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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all
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try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

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1 star

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1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); GitHub - hackrush01/GCPToSAT: A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem. · GitHub
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GCP To SAT

A simple python code which reduces the Graph Colorablity Problem to Boolean Satisfiability Problem.

Requirements

  1. Python 3
  2. minisat solver from https://github.com/niklasso/minisat

Install Instructions

  1. cd to your home directory cd ~
  2. create new folder for git repositories mkdir gitRepos
  3. cd to the newly created folder cd gitRepos
  4. clone this repo to you folder git clone https://github.com/hackrush01/GCPToSAT.git
  5. cd to the repo cd GCPToSAT
  6. run sudo pip3 install -r pip.txt
  7. run using python3 GCP_To_SAT.py <path-to-graph-file>

Note: Complete installation instructions for MiniSat Solver are mentioned in it's respective repository but in short:

  1. cd to your git repo folder created above cd ~/gitRepos
  2. clone minisat git clone https://github.com/niklasso/minisat.git
  3. cd to minisat directory cd minisat
  4. install using sudo make install

How to run

Just install the minisat solver in your preferred linux distro. After that just execute the python file.

Input Format

Make a graph.txt file in the same directory as the git repository or run the program as follows python3 GCP_To_SAT.py <path-to-graph-file>.

It's important to note that the graph text file must adhere to the standard input format i.e.

  1. First line contains exactly one number defining the number of vertices.
  2. After that each line should contain exactly one edge with space separated vertices.(e.g. 5 8, indicates an edge between 5th and 8th vertices)
  3. All edges are 1-indexed.
  4. Since the graph is undirectional, so the edges should not be repeated. It doesn't change the solution but the number of clauses increases, decreasing the performance. One example graph.txt file is included.

About

A simple python code which reduces the Graph Colourablity Problem to Boolean Satisfiability Problem.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages