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PyMoDAQ

Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps

It is organised a shown below:

overview

PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.

The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).

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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).

Any number of these modules can be instantiated in the Dashboard.

The Dashboard allows you to start dedicated extensions that will make use of the control modules:

  • 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.

and many others to simplify any application development.

Published under the MIT FREE SOFTWARE LICENSE

GitHub repo: https://github.com/PyMoDAQ

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

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Modular Data Acquisition with Python

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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PyMoDAQ
Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
About
Modular Data Acquisition with Python
pymodaq.cnrs.fr
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PyMoDAQ
Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
About
Modular Data Acquisition with Python
pymodaq.cnrs.fr
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PyMoDAQ
Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
About
Modular Data Acquisition with Python
pymodaq.cnrs.fr
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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PyMoDAQ
Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
About
Modular Data Acquisition with Python
pymodaq.cnrs.fr
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
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} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PyMoDAQ
Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
About
Modular Data Acquisition with Python
pymodaq.cnrs.fr
Resources
Readme
MIT license
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
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} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
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Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
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Modular Data Acquisition with Python
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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PyMoDAQ
Latest VersionDocumentation Statushttps://codecov.io/gh/PyMoDAQ/PyMoDAQ/graph/badge.svg?token=IQNJRCQDM2
LinuxPyQt5PyQt6PySide6
Python 3.939-linux-pyqt539-linux-pyqt639-linux-pyside6
Python 3.10310-linux-pyqt5310-linux-pyqt6310-linux-pyside6
Python 3.11311-linux-pyqt5311-linux-pyqt6311-linux-pyside6
Python 3.12312-linux-pyqt5312-linux-pyqt6312-linux-pyside6
WindowsPyQt5PyQt6PySide6
Python 3.939-windows-pyqt539-windows-pyqt639-windows-pyside6
Python 3.10310-windows-pyqt5310-windows-pyqt6310-windows-pyside6
Python 3.11311-windows-pyqt5311-windows-pyqt6311-windows-pyside6
Python 3.12312-windows-pyqt5312-windows-pyqt6312-windows-pyside6
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 extensions.
  • Second, to provide various tools (modules) to easily build custom apps
It is organised a shown below:
overview
PyMoDAQ's Dashboard and its extensions: DAQ_Scan for automated acquisitions, DAQ_Logger for data logging and many other.
The main component is the Dashboard : This is a graphical component 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 (numbers and types of control modules).
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 in the Dashboard
  • DAQ_Viewer_module : used to control/drive a detector (stand alone and/or automated).
Any number of these modules can be instantiated in the Dashboard.
The Dashboard allows you to start dedicated extensions that will make use of the control modules:
  • 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.
and many others to simplify any application development.
Published under the MIT FREE SOFTWARE LICENSE
GitHub repo: https://github.com/PyMoDAQ
Documentation: http://pymodaq.cnrs.fr/
About
Modular Data Acquisition with Python
pymodaq.cnrs.fr
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages