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PrefPy

Rank aggregation algorithms in the computer science field of computational social choice

What's New

  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy

Work In Progress

  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)

Installation

  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine

Install directly from PyPI using pip for Python 3.4 (or greater) with the command

pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command

python3 setup.py develop

About

Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development

Resources

Readme
GPL-3.0 license
Activity
Custom properties

Stars

11 stars

Watchers

12 watching

Forks

11 forks
Report repository

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
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Used by
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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");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
Releases
Packages
Used by
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('^' + ".*" + '

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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
Releases
Packages
Used by
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
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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
Releases
Packages
Used by
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
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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
Releases
Packages
Used by
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
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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, '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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PrefPy
Rank aggregation algorithms in the computer science field of computational social choice
What's New
  • Released on Python Package Index (PyPI) for public download and install with pip (see Installation below)
  • Experiments and tests have been factored out of the repository (now located at https://github.com/pdpiech/prefpy-experiments)
  • Generalized method of moments algorithm for mixtures of Plackett-Luce models
  • GMM algorithm implemented for OPRA (https://github.com/PrefPy/opra/)
  • Implementation of EMM algorithm for mixtures of Plackett-Luce by Gormley & Murphy
Work In Progress
  • This is an initial version of the Python package form, further structural changes will be coming
  • Module naming conventions will be changed; currently the algorithm files take the initials of the names of the papers from which they originate (e.g. "gmmra" for Generalized Method of Moments for Rank Aggregation)
  • Mixture Model for Plackett-Luce EMM algorithm by Gormley & Murphy is forthcoming pending verification and testing of the method
  • Random utility model algorithms (verification of the implentation needs to be completed)
Installation
  • Use of MATLAB optimization in this package requires Python 3.4 due to lack of support yet for Python 3.5 by the MATLAB Engine
Install directly from PyPI using pip for Python 3.4 (or greater) with the command
pip install prefpy

Symlink install while developing to keep changes in the code instead by downloading from GitHub and run setup.py with the command
python3 setup.py develop

About
Collection of Python scripts for preference aggregation, estimation, and generation. Currently under initial development
Resources
Readme
GPL-3.0 license
Activity
Custom properties
Stars
11 stars
Watchers
12 watching
Forks
11 forks
Report repository
Releases
Packages
Used by
Contributors
Languages