napari-psfgenerator
PSF Generator Napari Plugin
The PSF Generator Napari Plugin provides an intuitive, interactive platform for simulating Point Spread Functions (PSFs) directly within the Napari ecosystem. Built on PyTorch, this plugin supports both CPU and GPU-accelerated computations, ensuring fast and efficient simulations for fundamental and advanced optical modeling.
Key Features:
- Flexible Propagation Models: Scalar and vectorial propagators in Cartesian and spherical coordinates.
- Customizable Parameters: Configure physical (e.g., numerical aperture, wavelength), numerical (e.g., pixel size, Z-stacks), and optical settings (e.g., Gibson-Lanni corrections, Zernike aberrations).
- Real-Time Visualization: Seamless integration with Napari for immediate visual feedback.
- Versatile API: Access propagators programmatically for custom workflows.
- Image Export: Save computed PSFs in TIFF format.
This plugin is a powerful tool for researchers in optics, computational microscopy, and imaging science, bridging user-friendly interactivity with the computational capabilities of our Python library.
This napari plugin was generated with copier using the napari-plugin-template.
Installation
Set up a Python virtual environment and install napari following this guide.
You can install napari-psfgenerator via pip:
pip install napari-psfgenerator
To install latest development version :
pip install git+https://github.com/Biomedical-Imaging-Group/napari-psfgenerator.git
Now you can try the plugin out! Open napari, click on the menu "Plugins" and select "Propagators (PSF Generator)".
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 MIT license, "napari-psfgenerator" is free and open source software
Issues
If you encounter any problems, please file an issue along with a detailed description.
Metadata
Release files for napari-psfgenerator 0.4.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| napari_psfgenerator-0.4.1.tar.gz | 17.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| napari_psfgenerator-0.4.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 34.4 kB
Release files / napari_psfgenerator-0.4.1.tar.gz
| Download URL | napari_psfgenerator-0.4.1.tar.gz |
|---|---|
| Size | 17.4 kB |
| Tags | Source |
|
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/3.11.10
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Release files / napari_psfgenerator-0.4.1-py3-none-any.whl
| Download URL | napari_psfgenerator-0.4.1-py3-none-any.whl |
|---|---|
| Size | 16.9 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 | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.10
|