arcosPx-napari
Introduction
This repository contains a dedicated ARCOS.px plugin for the napari image viewer. It tracks spatio-temporal correlations in images as described in a publication of Grädel et al. Tracking Coordinated Cellular Dynamics in Time-Lapse Microscopy with ARCOS.px (link).
ARCOS.px is a computational method to identify and track clusters of correlated cell signaling in time-lapse microscopy images. It is the latest addition to the ARCOS ecosystem developed in the Cellular Dynamics Lab at the University of Bern.
Example tracking
Actin polymerization waves in REF52 fibroblasts treated with 50 ng/mL PDGF, 24h before imaging.
Installation
You can install arcosPx-napari via pip:
pip install arcosPx-napari
To install latest development version :
pip install git+https://github.com/pertzlab/arcosPx-napari.git
Contributing
Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.
License
Distributed under the terms of the BSD-3 license, "arcosPx-napari" is free and open source software
Issues
If you encounter any problems, please file an issue along with a detailed description.
1 maintainer
Release files for arcosPx-napari 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| arcospx_napari-0.1.4.tar.gz | 28.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| arcospx_napari-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 28.6 MB
Release files / arcospx_napari-0.1.4.tar.gz
| Download URL | arcospx_napari-0.1.4.tar.gz |
|---|---|
| Size | 28.6 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
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twine/6.2.0 CPython/3.13.7
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Release files / arcospx_napari-0.1.4-py3-none-any.whl
| Download URL | arcospx_napari-0.1.4-py3-none-any.whl |
|---|---|
| Size | 20.1 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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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.7
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