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TSP

napari-time-series-plotter

A Plugin for napari to visualize pixel values over the first dimension (time -> t+3D, t+2D) as graphs.

License Python Version PyPI Anaconda-Server Badge napari hub tests codecov

Description

Napari-time_series_plotter (TSP) is a plugin for the napari ndimensional image viewer.

TSP adds live plotting of time-resolved images to napari. You can select and visualize pixel/voxel or ROI mean values from one or multiple image layers as intensity-over-time line plots (The first image dimension is handled as time) and save the figures or the underlying time series data as CSV file. TSP supports 3D to nD images (3D: t+2D, nD: t+nD).

Plotting is handeled by the Explorer widget, it offers three different plotting modes: Voxel, Shapes, Points
--> Voxel mode offers live plotting while moving the cursor over an image layer
--> Shapes mode offers shape-based ROI plotting the ROI combination method can be one of [Mean, Median, STD, Sum, Min, Max]; multiple ROIs can be plotted simultaneously
--> Points mode offers simultaneous, point-based plotting of multiple voxels
You can modify and save the plots through the canvas toolbar.
Plotting powered by napari-matplotlib.

Viewing the time series as a table is handled by the Inspector widget. You can load the data you've plotted and inspect the single time point values of each selection. The columns are named like the plots in the Explorer. You can copy the whole tabe or a selection to the clipboard or directly expot it to a CSV file to save the time series.


Installation

You can either install the latest version via pip or conda.

pip:

pip install napari-time-series-plotter

or download the packaged tar.gz file from the release assets and install it with

pip install /path/to/file.tar.gz

conda:

conda install -c conda-forge napari-time-series-plotter

Alternatively, you can install the plugin directly in the napari viewer plugin manager, the napari hub, or the release assets.


To install the latest development version install directly from the relevant GitHub branch.

Usage

Basics and Live plotting

basic_demo

  1. Select the TSPExplorer widget in the Plugins tab of the napari viewer
  2. Use the LayerSelector to choose the image layers you want to source for plotting
  3. Move the corsor over the layer while holding "Shift"

The Options tab offers multiple options to customize your plot.

  • Set custom title or axe labels
  • Switch between autoscaling and manually defined max and min values of the axes
  • Switch to label truncation in the options tab if your layer names are too long for the figure legend (set max length manually)
  • Set a scaling factor for the X-axis

The plot can be modified and saved through its toolbar above.

Plotting ROIs

roi_demo

  1. Select the Shapes plotting mode via the Options tab (Voxel mode is the default).
  2. Use the LayerSelector to choose the image layers you want to source for plotting.
  3. Add one ore more shapes to the "ROI Selection" layer.
    The "ROI Selection" shapes are 2D only, effecting the currently displayed slice.
    (newly added shapes might have to be moved before they are correctly plottet)
  4. Reposition or remove shapes if needed.
  5. Change the ROI mode in the Options tab (Default: mean).

Plotting multiple Points

points_demo

  1. Select the Shapes plotting mode via the Options tab (Voxel mode is the default).
  2. Use the LayerSelector to choose the image layers you want to source for plotting.
  3. Add one or more points to the "Point selection" layer.
    The points can be on different slices (3D and 4D support only) or images (grid mode)
  4. Reposition or remove points if needed.

View time series as table

points_demo

  1. Select the TSPInspector widget in the Plugins tab of the napari viewer
  2. Press the load from plot button to load the currently displayed plots into the Inspector

You can copy the whole table or a selection to your clipboard or export it to CSV file through the buttons above.

ToDo (help welcome)

  • Add Sphinx documentation

Version 0.1.0 Milestones

  • Update to napari-plugin-engine2 #5
  • Update widget GUI #6
  • Add widget to save pixel/voxel time series to file #7
  • Add ROI and multi-voxel plotting #14
  • Evaluate and close remaining issues (#22, #25,)

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-time_series_plotter" is free and open-source software

Issues

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


References

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

Images used in the demo gif were taken from The Cancer Imaging Archive

DOI: https://doi.org/10.7937/K9/TCIA.2015.VOSN3HN1
Images: 1.3.6.1.4.1.9328.50.16.281868838636204210586871132130856898223
        1.3.6.1.4.1.9328.50.16.254461916058189583774506642993503110733

Version:

  • 0.0.6

Last updated:

  • 25 July 2023

First released:

  • 01 December 2021

License:

Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 11
  • Forks: 5
  • Issues + PRs: 9

Python versions supported:

Operating system:

Requirements:

  • napari-matplotlib (<1.0)
  • numpy
  • pandas
  • qtpy