[AstroPy] Projects involving irregularly shaped data

Wortmann, Peter P.Wortmann at skatelescope.org
Fri Oct 9 10:29:23 EDT 2020

Hi Jim

Another possible use case you might want to be aware of - for the Square 
Kilometre Array (https://www.skatelescope.org/) we are currently in the 
early stages of evaluating concrete technologies for dealing with data 
exchange within our pipelines. We are expecting heavy I/O workloads and 
want to evolve our software quite a bit over the lifetime of the 
observatory, so we are considering building around Apache Arrow (or 
similar) in-memory data structures.

While most of our "primary" data is likely regularly shaped, there will 
definitely be very significant amounts of "secondary" data - such as sky 
models, or complex calibration and flagging data at minimum. To us, 
Awkward sounds like a very good candidate for dealing with such data.

We will likely be building some prototypes over the next year to see how 
we could utilise Awkward in processing. I realise this is not quite what 
you were asking for, but might still be worthwhile to get in touch at 
some point?

   Peter Wortmann

(Data Processing Architect, Square Kilometre Array Organisation)

On 07/10/2020 20:59, Jim Pivarski wrote:
> Hi everyone,
> Adrian Price-Whelan recommended that I ask my question here, since it 
> would reach a greater number of people involved in astronomical software.
> I'm a developer of Awkward Array 
> <https://awkward-array.org/what-is-awkward.html>, a Python package for 
> manipulating large, irregularly shaped datasets: arrays with 
> variable-length lists, nested records, missing values, or mixed data 
> types. The interface is a strict generalization of NumPy: you can slice 
> jagged arrays as though they were ordinary multidimensional arrays, and 
> there are new functions that only make sense in the context of irregular 
> data. Like NumPy, the actual calculations are precompiled loops on 
> internally homogeneous arrays, and we're expanding it to include GPUs 
> transparently (irregular data on GPUs in a NumPy-like syntax).
> This package was developed for particle physics (variable numbers of 
> particles emerging from an array of collision events), but it seems like 
> these problems would exist in other fields as well. Right now, we're 
> working on a proposal to find data analysis projects that need to deal 
> with large, irregularly structured data to see if Awkward Array is 
> applicable and if it can be made more useful for them. Ideally, this 
> would motivate more interoperability with other scientific Python 
> libraries. (We can already use Awkward Arrays in Numba; we're working on 
> cuDF, Dask, and Zarr. Adrian also recommended ASDF, which I'm looking 
> into now.)
> Does anyone have or know about a data analysis project that is currently 
> limited by this combination of large + irregular data? Is anyone 
> interested in collaborating?
> Thank you!
> -- Jim
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