Search Results for "google-visualization-python"
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Showing 11 open source projects for "google-visualization-python"
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ngraph.path
Path finding in a graph
...The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. It can be integrated with visualization libraries like VivaGraphJS to animate or highlight computed paths in a rendered graph, enabling interactive routing features. Its data structures and algorithm choices are optimized for performance and memory efficiency, so even large meshes or road networks can be navigated interactively. With its standalone design, ngraph.path can be used in browser apps, server-side Node.js services. -
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RBush
High-performance JavaScript R-tree-based 2D spatial index
...Spatial index is a special data structure for points and rectangles that allows you to perform queries like "all items within this bounding box" very efficiently (e.g. hundreds of times faster than looping over all items). It's most commonly used in maps and data visualizations. The demos contain visualization of trees generated from 50k bulk-loaded random points. Open web console to see benchmarks; click on buttons to insert or remove items; click to perform search under the cursor. An optional argument to RBush defines the maximum number of entries in a tree node. 9 (used by default) is a reasonable choice for most applications. ... -
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LeetCode Python
LeetCode Solutions: A Record of My Problem Solving Journey
This repository is a comprehensive personal journal of LeetCode problem-solving journey. It includes detailed solutions with code, algorithm insights, data structure summaries, Anki flashcards, daily challenge logs, and future planning sections. -
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ipytracer
Algorithm Visualizer for IPython/Jupyter Notebook
Algorithm Visualizer for IPython/Jupyter Notebook. If you use the display(TracerObject) code from where you want to see, you can use it without any special modification. -
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Illustrated Algorithms
Interactive algorithm visualizations
Inspired by Grokking Algorithms and python-execution-trace, this project aims to reveal the mechanics behind algorithms via interactive visualizations of their execution. Visual representations of variables and operations augment the control flow, alongside actual source code. You can fast forward and rewind the execution to closely observe how an algorithm works. The same code that is displayed next to the illustration is also decorated using babel-plugin-trace-execution and executed to record the context at every step. ... -
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Javascript-Voronoi
JS implementation of Fortune's algorithm to compute Voronoi cells
This repository implements Steven Fortune’s algorithm (sweep-line method) for generating Voronoi diagrams in JavaScript, providing a performant browser-side solution for computational geometry of planar point sets. With this library you can feed a set of sites (points) and compute their Voronoi cells – the partition of the plane into regions closest to each site – in O(n log n) time. It’s especially useful in web UIs, visualizations, interactive maps, and generative-art contexts where you... -
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JSolutions
The solution to all your problems
The Jsolution package is a collection of programs, scripts,libraries and documents that i have written and use in my daily life. -
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Math tools in Python to tackle down problems in Operational Research fields. Comes with a Django based web interface to allow remote access to complex simulation means.
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Free Java Flowchart simulator / interpreter
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GraphScript project is a network theory simulator based purely on Java and Java scripting engines. It is intended to allow fast development, testing and visualization of network theory (graph) algorithms.
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cosmos
Algorithms that run our universe | Your personal library of every algo
Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.
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