No description provided.
Pure random number generator written in TypeScript
A small library for generating random numbers
Generate random tokens
TypeScript definitions for brorand
A term-rand function-factory actor
A math util library
Wraps a function so that it's only ever executed once.
A JavaScript implementation of UUID version 7
Simple and complete DOM testing utilities that encourage good testing practices.
This package is for getting latest agents and randomize it
Simple and complete React DOM testing utilities that encourage good testing practices.
A dead-simple module for picking a random item with weights.
Improved randomness without any external dependencies.
Custom jest matchers to test the state of the DOM
URL and cookie safe UIDs
Fire events the same way the user does
Delightful JavaScript Testing.
Delightful JavaScript Testing.
ESLint plugin to follow best practices and anticipate common mistakes when writing tests with Testing Library
Secure random numbers of any size in any base
A simple seeded pseudo-random number generator
Simple and complete React hooks testing utilities that encourage good testing practices.
React package for snapshot testing.
== USAGE: require 'octave' engine = Octave::Engine.new engine.eval "123.456 * 789.101112" engine.rand(10) matrix = Octave::Matrix.new(20, 400) 20.times { |m| 400.times { |n| matrix[m, n] = rand } } engine.put_variable("m", matrix) engine.save "/tmp/20_x_400_matrix" == REQUIREMENTS: * Octave * GCC or some other compiler to build the included extension * Mocha (For testing only)
== USAGE: require 'octave' engine = Octave::Engine.new engine.eval "123.456 * 789.101112" engine.rand(10) matrix = Octave::Matrix.new(20, 400) 20.times { |m| 400.times { |n| matrix[m, n] = rand } } engine.put_variable("m", matrix) engine.save "/tmp/20_x_400_matrix" == REQUIREMENTS: * Octave * GCC or some other compiler to build the included extension * Mocha (For testing only)
**CheapRandom** is a set of tools for pseudo random number generation from arbitrary data. The properties of the **CheapRandom seed** make convenient random number generation possible -- useful for easily repeatable software testing. The **CheapRandom algorithm** is information conserving and generally appears to produce lower chi-squared statistics than **Kernel::rand** i.e. it appears to be more random. The **CheapRandom algorithm**, an original work by Bardi Einarsson, has been in use for 6 years.
== USAGE: require 'matlab' engine = Matlab::Engine.new engine.put_variable "x", 123.456 engine.put_variable "y", 789.101112 engine.eval "z = x * y" engine.get_variable "z" matrix = Matlab::Matrix.new(20, 400) 20.times { |m| 400.times { |n| matrix[m, n] = rand } } engine.put_variable "m", matrix engine.save "/tmp/20_x_400_matrix" engine.close # May also use block syntax for new Matlab::Engine.new do |engine| engine.put_variable "x", 123.456 engine.get_variable "x" end == REQUIREMENTS: * MATLAB * GCC or some other compiler to build the included extension * SWIG (If you want to recompile the SWIG wrapper) * Mocha (For testing only)
GuerrillaRotate ============== This plugin lets you have multiple view pages for the one action, so that you can rotate through different views in order to test which one is the most effective. This is known as A/B testing, split testing or side-by-side testing. It will automatically switch between the different views for different web requests (uses .rand so is pseudo random, not round-robin or anything). The particular view is sticky for a (rails) session, so that once that view has been chosen for that visitor they will see the same, consistent view each time. It integrates automagically into [Rubaidh::GoogleAnalytics](http://github.com/rubaidh/google_analytics) by setting the override_trackpageview to the name of the unique view file (instead of the action-based URL) so you can track it easily in Google Analytics. Without that you'll want to track it by putting different tracking codes in each of your view templates. Example ------- So, in your views you will create some new templates with something (can be anything including nothing) between the template name and the first part of the extension. So you might have the following files for the products/index action: app/views/products/index.html.erb app/views/products/index_alt.html.erb app/views/products/index_new.html.erb Then all you need to do is tell your controller to rotate for that action: ### app/controllers/products_controller.rb class ProductsController < ApplicationController guerrilla_rotate :index, :show # etc.. end NB: guerrilla_rotate is also aliased as guerilla_rotate for the alternative spelling and typos. Copyright © 2009 Jason King, released under the MIT license
== DESCRIPTION: Charlie is a library for genetic algorithms (GA) and genetic programming (GP). == FEATURES: - Quickly develop GAs by combining several parts (genotype, selection, crossover, mutation) provided by the library. - Sensible defaults are provided with any genotype, so often you only need to define a fitness function. - Easily replace any of the parts by your own code. - Test different strategies in GA, and generate reports comparing them. Example report: http://charlie.rubyforge.org/example_report.html == INSTALL: * sudo gem install charlie == EXAMPLES: This example solves a TSP problem (also quiz #142): N=5 CITIES = (0...N).map{|i| (0...N).map{|j| [i,j] } }.inject{|a,b|a+b} class TSP < PermutationGenotype(CITIES.size) def fitness d=0 (genes + [genes[0]]).each_cons(2){|a,b| a,b=CITIES[a],CITIES[b] d += Math.sqrt( (a[0]-b[0])**2 + (a[1]-b[1])**2 ) } -d # lower distance -> higher fitness. end use EdgeRecombinationCrossover, InversionMutator end Population.new(TSP,20).evolve_on_console(50) This example finds a polynomial which approximates cos(x) class Cos < TreeGenotype([proc{3*rand-1.5},:x], [:-@], [:+,:*,:-]) def fitness -[0,0.33,0.66,1].map{|x| (eval_genes(:x=>x) - Math.cos(x)).abs }.max end use TournamentSelection(4) end Population.new(Cos).evolve_on_console(500)