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Mathematics Tools Software

Stanford University_080921C
[Stanford University]

 

- Overview

Mathematics software encompasses a wide range of tools for tasks like symbolic computation, numerical analysis, plotting, and document preparation, including popular options such as Mathematica and MATLAB for advanced analysis, GeoGebra and Desmos for dynamic geometry and graphing, and LaTeX for typesetting mathematical documents. 

There are also free and open-source alternatives like SageMath, GNU Octave, and Maxima, as well as specialized apps for problem-solving and online platforms for homework and collaboration. 

1. For General Mathematical Computation:

  • Mathematica: A powerful package for symbolic computation, numerical analysis, and visualization, used in science, engineering, and research.
  • MATLAB: Widely used in engineering and scientific research for numerical computing, data analysis, and simulation.
  • SageMath: A free and open-source system offering a wide range of mathematical functions and tools.
  • GNU Octave: A free software environment that is largely compatible with MATLAB.
  • Maxima: An open-source program for symbolic mathematics, similar in function to Mathematica.
  • SymPy: An open-source computer algebra system written in Python.

 

2. For Geometry, Graphing, and Visualization:
  • GeoGebra: A versatile tool that combines geometry, algebra, spreadsheets, graphing, statistics, and calculus in one package.
  • Desmos: A popular suite of free math tools, including a highly-regarded graphing calculator used globally by teachers and students.
  • gnuplot: A free graphing utility for Windows, macOS, and Linux.


3. For Document Creation and Typesetting:
  • LaTeX: A powerful typesetting system for creating high-quality scientific and mathematical documents, including complex equations and symbols.
  • Overleaf: An online, collaborative platform for writing and editing documents using LaTeX or rich text.


4. For Specific Tasks:
  • Python with Libraries: A versatile programming language with powerful libraries like NumPy (numerical computing), SciPy (scientific computing), and Matplotlib (data visualization).
  • R: A programming language and environment for statistical computing and graphics, frequently used in data analysis and machine learning.
  • Problem-Solving Apps: Apps like Photomath, Mathway, and Wolfram Alpha can solve specific math problems and provide information on mathematical topics. 


Please refer to the following for more information:

 

- The Python Math Library

The Python math library provides us with access to some common math functions and constants in Python that we can use throughout our code to perform more complex math calculations. The library is a built-in Python module, so you don't need any installation to use it. Here are some examples. 

  • import math
  • math.pi
  • math.exp(x) 

 

- SymPy

SymPy (https://www.sympy.org/en/index.html) is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python.

SymPy is…

  • Free: Licensed under BSD, SymPy is free both as in speech and as in beer.
  • Python-based: SymPy is written entirely in Python and uses Python for its language.
  • Lightweight: SymPy only depends on mpmath, a pure Python library for arbitrary floating point arithmetic, making it easy to use.
  • A library: Beyond use as an interactive tool, SymPy can be embedded in other applications and extended with custom functions.


 

[More to come ...]

 

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