napari-locpix 0.0.7

Load in SMLM data and annotate within napari

napari-locpix

Load in SMLM data and annotate within napari

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This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.

Installation

Install napari via pip:

pip install "napari[all]"

You can install napari-locpix via pip:

pip install napari-locpix

To install latest development version :

pip install git+https://github.com/oubino/napari-locpix.git

Usage

First launch napari

napari

Then can find the plugin in napari, in the plugins menu, titled 'Annotate (napari-locpix)'

This plugin allows a user to

1. Read in SMLM data
2. Visualise SMLM data in a histogram
3. Add segmentations to the data
4. Extract the underlying localisations from the segmentations

IO

The input data can be in the form of a .csv or .parquet.

We expect there to be 4 columns at least, which should he identified inthe file column selection:

• X coordinate
• Y coordinate
• Frame
• Channel

If the data has been annotated with this software we can also load this in. Note however we currently only support loading in annotated data saved as a .parquet folder. Therefore, we recommend always keeping a .parquet copy until loading in an annotated .csv is supported.

The data can be outputted to a .parquet or a .csv

Drop localisations with zero label, gives you the option to only save the localisations which have been annotated i.e. labels 1 and above.

Channels labels allows you to give a real name label to each of the channels e.g. Chan 0 label: 'Alexa 647'

Visualisation

Using the render button you can render the loaded in data according to the histogram settings

X/Y bins defines the number of bins for the histogram. Use the X/Y bins ratio to retain the original aspect ratio of the FOV (or close) in the visualisation, if desired. The aspect ratio in this rendering does not affect the underlying localisation position data.

Vis interpolation defines how to interpolate the image before viewing

Annotations

Annotations can be added using Napari's viewer.

Click on the Napari button to create a new labels layer.

Rename the new labels layer to "Labels", otherwise the annotations will not be saved.

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-locpix" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.