Skip to main content

Modular Data Acquisition with Python

Project description

shortcut

PyMoDAQ, Modular Data Acquisition with Python, is a set of python modules used to interface any kind of experiments. It simplifies the interaction with detector and actuator hardware to go straight to the data acquisition of interest.

It has two purposes:

  • First, to provide a complete interface to perform automated measurements or logging data without having to write a user/interface for each new experiment, this is under the Dashboard_module environment and its two extensions.

  • Second, to provide various tools (modules) to easily build custom apps

It is divided in three main modules:

  • Dashboard_module : This is the module that will initialize actuators and detectors given the need of your particular experiment. You configure the dashboard using an interface for quick launch of various configurations.

  • DAQ_Logger_module : This module lets you log data from one or many detectors defined in the dashboard. You can log data in a binary hierarchical hdf5 file or towards a sql database

  • DAQ_Scan_module : This module lets you configure automated data acquisition from one or many detectors defined in the dashboard as a function or one or more actuators defined also in the dashboard.

The detectors and the actuators are represented and manipulated using two control modules:

  • DAQ_Move_module : used to control/drive an actuator (stand alone and/or automated). Any number of these modules can be instantiated.

  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated). Any number of these modules can be instantiated.

and many others to simplify any application development.

Published under the CeCILL-B FREE SOFTWARE LICENSE

GitHub repo: https://github.com/CEMES-CNRS

Documentation: http://pymodaq.cnrs.fr/

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

pymodaq-2.2.3.tar.gz (3.8 MB view details)

Uploaded Source

Built Distribution

pymodaq-2.2.3-py3-none-any.whl (4.0 MB view details)

Uploaded Python 3

File details

Details for the file pymodaq-2.2.3.tar.gz.

File metadata

  • Download URL: pymodaq-2.2.3.tar.gz
  • Upload date:
  • Size: 3.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.1.post20201107 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.0

File hashes

Hashes for pymodaq-2.2.3.tar.gz
Algorithm Hash digest
SHA256 ff69ae9979f10798e6a83797591952977d0bb02c8fd81b153db552f3ef9ad955
MD5 fb11c6b5fe0ad5650aa16b486c7900f6
BLAKE2b-256 e339b813601471daa280bd6641f5ae60e9f8450011ac32d8069f3b41c8719b13

See more details on using hashes here.

File details

Details for the file pymodaq-2.2.3-py3-none-any.whl.

File metadata

  • Download URL: pymodaq-2.2.3-py3-none-any.whl
  • Upload date:
  • Size: 4.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.1.post20201107 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.0

File hashes

Hashes for pymodaq-2.2.3-py3-none-any.whl
Algorithm Hash digest
SHA256 ccbcae3e069461ff98a283fa630f4a83447477c73ca166c0961e6489afeb1c04
MD5 9256de61a95a8dcebd239e4950348a88
BLAKE2b-256 5e360aae0039e1afe792ef01850464547f12a9613971065eb8e0d2f6f752132b

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