Compute the euclidean distance between two vectors
Calculate the Euclidean distance between two points
Computes the L2 norm (Euclidean norm) of an array of values.
compute the least common multiple using Euclidean algorithm
Calculate the Euclidean distance been two points in 2D/3D/nD space.
TypeScript definitions for euclidean-distance
Euclidean geometry classes and tools for JavaScript
Calculates the patterns based on the euclidean/bjorklund's algorithm
Euclidean vector library written in JavaScript
g2o Euclidean Geometry Utilities
Euclidean Geometry Utilities
GCD + Euclidean algorithm
Finds the closest color name to a given hex, rgb and hsl color (with and without alpha). It uses the Euclidean distance formula to calculate the distance between colors in the RGB color space
Get Euclidean distance between arrays.
High-performance WebGL scatter plot renderer for Euclidean, Hyperbolic, and non-Euclidean embeddings.
huffman + Euclidean algorithm
Calculate euclidean distance in arbitrary dimensions
Computes the Euclidean distance between two arrays.
Compute the squared Euclidean distance between two double-precision floating-point strided arrays.
Traditional music rhythms (Euclidean/Bjorklung algorithm)
Interactive Euclidean geometry constructions in the browser — a TypeScript port of David E. Joyce's 1996 Java Geometry Applet.
Euclidean pattern generator
Compute the Euclidean distance between two double-precision floating-point strided arrays.
Euclidean geometry in javascript.
A collection of operations for euclidean geometry in three dimensions.
Generate Euclidean rhythms using Bjorklund's algorithm - musically interesting patterns for percussion and generative music
Pure-Rust implementation of Hierarchical Navigable Small World (HNSW) approximate nearest-neighbour search
Multivector and MultiField implementation for DeepCausality
Generic distance and similarity metrics for machine learning
Portable mixed-precision BLAS-like vector math library for x86 and ARM
A rust library to provide distances for multidimensional arrays
implements modular inversion based on the paper: `fast constant-time gcd computation and modular inversion` by Daniel J. Bernstein and Bo-Yin Yang.
Implementation of the euclidean algorithm to find the greatest common divisor.
This library computes the greatest common divisor of 2 natural numbers and 2 additional numbers such that gcd(a,b)=s·a+t·b holds.
Fast and accurate geographic distance calculations with geodesic, haversine, and euclidean algorithms
Profile Python hotspots and auto-generate Rust + PyO3 stubs via maturin
Basic Geometric primitives and algoritms for Ruby
Generates sequences of hits spaced as evenly as possible across given pulses using the Euclidean algorithm.
Uses KMeans clustering and the L*A*B* colorspace to extract "approximate human vision" dominant colors from an image. Optionally, use Euclidean Distance to map those dominant colors into preferred "color bins" for a search index facet-by-color solution.
Newtonian physics gives a way to predict the future state of a system of massive objects in a Euclidean space. This gem provides a library of classes such as Point, Vector, Force. This gem enables a system built from these classes to be evolved forward in time according to Newton's laws of motion.
A Ruby gem for converting between 19 geodetic coordinate systems (LLA, ECEF, UTM, ENU, NED, MGRS, USNG, Web Mercator, UPS, State Plane, BNG, GH36, GH, HAM, OLC, GEOREF, GARS, H3, S2) with Vincenty great-circle and ECEF Euclidean distance calculations, unit-aware Distance and Bearing classes, geoid height support, and geographic area operations.
Hanny is a Hash-based Approximate Nearest Neighbor (ANN) search library in Ruby. Hash-based ANN converts vector data into binary codes and builds a hash table by using the binary codes as hash keys. To build the hash table, Hanny uses Locality Sensitive Hashing (LSH) of approximating cosine similarity. It is known that if the code length is sufficiently long (ex. greater than 128-bit), LSH can obtain high search performance. In the experiment, Hanny achieved about twenty times faster search speed than the brute-force search by Euclidean distance.
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