ndcube
ndcube is an open-source SunPy affiliated package for manipulating, inspecting and visualizing multi-dimensional contiguous and non-contiguous coordinate-aware data arrays.
It combines data, uncertainties, units, metadata, masking, and coordinate transformations into classes with unified slicing and generic coordinate transformations and plotting/animation capabilities. It is designed to handle data of any number of dimensions and axis types (e.g. spatial, temporal, spectral, etc.) whose relationship between the array elements and the real world can be described by World Coordinate System (WCS) translations.
Usage of Generative AI
We expect authentic engagement in our community. Be wary of posting output from Large Language Models or similar generative AI as comments on GitHub or any other platform, as such comments tend to be formulaic and low quality content. If you use generative AI tools as an aid in developing code or documentation changes, ensure that you fully understand the proposed changes and can explain why they are the correct approach and an improvement to the current state.
Acknowledging ndcube
If you use ndcube is your work, we kindly ask you to acknowledge ndcube in your publications and presentations.
Installation
For detailed installation instructions, see the installation guide in the ndcube docs.
Getting Help
For more information or to ask questions about ndcube, check out:
Contributing
We love contributions! ndcube is open source, built on open source, and we’d love to have you hang out in our community.
If you would like to get involved, check out the Developers Guide section of the SunPy docs. Stop by our chat room #ndcube:openastronomy.org if you have any questions. Help is always welcome so let us know what you like to work on, or check out the issues page for the list of known outstanding items.
For more information on contributing to SunPy, please read our Newcomers’ guide.
When you are interacting with the SunPy community you are asked at to follow our code of conduct.
Release files for ndcube 2.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ndcube-2.4.2.tar.gz | 716.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ndcube-2.4.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 891.1 kB
Release files / ndcube-2.4.2.tar.gz
| Download URL | ndcube-2.4.2.tar.gz |
|---|---|
| Size | 716.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Provenance
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Signed by GitHub Actions, verified by PyPI on Sep 17, 2026.
Transparency logRelease files / ndcube-2.4.2-py3-none-any.whl
| Download URL | ndcube-2.4.2-py3-none-any.whl |
|---|---|
| Size | 174.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 17, 2026.
Transparency log
