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SymPy is an open-source Python library for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.
In computer science, a symbolic language is a language that uses characters or symbols to represent concepts, such as mathematical operations and the entities (or operands) on which these operations are performed. [1] Modern programming languages use symbols to represent concepts and/or data and are, therefore, examples of symbolic languages. [1]
Variables are defined using the assignment operator, =. MATLAB is a weakly typed programming language because types are implicitly converted. [39] It is an inferred typed language because variables can be assigned without declaring their type, except if they are to be treated as symbolic objects, [40] and that their type can change.
Symbolic Math Toolbox MathWorks: 1989 2008 9.4(2018a) 2018: $3,150 (Commercial), $99 (Student Suite), $700 (Academic), $194 (Home) including required Matlab: Proprietary: Provides tools for solving and manipulating symbolic math expressions and performing variable-precision arithmetic. SymPy: Ondřej Čertík 2006 2007 1.13.2: 11 August 2024: Free
In computer programming, symbolic programming is a programming paradigm in which the program can manipulate its own formulas and program components as if they were plain data. [ 1 ] Through symbolic programming, complex processes can be developed that build other more intricate processes by combining smaller units of logic or functionality.
In computer science, symbolic execution (also symbolic evaluation or symbex) is a means of analyzing a program to determine what inputs cause each part of a program to execute. An interpreter follows the program, assuming symbolic values for inputs rather than obtaining actual inputs as normal execution of the program would.
Examples of symbolic computations are given below. Maple incorporates a dynamically typed imperative-style programming language (resembling Pascal), which permits variables of lexical scope. [3] There are also interfaces to other languages (C, C#, Fortran, Java, MATLAB, and Visual Basic), as well as to Microsoft Excel.
Evolutionary Forest is a Genetic Programming-based automated feature construction algorithm for symbolic regression. [15] [16] uDSR is a deep learning framework for symbolic optimization tasks [17] dCGP, differentiable Cartesian Genetic Programming in python (free, open source) [18] [19]