napari-plot

Interactive plotting in napari or a standalone Qt viewer

napari-plot provides GPU-accelerated Line, Scatter, MultiLine, Centroids, Text, Region, InfLine, and Bar layers. It supports linear, logarithmic, and categorical axes, an interactive legend, data selection tools, and image display.

Usage

You can use napari-plot alongside napari where it is embedded as a dock widget. If using this option, controls are relegated to a toolbar where you can adjust layer properties like you would do in napari.

Or as a standalone app where only one-dimensional plotting is enabled. In this mode, controls take central stage and reflect napari's own behaviour where layer controls are embedded in the main application.

Data selection is also permitted by enabling one of the available selection tools.

Roadmap:

This is only provisional list of features that I would like to see implemented. It barely scratches the surface of what plotting tool should cover so as soon as the basics are covered, focus will be put towards adding more exotic features. If there are features that you certainly wish to be included, please modify the list below or create a new issue

• Support for new layer types. Layers are based on napari's Layer, albeit in a two-dimensional setting. Supported and planned layers:
  • Line Layer - simple line plot.
  • Scatter Layer - scatter plot (similar to napari's Points layer).
  • Centroids/Segments Layer - horizontal or vertical line segments.
  • InfLine Layer - infinite horizontal or vertical lines that span over very broad range. Useful for defining regions of interest.
  • Region Layer - infinite horizontal or vertical rectangular boxes that span over very broad range. Useful for defining regions of interest.
  • Shapes Layer - napari's own Shapes layer
  • Points Layer - napari's own Points layer
  • Multi-line Layer - more efficient implementation of Line layer when multiple lines are necessary.
  • Bar - horizontal and vertical bar charts.
• Proper interactivity of each layer type (e.g. moving Region or InfLine, adding points, etc...)
• Intuitive interactivity. napari-plot will provide excellent level of interactivity with the plotted data. We plan to support several types of Tools that permit efficient interrogation of the data. We currently provide several zoom and select tools and hope to add few extras in the future.
  • Box-zoom - standard zooming rectangle. Simply left-mouse + drag/release in the canvas on region of interest
  • Horizontal span - zoom-in only in the y-axis by Ctrl + left-mouse + drag/release in the canvas.
  • Vertical span - span-in only in the x-axis by Shift + left-mouse + drag/release in the canvas.
  • Rectangle select - rectangle tool allowing sub-selection of data in the canvas. Similar to the Box-zoom but without the zooming part.
  • Polygon select - polygon tool allowing sub-selection of data in the canvas.
  • Lasso select - lasso tool allowing sub-selection of data in the canvas.
• Interactive plot legend
• Customizable axis visuals.
  • Plot axis enabling customization of tick/label size and color
  • Support for logarithmic and categorical scales
• Add convenient plotting interface:
  • Add .plot functionality
  • Add .scatter functionality
  • Add .hbar and .vbar functionality
  • Add .imshow functionality

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

Installation

napari-plot requires napari 0.10.0 and Python 3.11 or later. Use a Qt6 backend with pip install "napari-plot[pyqt6]" or pip install "napari-plot[pyside6]". Qt5 is no longer supported.

You can install napari-plot directly from PyPI via:

pip install napari-plot

or from the git repo:

git clone https://github.com/lukasz-migas/napari-plot.git
cd napari-plot
pip install -e '.[all]'

The plot widgets open in a tabified bottom dock in napari. Custom layers retain their individual controls; selecting several layers exposes shared opacity and blending controls. Built-in-only selections use napari's dynamic controls.

viewer.scene.camera and viewer.canvas.overlays expose the new model layout. Existing viewer.camera, viewer.text_overlay, viewer.legend, and viewer.grid_lines accessors refer to the same objects. The custom camera, log axes, and plot grid remain available.

Layer axis labels automatically populate the plot labels until those labels are edited explicitly. Unspecified text and legend font sizes follow the application's appearance font size; pass a number to fix the size.

Python 3.11 or later is required. See the documentation for standalone and embedded quick starts, layer examples, axis controls, interactions, and the public API.

Contributing

Contributions are very welcome. Install the test environment and run the tests with uv:

uv sync --no-dev --group test --extra pyqt6 --extra optional
uv run --no-sync pytest

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-plot" is free and open source software

Issues

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

Support

This project is supported by a Chan-Zuckerberg Initiative napari grant.