This project contains example usage of the iterplot libary in a Qt application. The Qt application allows to select a set of UDA variables and the plot them using either matplotlib or PyQtGraph graphics library. Following features are currently supported:
- Plotting multiple graphs in a row/column layout
- Plotting multiple signals in one plot (either stacked or not) by using the
ROW.COLUMN.STACKformat - Support for Pan/Zoom/Crosshair/Distance/Markers
- Support for automatically downloading UDA data (for continous signals - currently Matplotlib only)
- Support for basic data processing. See iplotProcessing
- Customize appearance and styling of canvas, plots, axes, fonts, lines in a cascading manner.*
- Computation of different statistical metrics for the displayed signals.
- Export of canvas data to CSV format.
- Export of canvas data and MINT tables to .h5 or .parquet formats
Install the package from PyPi:
pip install iter-mintmintThe embedded manual (mint/data/help/manual.html) is generated from
mint/data/help/manual.md plus sections injected from the code (keyboard
shortcuts, access modes, supported data source types). The HTML is
regenerated automatically on every push by a GitHub Action — you only
edit the Markdown.
To preview a change locally before pushing:
pip install -e ".[docs]"
python -m mint.tools.build_manual- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request