arrayview

This is my array viewer. There are many like it, but this one is mine.

Arrayview lets you scroll through multi-dimensional arrays.

Open it from the shell, from Python, Julia, or Matlab, or inside a Jupyter notebook. Use it locally or over SSH.

If you work in VS Code, you can open arrays directly from the explorer — click an array file, or right-click a folder and choose Open Folder in ArrayView to review a DICOM series or a whole directory of arrays as one stack. With Remote SSH or a tunnel, it works the same way.

It is meant to feel simple but there's more to it than meets the eye.

Curious? Give it a try with

uvx arrayview your_array.npy
uvx arrayview path/to/dicom-series/

Press v for the three-plane ortho view. Shift+3 replaces the current slice, or all three ortho panes, with interactive 3D cutaway renders. Drop another file onto an open viewer to compare, open separately, or overlay it. Press Shift+R for ROI analysis: a compact HUD lists each region's mean and standard deviation. The HUD sits beside the image when space allows; drag its header to move it. Hover a row or region to highlight its counterpart, and use each row's trash icon to delete that region. Open the detailed analysis with the button beside the HUD's column headings. Hold a flood-fill seed and drag up/down to adjust sensitivity; a translucent tapered gauge at the starting point shows the current value and the 1%–100% range. The pointer hides while adjusting; only the gauge marker moves.

Check the docs to learn more.

Warning: Arrayview is still under active development. Things may break or change without warning.

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Credits

Author: Oscar

GitHub Statistics

Data verified by PyPI on Sep 14, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.12

Tags

array mri npy viewer visualization

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