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R is both a language and software used for statistical computing and graphing. R was originally developed by Bell Laboratories (Currently known as Lucent Technologies ) by John Chambers . Since R is largely written in C language , users can use C or C++ commands to manipulate R-objects directly.
NuCalc, also known as Graphing Calculator, is a computer software tool made by Pacific Tech. It can graph inequalities and vector fields, and functions in two, three, or four dimensions. It supports several different coordinate systems, and can solve equations. It runs on OS X as Graphing Calculator, and on Windows.
Grace is a free WYSIWYG 2D graph plotting tool, for Unix-like operating systems. The package name stands for "GRaphing, Advanced Computation and Exploration of data." Grace uses the X Window System and Motif for its GUI. It has been ported to VMS, OS/2, and Windows 9*/NT/2000/XP (on Cygwin).
Vector graphics software can be used for manual graphing or for editing the output of another program. Please see: Category:Vector graphics editors; Comparison of vector graphics editors; A few online editors using vector graphics for specific needs have been created.
In it, geometrical shapes can be made, as well as expressions from the normal graphing calculator, with extra features. [8] In September 2023, Desmos released a beta for a 3D calculator, which added features on top of the 2D calculator, including cross products, partial derivatives and double-variable parametric equations.
GNU plotutils is a set of free software command-line tools and software libraries for generating 2D plot graphics based on data sets. It is used in projects such as PSPP and UMLgraph, and in many areas of academic research, [1] [2] [3] and is included in many Linux distributions such as Debian. [4]
Learn how to download and install or uninstall the Desktop Gold software and if your computer meets the system requirements.
As the amounts of collected data and computing power grow (multicore, GPUs, clusters, clouds), modern datasets no longer fit into one computing node. Efficient distributed parallel algorithms for handling large-scale data are required. The GraphLab framework is a parallel programming abstraction targeted for sparse iterative graph