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ndcube v2.1.1: Enhancing Analysis Capabilities for N-dimensional Astronomical Coordinate-aware Data in Python

Presentation #110.18 in the session Data Analysis Techniques Posters.

Published onSep 18, 2023
ndcube v2.1.1: Enhancing Analysis Capabilities for N-dimensional Astronomical Coordinate-aware Data in Python

We outline new features in the latest release (v2.1.1) of ndcube, a free, open-source, community-developed Python package. ndcube already provides powerful tools for inspecting, manipulating, and visualizing n-dimensional coordinate-aware astronomical data, independent of the number of data dimensions and the physical coordinate types they represent. This has made ndcube a foundation upon which various instrument-specific packages have been built including those for DKIST, JWST, EIS, IRIS, PUNCH and Solar Orbiter/SPICE. The v2.1.1 release includes new features that enhance ndcube’s data analysis capabilities including support for basic arithmetic operations between coordinate-aware and coordinate-agnostic data, unit conversion, data rebinning and reprojecting data to another set of coordinate transformations. These greatly improve users abilities in analysis tasks such as increasing signal-to-noise by summing neighbouring pixels and reprojecting images to a new viewpoint. All ndcube’s features automatically and self-consistently alter both the data and coordinates. This frees users from complex but well-defined tasks, thus speeding up their scientific investigations and reducing the scope for analysis errors.

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