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napari-locpix

napari-locpix

Load in SMLM data and annotate within napari

    License MIT PyPI Python Version tests codecov napari hub

    Load in SMLM data and annotate within napari


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

    Installation

    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

    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:

    • 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 and a .csv

    This includes the annotated data.

    Visualisation

    Using the render button you can render the loaded in data

    Segmentation

    Segmentations can be added using Napari's viewer.

    Simply click the add Labels.

    Note that this software will expect the labels to be called "Labels"

    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.

    Version:

    • 0.0.3

    Last updated:

    • 23 January 2023

    First released:

    • 16 January 2023

    License:

    • MIT

    Supported data:

    • Information not submitted

    Plugin type:

    GitHub activity:

    • Stars: 0
    • Forks: 0
    • Issues + PRs: 6

    Python versions supported:

    Operating system:

    Requirements:

    • numpy
    • qtpy
    • polars
    • pyarrow

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