AutodiDAQt is a simple data acquisition framework. For science.
autodidaqt := DAQ + UI generation + Reactivity + Instruments
You should be spending your time designing and running experiments, not your DAQ software.
autodidaqt is a nuts and bolts included framework for scientific data acquisition (DAQ), designed for rapid prototyping and the challenging DAQ environment of angle resolved photoemission spectroscopy. If you specify how to sequence motions and data collection, autodidaqt can manage the user interface, talking to and managing instruments, plotting interim data, data collation, and IO for you.
autodidaqt also has logging and notification support built in and can let you know over email or Slack when your experiment finishes (successfully or not!).
If autodidaqt doesn’t do exactly what you need, get in contact with us or check out the examples. There’s a good chance that if it isn’t built in, autodidaqt is flexible enough to support your use case.
Python 3.7 over
autodidaqt wraps instruments and data sources in a uniform interface, if you specify how to sequence motion and acquisition, autodidaqt handles async collection, IO, and visualizing your data as it is acquired.
autodidaqt using PyQt and Qt5 to generate UIs for your experiments. It also provides simple bindings (autodidaqt.ui) that make making managing the day to day of working on PyQt simpler, if you need to do UI scripting of your own.
It also ships with a window manager that you can register your windows against, making it seamless to add extra functionality to your experiments.
The autodidaqt UI bindings are wrapped to publish as RxPY observables, making it easier to integrate your PyQT UI into a coherent asynchronous application.
$ pip install autodidaqt
Installation from Source
Clone this repository
Install make if you are on a Windows system
Install poetry (the alternative Python package manager)
Run make install from the directory containing this README
For usage examples, explore the scripts in the examples folder. You can run them with
$ python -m autodidaqt.examples.[example_name]
replacing [example_name] with one of:
You can also get a list of all the available examples by running
$ python -m autodidaqt.examples
Examples for “remote control”, including a “virtual nanoXPS lab” are available in integration_tests folder of AutodiDAQt receiver in its companion repository.
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Hashes for autodidaqt-1.1.0-py3-none-any.whl