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Description:

hpmoc 1.0.0

hpmoc: HEALPix Multi-Order Coordinate Partial Skymaps
HPMOC is an ultra high-performance, cross-platform toolset for working with
multi-order coordinate (MOC) HEALPix_ images (i.e. images with multiple pixel
resolutions). MOC images are used by the LIGO-Virgo-KAGRA collaboration,
the Interplanerary Network and others to represent portions of
the sky with variable resolution. By only including pixels in regions of
interest, and only then at a resolution appropriate to how they were
observed/calculated, it is possible to reduce storage and computation costs by
several orders of magnitude.
HPMOC is the only library providing tools for loading partial/whole MOC
skymaps (as well as standard HEALPix skymaps), taking spatial intersections,
modifying resolution, plotting the skymaps, converting them to and from
Astropy WCS projections,
performing pointwise math, and generating PSF skymaps from point sources,
all using algorithms that minimize memory, computation, and storage costs.
It is based off of work on LLAMA, the world's first Gravitational
Wave/High-Energy Neutrino low-latency search pipeline, which has been improved
and refactored into this separate module.
If you use hpmoc in published research, we ask that you cite Stefan Countryman's thesis.
hpmoc is introduced in section 4.5.13.
hpmoc is licensed under the terms of the GNU General Public License, version 2 or later
Installation
hpmoc has only a few dependencies, but they are large numerical/scientific
libraries. You should therefore probably create a virtual environment of some
sort before installing. The easiest and best way to do this at the moment is to
use conda, which should come with an Anaconda distribution of Python:
conda create -n hpmoc
conda activate hpmoc

note that creating a new environment is optional and hpmoc can now be installed similar to any other python package.
With pip
If you just want to use hpmoc and don't need to modify the source code, you
can install using pip:
pip install hpmoc

This should install all required dependencies for you.
Developers
If you want to install from source (to try the latest, unreleased version, or
to make your own modifications, run tests, etc.), first clone the repository:
git clone https://github.com/markalab/hpmoc.git
cd hpmoc

Make sure the build tool, flit, is installed:
pip install flit

Then install an editable version of hpmoc with flit:
flit install --symlink

As with the pip installation method, this should install all requirements for
you. You should now be able to import hpmoc. Note that you'll need to quit
your python session (or restart the kernel in Jupyter) and reimport hpmoc
before your changes to the source code take effect (which is true for any
editable Python installation, FYI).
You can go ahead and run the tests with pytest (which should have been
installed automatically by flit):
py.test --doctest-modules --cov=hpmoc