A simple way to interact with linear equation
Simple solver of a linear equation system
Linear álgebra and solver of linear equation system
calculates linear equation systems
calculates linear equation systems
This package offers command line tools to + do exact calculations with fractions and integers (add, subtract, cancel) + solve linear equation systems (Gauss alogrithm)
Solve equations using numerical methods, linear álgebra and solver of linear equation system
C++ bindings for all single- and double-precision CLAPACK (Linear Algebra Package) routines.
An astronomical library
The Linear Client SDK for interacting with the Linear GraphQL API
This allows you to add regression lines to any series. Supports: linear, polynomial, logarithmic, exponential and loess. Calculates the r-value
HTTP server cookie parsing and serialization
Use the display-p3-linear color space on the color() function in CSS
A <LinearGradient> element for React Native
Creates an AST parser from a [E]BNF file
Provides a React component that renders a gradient view.
A library to find JS RegExp with super-linear worst-case time complexity for attack strings that repeat a single character.
Node module performing trilateration calculations.
Use double-position gradients in CSS
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The Material Components for the web linear progress indicator component
markdown-it extension for rendering TeX Math
Implementation of Kahan's polynomial root finders for polynomials up to degree 4.
it performs a linear sum assignment even if the cost matrix is rectangular.
Program to solve quadratic and linear modular equations.
An instantiation of the Poseidon SNARK-friendly hash function.
A toolbox of numerical differential equation solvers written in pure Ruby. Currently there are multiple methods available to solve initial value ODEs (Dormand-Prince, Forward Euler, 2nd order Adams-Bashforth), boundary value ODEs (Linear Finite Element Galerkin), 2D Poisson's equation (5-point Laplacian), and the 1D advection equation (Upwind, Lax-Friedrichs, Leapfrog, Lax-Wendroff).
An implementation of a linear regression machine learning algorithm implemented in Ruby. The library supports simple problems with one independent variable used to predict a dependent variable as well as multivariate problems with multiple independent variables to predict a dependent variable. You can train your algorithms using the normal equation or gradient descent. The library is implemented in pure ruby using Ruby's Matrix implementation.
An implementation of a linear regression machine learning algorithm implemented in Ruby. The library supports simple problems with one independent variable used to predict a dependent variable as well as multivariate problems with multiple independent variables to predict a dependent variable. You can train your algorithms using the normal equation or gradient descent. The library is implemented in pure ruby using Ruby's Matrix implementation.
This gem implements: 1.) a logistic map function (#logistic_map), which is a discrete, non-linear, dynamic equation which can show - with proper parameters - chaotic behaviour with super-sensitivity to the initial parameters. Very small changes to initial parameters cause huge changes in the result (can be used as a PRNG as iterated over and over); 2.) A tent-map version of the logistic map (#logistic_points) which returns an array of Nth iterated values of several logistic maps with their initial X0 parameter ranging from 0 to 1 by user defined steps, showing curve-like properties when plotted.
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