provided, so running make uninstall from the build directory should remove all files created by a previous make install.

Installation with Pip

Use pip to install the python package. Ensure that you use the appropriate options as necessary for your installation, e.g. --user or --prefix.

For pre-built wheels hosted on PyPI, available for most Linux x86_64, macOS x86_64 and macOS arm64 platforms, simply install the package without any additional options:

pip install spt3g

The hosted wheels will include the necessary libraries (flac, etc) bundled with the package. Otherwise, ensure that the dependency libraries are installed as explained above, and processed to one of the following steps.

To install the package from the github repo, run pip as usual (this may take a while, so consider setting the CMAKE_BUILD_PARALLEL_LEVEL environment variable):

cd spt3g_software
CMAKE_BUILD_PARALLEL_LEVEL=4 pip install -v .

By default this will create a directory called build in the repo and run the cmake build from there. The build directory location can be changed by setting the BUILD_DIR environment variable, but keep in mind that pip requires that the build directory must be a path inside the repo file tree. For development builds, use the --editable option to assemble the python package from the appropriate compiled extensions and python directories:

cd spt3g_software
CMAKE_BUILD_PARALLEL_LEVEL=4 BUILD_DIR=build pip install -v --editable .

An editable build adds references to the python directories to your python path, so that edits to library python files are immediately reflected in a fresh python session.

To pass arguments to the cmake build system, use the CMAKE_ARGS environment variable with arguments separated by spaces. For example:

cd spt3g_software
CMAKE_ARGS="-DCMAKE_INSTALL_PREFIX=/usr/local -DCMAKE_MODULE_PATH=/usr/local/share/cmake" pip install -v --prefix=/usr/local .

To run the test suite on the compiled package, you must have cmake, and in particular the ctest utility, available on your path. You must also know the location of the build directory where the cmake build was assembled (e.g. the value of $BUILD_DIR above).

ctest --test-dir path/to/spt3g_software/build --output-on-failure

Release Version Tracking

Use git tags to keep track of release versions. Tags should be of the form “v0.1.2” for release with major version 0, minor version 1 and patch version 2. If such a tag is defined, cmake will populate the following outputs:

• A cmake/Spt3gConfigVersion.cmake file that contains the version number to be checked when including the Spt3g libraries in another cmake project

• A spt3g/version.py file containing VCS parameters for access in python and stored in PipelineInfo frames

• Add a SPT3G_VERSION compiler definition for accessing the version string in C++ code

Use the git archive command or the Python build package to export the source tree to a standalone archive.

Version Control Hygiene

The following is a brief overview of how to use git in a way that your collaborators will appreciate.

To initially check out the repository:

git clone https://user@github.com/CMB-S4/spt3g_software.git

To update your checkout (the –rebase is important, especially if you have local changes):

git pull --rebase

To send your changes back:

git diff files_to_commit <- Examine this
git commit files_to_commit
git push