Skip to main content

AutodiDAQt is a simple data acquisition framework. For science.

Project description

test_status coverage docs_status

example

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.

Requirements

  • Python 3.7 over

  • NoArch

Features

Automated DAQ

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.

UI Generation

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.

Installation

$ pip install autodidaqt

Installation from Source

  1. Clone this repository

  2. Install make if you are on a Windows system

  3. Install poetry (the alternative Python package manager)

  4. Run make install from the directory containing this README

Usage

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:

  1. minimal_app

  2. plot_data

  3. simple_actors

  4. ui_panels

  5. wrapping_instruments

  6. scanning_experiment

  7. scanning_experiment_revisited

  8. scanning_interlocks

  9. scanning_custom_plots

  10. scanning_setup_and_teardown

  11. scanning_properties_and_profiles

  12. manuscript_fig4

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

autodidaqt-1.1.0.tar.gz (1.1 MB view details)

Uploaded Source

Built Distribution

autodidaqt-1.1.0-py3-none-any.whl (1.1 MB view details)

Uploaded Python 3

File details

Details for the file autodidaqt-1.1.0.tar.gz.

File metadata

  • Download URL: autodidaqt-1.1.0.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.11 CPython/3.8.5 Windows/10

File hashes

Hashes for autodidaqt-1.1.0.tar.gz
Algorithm Hash digest
SHA256 e73f1292baefbd63c030960568d3707be80aa1cd69b6a364035aaf55ca74fdd5
MD5 04fa2b684923d52700b039411bcf18f9
BLAKE2b-256 17a69545ff24e16ba0ef8e51cad1212e574d7fe05ec9fbf8305e5ea8b8c6e89d

See more details on using hashes here.

File details

Details for the file autodidaqt-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: autodidaqt-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 1.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.11 CPython/3.8.5 Windows/10

File hashes

Hashes for autodidaqt-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8d0b2cd891699cea3379b7eb2efd2736257492ff0ab1db86ade0bf84f8fe8c18
MD5 20a7b6fa7981465c8727c818bae5c132
BLAKE2b-256 cc2fa5dac5ede7266857d73456b735bd64e99e0020f845b927432bee502cebab

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page