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A tool for live plotting and processing data

Project description

plottr: modular data plotting and processing

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A framework for inspecting data, based on flowcharts from pyqtgraph. plottr's main aim is to allow the user to define custom data processing flows and plotting. A particular use case is data filtering and plotting.

Documentation: (work in progress...)

Recent changes:


  • Drop support for Python 3.6 and support type-checking with qcodes 0.21.0
  • Fix type-checking with numpy 1.20


  • Fixed y-axis to not show axis-label if more than one plot is selected in 1D single-plot show.


  • Workaround for bug with pyqt installed via conda that would result in blank icons.
  • Add experimental support for using Pyside2 as an alternative to PyQt5



  • Entry points for inspectr (plottr-inspectr) and autoplot (plottr-autoplot-ddh5)
  • LICENSE file has been added (no change to license of the code)
  • has been tweeked to ensure that sdist and bdist_wheel packages are generated correctly



  • Usable version of hdf5 file support. can use the apps/ script to launch a tool that allows easy (live) plotting.



  • there were several issues/annoyances that caused (minor) issues with grid handling and plotting in rare-ish circumstances. Most of them should be fixed now.


  • A few docs and examples, mostly about grid usage.





Plottr is installable from pypi with pip install plottr

To install with either PyQt5 or Pyside2 backend you can do pip install plottr[PyQt5] or pip install plottr[Pyside2] Note that if you have installed pyqt from (Ana)Conda you should not use any of these targets but do pip install plottr

To install from source: clone the repo, and install using pip install -e .

inspectr: QCoDeS dataset inspection and (live) plotting

You can use the inspectr tool to get a simple overview over QCoDeS database files, and plot datasets contained in the database.

To use: run plottr-inspectr [--dbpath <path to your .db file>]

As an alternative from the root of the cloned plottr repository, run python apps/ [--dbpath <path to your .db file>]

For basic instructions, check out the Notebook Live plotting qcodes data under /doc/examples.

Some notes on installing

Note: this package is not compatible with the original plottr tool. You might want to install freshly if you still use the old version.


  • python >= 3.7 (f-strings...)
  • the usual: numpy, mpl, ...
  • pandas >= 0.22
  • xarray
  • pyqtgraph >= 0.10.0

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