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Description

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.STACK format
  • 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

Installation

Install the package from PyPi:

pip install iter-mint

Run the app

mint

User manual

The 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

Contributing

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch:git push origin my-new-feature
  5. Submit a pull request

Metadata

Release files for iter-mint 1.5.1

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Source distribution for iter-mint 1.5.1
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Total release size: 2.9 MB

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