1.MATLAB
MATLAB (Matrix Laboratory) is a powerful numerical computing and scientific programming software. It provides a wealth of mathematical functions and tools for data analysis, algorithm development, signal processing, image processing, control system design, simulation and other application fields.
MATLAB has an intuitive syntax that enables users to quickly perform numerical calculations and data visualization. Users can use MATLAB to perform vector and matrix operations, numerical integration, symbolic calculations, linear algebra operations, and more. In addition, MATLAB also has rich drawing functions, users can draw 2D and 3D graphics, make animation and visualization effects.
In terms of algorithm development, MATLAB provides many built-in functions and toolboxes for mathematical modeling, optimization, machine learning, deep learning, etc. Users can use MATLAB to quickly implement and test various algorithms, and perform tuning and analysis on them.
MATLAB also supports integration with other programming languages (such as C++, Python, etc.), and users can share data and call functions in different programming environments through the MATLAB engine interface. In addition, MATLAB also has a rich toolbox and applications for problem solving and research in specific domains.
2.Python
Python is a widely used high-level programming language and an open source, extensible software development platform. It has concise and easy-to-read syntax and powerful functions, and is widely used in data science, machine learning, artificial intelligence and other fields. It has powerful data processing and analysis capabilities, and provides many libraries for machine learning and deep learning, such as NumPy , Pandas , Matplotlib , Scikit-learn , etc.
In order to better use python for programming, several commonly used software have emerged to provide users with a better programming experience.
2.1 Anaconda
Anaconda is a popular Python data science platform. It is an open source distribution that integrates a Python interpreter and a large number of commonly used scientific computing and data processing libraries. Anaconda aims to provide an environment that is easy to install, manage and use scientific computing tools, especially for data scientists and researchers.
Anaconda software also includes JupterNotebook and Spyder, among which JupterNotebook is often used for data analysis related work.
2.2 PyCharm
PyCharm is a Python integrated development environment ( IDE ) developed by JetBrains . It aims to provide a feature-rich and user-friendly development environment that enables developers to write, debug, and test Python code more efficiently.
2.3 VS Code
Visual Studio Code ( VS Code for short ) is a lightweight, cross-platform integrated development environment ( IDE ) developed and maintained by Microsoft. It supports multiple programming languages and provides rich functions and plug-in extensions for various development tasks.
3.Lingo
LINGO is a mathematical programming and optimization modeling tool, which is used to solve mathematical optimization problems such as linear programming, integer programming, and nonlinear programming. LINGO provides an intuitive interface and a powerful solution engine, enabling users to quickly build mathematical models and find optimal solutions.
4. Data analysis software: SPSS, R, etc.
SPSS (full name Statistical Package for the Social Sciences , Chinese name is Social Science Statistical Software) is a widely used statistical analysis software, especially suitable for data processing and analysis in the field of social sciences.
R language is an open source programming language and environment dedicated to data analysis, statistical modeling and visualization. It provides a wealth of statistical and data processing functions, widely used in academic research, data science, business analysis and big data fields.
5. Equation editor: MathType and AxMath
Mathtype and AxMath are different from the formula editors that come with Word, and are more convenient to use. However, the genuine versions of these two softwares have to be charged. In comparison, the cost of AxMath is lower, so it may be better for students to use.
For more content, please go to the official account at the end of the article.