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  5. Octave vs SageMath

Octave vs SageMath

OverviewComparisonAlternatives

Overview

SageMath
SageMath
Stacks11
Followers30
Votes0
Octave
Octave
Stacks67
Followers85
Votes15
GitHub Stars144
Forks48

Octave vs SageMath: What are the differences?

Introduction:

Octave and SageMath are both popular mathematical software packages that provide tools for numerical computation, data analysis, and simulations. While they have similarities in terms of functionality and purpose, there are several key differences that set them apart. In this article, we will explore the main differences between Octave and SageMath.

  1. Language Support: Octave is primarily designed for numerical computations and supports a language similar to Matlab. It provides a high-level programming language that is focused on mathematical operations. On the other hand, SageMath is based on Python and supports a wide range of programming paradigms. It combines various mathematical software packages and tools, making it a robust platform for mathematical computations and symbolic mathematics.

  2. Computation Speed: Octave is known for its efficient execution of numerical operations, making it well-suited for large-scale scientific computing. It leverages highly optimized numerical libraries and can handle complex calculations efficiently. On the other hand, SageMath, being based on Python, may be slower in terms of computation speed due to its more generalized nature and the need for interpreting Python code.

  3. Community and Support: Octave has a dedicated user community that actively develops and maintains the software. It has a large repository of user-contributed packages and a comprehensive documentation system. SageMath, being based on Python, benefits from the broader Python community and has access to a vast ecosystem of libraries and resources. This makes it easier to find support, share code, and leverage existing Python tools for various mathematical applications.

  4. Symbolic Mathematics: Octave primarily focuses on numerical computations and lacks native support for symbolic mathematics. It does not have built-in capabilities for handling symbolic expressions and computations. On the other hand, SageMath has robust support for symbolic mathematics, allowing users to perform operations with symbolic variables, manipulate algebraic expressions, and solve symbolic equations. This makes SageMath a more suitable choice for tasks involving symbolic computations.

  5. Visualization and Plotting: Octave provides built-in functions and libraries for creating visualizations and generating plots. It offers a wide range of plotting options and customization features, allowing users to create publication-quality plots. SageMath, being built on Python, also has excellent visualization capabilities. It leverages popular Python libraries such as Matplotlib and provides a rich set of tools for creating high-quality visualizations and interactive plots.

  6. Operating System Compatibility: Octave is developed to run on various operating systems, including Windows, macOS, and Linux. It has a consistent user interface across different platforms, making it easy to use and deploy. SageMath, being based on Python, is also highly compatible with different operating systems and can be run on Windows, macOS, Linux, as well as online through cloud-based services. This compatibility makes both Octave and SageMath accessible to a wide range of users.

**In Summary, Octave and SageMath differ in language support, computation speed, community and support, symbolic mathematics capabilities, visualization and plotting options, and operating system compatibility. Octave is focused on numerical computations and provides a dedicated environment for scientific computing, while SageMath combines various mathematical software packages and leverages Python's broader ecosystem for a wider range of mathematical applications.

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Detailed Comparison

SageMath
SageMath
Octave
Octave

It is a free open-source mathematics software system licensed under the GPL. It builds on top of many existing open-source packages: NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, R and many more.

It is software featuring a high-level programming language, primarily intended for numerical computations. Octave helps in solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB.

A browser-based notebook for review and re-use of previous inputs and outputs, including graphics and text annotations; A text-based command-line interface using IPython; Support for parallel processing using multi-core processors, multiple processors, or distributed computing
Quality Control; Design; Data Visualization; Fluid analysis; Finite element analysis
Statistics
GitHub Stars
-
GitHub Stars
144
GitHub Forks
-
GitHub Forks
48
Stacks
11
Stacks
67
Followers
30
Followers
85
Votes
0
Votes
15
Pros & Cons
No community feedback yet
Pros
  • 8
    Free
  • 4
    Easy
  • 2
    Small code
  • 1
    MATLAB but free
Cons
  • 1
    Not widely used in the industry
Integrations
Python
Python
Plotly.js
Plotly.js
Polyaxon
Polyaxon
Julia
Julia
MATLAB
MATLAB
Python
Python

What are some alternatives to SageMath, Octave?

JavaScript

JavaScript

JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.

Python

Python

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

PHP

PHP

Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.

Ruby

Ruby

Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.

Java

Java

Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!

Golang

Golang

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

HTML5

HTML5

HTML5 is a core technology markup language of the Internet used for structuring and presenting content for the World Wide Web. As of October 2014 this is the final and complete fifth revision of the HTML standard of the World Wide Web Consortium (W3C). The previous version, HTML 4, was standardised in 1997.

C#

C#

C# (pronounced "See Sharp") is a simple, modern, object-oriented, and type-safe programming language. C# has its roots in the C family of languages and will be immediately familiar to C, C++, Java, and JavaScript programmers.

Scala

Scala

Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.

Elixir

Elixir

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.

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