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.
1 maintainer
Metadata
1 maintainer
Release files for arrayview 0.46.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| arrayview-0.46.0.tar.gz | 1.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| arrayview-0.46.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.9 MB
Release files / arrayview-0.46.0.tar.gz
| Download URL | arrayview-0.46.0.tar.gz |
|---|---|
| Size | 1.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
88e6cd3ddf7de1ff6112c5aa80687a811ef2cdd4743a4f6659e6b4a7154786b8
|
|
BLAKE2b-256 checksum How to use checksums |
3c11289d6212a57d19f79347c42880ff0c2280fdb5a1a9c883ba6b33cfa384a9
|
| 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 18, 2026.
Transparency logRelease files / arrayview-0.46.0-py3-none-any.whl
| Download URL | arrayview-0.46.0-py3-none-any.whl |
|---|---|
| Size | 833.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e028d2347441ec3d90e7cae51de9ff48f17cb5c5972265594d98a38a3654acd3
|
|
BLAKE2b-256 checksum How to use checksums |
287d728ea4b3a14ec6f897cf29c9385f0b0aef696d874284dc73f10ec1f7466c
|
| 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 18, 2026.
Transparency log
