pixell

https://github.com/simonsobs/pixell/workflows/Build/badge.svg https://readthedocs.org/projects/pixell/badge/?version=latest https://codecov.io/gh/simonsobs/pixell/branch/master/graph/badge.svg?token=DOIG32B6NT https://badge.fury.io/py/pixell.svg

pixell is a library for loading, manipulating and analyzing maps stored in rectangular pixelization. It is mainly targeted for use with maps of the sky (e.g. CMB intensity and polarization maps, stacks of 21 cm intensity maps, binned galaxy positions or shear) in cylindrical projection, but its core functionality is more general. It extends numpy’s ndarray to an ndmap class that associates a World Coordinate System (WCS) with a numpy array. It includes tools for Fourier transforms (through numpy or pyfft) and spherical harmonic transforms (through ducc0) of such maps and tools for visualization (through the Python Image Library).

Dependencies

  • Python>=3.7

  • gcc/gfortran or Intel compilers (clang might not work out of the box), if compiling from source

  • ducc0, healpy, Cython, astropy, numpy, scipy, matplotlib, pyyaml, h5py, Pillow (Python Image Library)

On MacOS, and other systems with non-traditional environments, you should specify the following standard environment variables:

  • CC: C compiler (example: gcc)

  • CXX: C++ compiler (example: g++)

  • FC: Fortran compiler (example: gfortran)

We recommend using gcc installed from Homebrew to access these compilers on MacOS, and you should make sure to point e.g. $CC to the full path of your gcc installation, as the gcc name usually points to the Apple clang install by default.

Runtime threading behaviour

Certain parts of pixell are parallelized using OpenMP, with the underlying ducc0 library using pthreads. By default, these libraries use the number of cores on your system to determine the number of threads to use. If you wish to override this behaviour, you can use two environment variables:

  • OMP_NUM_THREADS will set both the number of pixell threads and ducc0 threads.

  • DUCC0_NUM_THREADS will set the number of threads for the ducc0 library to use, overwriting OMP_NUM_THREADS if both are set. pixell behaviour is not affected.

If you are using a modern chip (e.g. Apple M series chips, Intel 12th Gen or newer) that have both efficiency and performance cores, you may wish to set OMP_NUM_THREADS to the number of performance cores in your system. This will ensure that the efficiency cores are not used for the parallelized parts of pixell and ducc0.

Installing

Make sure your pip tool is up-to-date. To install pixell, run:

$ pip install pixell --user
$ test-pixell

This will install a pre-compiled binary suitable for your system (only Linux and Mac OS X with Python>=3.7 are supported). Note that you need ~/.local/bin to be in your PATH for the latter test-pixell to work.

If you require more control over your installation, e.g. using Intel compilers, please see the section below on compiling from source. The test-pixell command will run a suite of unit tests.

Compiling from source (advanced / development workflow)

For compilation instructions specific to NERSC/cori, see NERSC.

For all other, below are general instructions.

First, download the source distribution or git clone this repository. You can work from master or checkout one of the released version tags (see the Releases section on Github). Then change into the cloned/source directory.

Run setup.py

If not using Intel compilers (see below), build the package using

$ python setup.py build_ext -i

You may now test the installation:

$ py.test pixell/tests/

If the tests pass, you can install the package (optionally with -e if you would like to edit the files after installation)

$ python setup.py install --user

Intel compilers

Intel compilers require you to modify the build step above as follows

$ python setup.py build_ext -i --fcompiler=intelem --compiler=intelem

On some systems, further specification might be required (make sure to get a fresh copy of the repository before trying out a new install method), e.g.:

$ LDSHARED="icc -shared" LD=icc LINKCC=icc CC=icc python setup.py build_ext -i --fcompiler=intelem --compiler=intelem

Contributions

If you have write access to this repository, please:

  1. create a new branch

  2. push your changes to that branch

  3. merge or rebase to get in sync with master

  4. submit a pull request on github

If you do not have write access, create a fork of this repository and proceed as described above. For more details, see Contributing.