D3 plugin which computes a Weighted Voronoi tesselation
A dead-simple module for picking a random item with weights.
Toggle current selected content in browser
Data-driven DOM manipulation: select elements and join them to data.
TypeScript definitions for d3-selection
Animated transitions for D3 selections.
ProseMirror's rowspan/colspan tables component
Spectrum UI components in React
This package contains utilities and helpers for handling Lexical selection.
Select a one- or two-dimensional region using the mouse or touch.
Spectrum UI components in React
Interactive Selection Component for Victory
Core logic for the cascade-select widget implemented as a state machine
Miscellaneous graph metrics for graphology.
TypeScript definitions for d3-brush
TypeScript definitions for d3-drag
Miscellaneous indices for graphology.
A random weighted item chooser with custom seed option for JavaScript and TypeScript.
Sortition pool is a logarithmic data structure used to store the pool of eligible operators weighted by their stakes. In the Keep network the stake consists of staked KEEP tokens. It allows to select a group of operators based on the provided pseudo-rando
TypeScript definitions for d3-zoom
Node.js module to make a random choice among weighted elements of table.
TypeScript definitions for d3-transition
DOM utilities module for WordPress.
TypeScript definitions for d3-axis
Simple, weighted selection of items.
Gem for selecting items by weight
A simple library for obtaining weighted randomized selections
When the method `select_from_hash_list` is given an array of hashes where the value of each hash is a weight, the gem will take that into account and select a value at random.
Provides a method to select a element by weighted randomization from a hash with weights.
Selectivity.js is a modular and light-weight selection library for jQuery and Zepto.js. This gem integrates Selectivity.js with Ruby on Rails.
Proper related posts plugin for Jekyll - uses document correlation matrix on TF-IDF (optionally with Latent Semantic Indexing). Each document is tokenized and stemmed, every word found is treated as keyword for analysis (except for some stop words). TF-IDF matrix for the whole site is calculated (including extra provided weights), then if given accuraccy is lower than 1.0, LSI algorithm is used to compute new simplified vector space. Document correlation matrix is created using dot product of the matrix and its transpose. For each of the post' related documents are inserted into priority queue (sorted by score from document correlation matrix), assuming the score is greater than minimal required score. Selected few bests related posts are retrieven from the queue. Liquid template for each post is rendered and <related-posts /> is replaced with the outcomes of algorithm.
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