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Article overview
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Scipp: Scientific data handling with labeled multi-dimensional arrays for C++ and Python | | Simon Heybrock
; Owen Arnold
; Igor Gudich
; Daniel Nixon
; Neil Vaytet
; | | Date: |
1 Oct 2020 | | Abstract: | Scipp is heavily inspired by the Python library xarray. It enriches raw
NumPy-like multi-dimensional arrays of data by adding named dimensions and
associated coordinates. Multiple arrays are combined into datasets. On top of
this, scipp introduces (i) implicit handling of physical units, (ii) implicit
propagation of uncertainties, (iii) support for histograms, i.e., bin-edge
coordinate axes, which exceed the data’s dimension extent by one, and (iv)
support for event data. In conjunction these features enable a more natural and
more concise user experience. The combination of named dimensions, coordinates,
and units helps to drastically reduce the risk for programming errors. The core
of scipp is written in C++ to open opportunities for performance improvements
that a Python-based solution would not allow for. On top of the C++ core,
scipp’s Python components provide functionality for plotting and content
representations, e.g., for use in Jupyter Notebooks. While none of scipp’s
concepts in isolation is novel per-se, we are not aware of any project
combining all of these aspects in a single coherent software package. | | Source: | arXiv, 2010.00257 | | Services: | Forum | Review | PDF | Favorites | |
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