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OpenPIV

Build StatusBuild and upload to PyPIDOI

PyPIAnaconda-Server Badge

OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in development, to ease the use for those users who don't have python skills.

Warning

The OpenPIV python version is still in its beta state. This means that it still might have some bugs and the API may change. However, testing and contributing is very welcome, especially if you can contribute with new algorithms and features.

Test it without installation

Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation: Binder

Installing

Use PyPI: https://pypi.python.org/pypi/OpenPIV:

pip install openpiv

Or conda

conda install -c alexlib openpiv

To build from source

Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip or clone using git

git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:

python setup.py build_ext --inplace

Or for the global installation, use:

python setup.py install

Documentation

The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org

Demo notebooks

  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV

These and many additional examples are in another repository: OpenPIV-Python-Examples

Contributors

  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan

Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.

How to cite this work

DOI

About

OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython

www.openpiv.net

Resources

Readme
License
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

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Packages

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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" + '

Skip to content
BranchesTags
Repository files navigation
OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
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0 stars
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0 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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OpenPIV
Build StatusBuild and upload to PyPIDOI
PyPIAnaconda-Server Badge
OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of
a set of PIV image pairs. In addition, a Qt and Tk graphical user interfaces are in
development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its beta state. This means that
it still might have some bugs and the API may change. However, testing and contributing
is very welcome, especially if you can contribute with new algorithms and features.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Binder
Installing
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv

Or conda
conda install -c alexlib openpiv

To build from source
Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip
or clone using git
git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:
python setup.py build_ext --inplace

Or for the global installation, use:
python setup.py install 
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass with Windows Deformation
  5. Multiple sets in one notebook
  6. 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer
  10. Andreas Bauer
  11. David Bohringer
  12. Erich Zimmer
  13. Peter Vennemann
  14. Lento Manickathan
Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.
How to cite this work
DOI
About
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
www.openpiv.net
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages