https://github.com/hanjinliu/napari-macrokit
Executable script generation for napari plugins
https://github.com/hanjinliu/napari-macrokit
napari napari-plugin
Last synced: 3 months ago
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Executable script generation for napari plugins
- Host: GitHub
- URL: https://github.com/hanjinliu/napari-macrokit
- Owner: hanjinliu
- License: bsd-3-clause
- Created: 2023-01-23T11:26:13.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-01-27T12:29:57.000Z (over 2 years ago)
- Last Synced: 2025-02-02T00:31:45.352Z (3 months ago)
- Topics: napari, napari-plugin
- Language: Python
- Homepage:
- Size: 2.9 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# napari-macrokit
[](https://github.com/hanjinliu/napari-macrokit/raw/main/LICENSE)
[](https://pypi.org/project/napari-macrokit)
[](https://python.org)
[](https://github.com/hanjinliu/napari-macrokit/actions)
[](https://codecov.io/gh/hanjinliu/napari-macrokit)
[](https://napari-hub.org/plugins/napari-macrokit)
Executable script generation for napari plugins.
↑ [Example](https://github.com/hanjinliu/napari-macrokit/blob/main/examples/regionprops.py) showing the real-time recording of GUI operation.
This napari plugin aims at making image analysis reproducible with arbitrary input/output types.
## Usage
Create a macro object, decorate functions with `record` method and run!
```python
from napari_macrokit import get_macro
macro = get_macro("my-plugin-specifier") # get macro object
# define a function
@macro.record
def add(a: float, b: float) -> float:
return a + b
# run
result = add(3.2, 5.4)
add(result, 1.0)
macro
# Out:
# >>> float0 = add(3.2, 5.4)
# >>> float1 = add(float0, 1.0)
```
## Record GUI Operations
You can use recordable functions in your widgets to keep tracks of GUI operations.
More simply, you can double-decorate functions with `record` and `magicgui`.
```python
import numpy as np
from magicgui import magicgui
import napari
from napari.types import ImageData
from napari_macrokit import get_macro
macro = get_macro("my-plugin-specifier") # get macro object
# define recordable magicgui
@magicgui
@macro.record
def add(image: ImageData, b: float) -> ImageData:
return image + b
viewer = napari.Viewer() # launch a viewer
viewer.add_image(np.random.random((100, 100))) # image data
viewer.window.add_dock_widget(add) # add magicgui to the viewer
```
Running add twice in GUI and you'll find macro updated like below.
```python
macro
# Out
# >>> image0 = add(viewer.layers['Image'].data, 0.06)
# >>> image1 = add(image0, 0.12)
```
## Combining Plugins
Suppose you have two modules that use `napari-macrokit`.
```python
# napari_module_0.py
from napari.types import ImageData
from scipy import ndimage as ndi
from napari_macrokit import get_macro
macro = get_macro("napari-module-0")
@macro.record
def gaussian_filter(image: ImageData, sigma: float) -> ImageData:
return ndi.gaussian_filter(image, sigma=sigma)
@macro.record
def threshold(image: ImageData, value: float) -> ImageData:
return image > value
```
```python
# napari_module_1.py
from napari.types import ImageData
import numpy as np
from napari_macrokit import get_macro
macro = get_macro("napari-module-1")
@macro.record
def estimate_background(image: ImageData) -> float:
return np.percentile(image, 10.0)
```
You can use functions from both modules to build an analysis workflow by collecting existing macro objects with `collect_macro` function. All the recordable actions in the modules will also be recorded to the returned macro object.
```python
import numpy as np
from napari_macrokit import collect_macro
from napari_module_0 import gaussian_filter, threshold
from napari_module_1 import estimate_background
# global_macro will record all the macro available at this point
global_macro = collect_macro()
# start image analysis!
image = np.random.random((100, 100))
out = gaussian_filter(image, 2.0)
thresh = estimate_background(out)
binary = threshold(out, thresh)
macro
# Out
# >>> image0 = gaussian_filter(arr0, 2.0)
# >>> float0 = estimate_background(image0)
# >>> image1 = threshold(image1, float0)
```
---------------------------------
This [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.
## Installation
You can install `napari-macrokit` via [pip]:
pip install napari-macrokit
To install latest development version :
pip install git+https://github.com/hanjinliu/napari-macrokit.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,
"napari-macrokit" is free and open source software
## Issues
If you encounter any problems, please [file an issue] along with a detailed description.
[napari]: https://github.com/napari/napari
[Cookiecutter]: https://github.com/audreyr/cookiecutter
[@napari]: https://github.com/napari
[MIT]: http://opensource.org/licenses/MIT
[BSD-3]: http://opensource.org/licenses/BSD-3-Clause
[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt
[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt
[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0
[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt
[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin
[file an issue]: https://github.com/hanjinliu/napari-macrokit/issues
[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/