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https://github.com/chris-n-k/napari-time-series-plotter
A napari Plugin for visualisaton of pixel values over time (t+ nD) as graphs.
https://github.com/chris-n-k/napari-time-series-plotter
image-analysis napari napari-plugin napari-visualization plotting python python3 qt time-series time-series-analysis timeseries timeseries-analysis
Last synced: 7 days ago
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A napari Plugin for visualisaton of pixel values over time (t+ nD) as graphs.
- Host: GitHub
- URL: https://github.com/chris-n-k/napari-time-series-plotter
- Owner: Chris-N-K
- License: bsd-3-clause
- Created: 2021-11-09T09:01:52.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-04-24T11:07:43.000Z (5 months ago)
- Last Synced: 2024-09-23T09:05:11.181Z (10 days ago)
- Topics: image-analysis, napari, napari-plugin, napari-visualization, plotting, python, python3, qt, time-series, time-series-analysis, timeseries, timeseries-analysis
- Language: Python
- Homepage:
- Size: 32.2 MB
- Stars: 10
- Watchers: 1
- Forks: 5
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
# napari-time_series_plotter
[](https://github.com/ch-n/napari-time_series_plotter/raw/main/LICENSE)
[](https://python.org)
[](https://pypi.org/project/napari-time_series_plotter)
[](https://anaconda.org/conda-forge/napari-time-series-plotter)
[](https://napari-hub.org/plugins/napari-time-series-plotter)
[](https://github.com/ch-n/napari-time_series_plotter/actions)
[](https://codecov.io/gh/Chris-N-K/napari-time_series_plotter)
## 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
[TSP_basic_and_voxel_plotting_demo.webm](https://github.com/Chris-N-K/napari-time_series_plotter/assets/56394171/89b12967-5cef-4645-9b68-1a13ea740be5)
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
[TSP_ROI_plotting_demo.webm](https://github.com/Chris-N-K/napari-time_series_plotter/assets/56394171/b4ce7e20-21d8-407c-8b3b-739a9385350d)
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.
2. 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)
3. Reposition or remove shapes if needed.
4. Change the ROI mode in the `Options` tab (Default: mean).
### Plotting multiple Points
[TSP_Points_plotting_demo.webm](https://github.com/Chris-N-K/napari-time_series_plotter/assets/56394171/a4f5ede5-8146-40a6-9629-c737aad2daef)
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
[TSP_Inspector_demo.webm](https://github.com/Chris-N-K/napari-time_series_plotter/assets/56394171/f5a2e7fc-0d33-4f70-a2e9-2bbf959354c6)
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
- [X] Update to napari-plugin-engine2 [#5](https://github.com/ch-n/napari-time_series_plotter/issues/5)
- [X] Update widget GUI [#6](https://github.com/ch-n/napari-time_series_plotter/issues/6)
- [x] Add widget to save pixel/voxel time series to file [#7](https://github.com/ch-n/napari-time_series_plotter/issues/7)
- [X] Add ROI and multi-voxel plotting [#14](https://github.com/ch-n/napari-time_series_plotter/issues/14)
- [ ] Evaluate and close remaining issues ([#22](https://github.com/ch-n/napari-time_series_plotter/issues/22), [#25](https://github.com/ch-n/napari-time_series_plotter/issues/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
[The Cancer Imaging Archive]: https://www.cancerimagingarchive.net/
[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/ch-n/napari-time_series_plotter/issues
[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/