The desktop environment is tuned for iterative engineering and scientific workflows. Same goes for SciPy and most of the rest of the scientific Python suite. Can I see your test suite? Logs from the latest continuous integration run? Code coverage? I can for NumPy all 10,000+ tests, on multiple platforms (Windows, MacOS, Linux) and the code coverage. New function interfaces undergo a rigorous design process that typically involves dozens to hundreds of developer-hours per function. The same is true of NumPy and SciPy, many of the names are identical to thier MATLAB equivalents. Function names and signatures are familiar and memorable, making them as easy to write as they are to read.Python development environments for scientific computing lack the reliability and integration of the MATLAB desktop.Įverything about MATLAB is designed specifically for engineers and scientists: Take a look for yourself, in addition to Oliphant, the second largest contributor is Charles Harris a physics major and mathematician (the mother and father disciplines of engineering.), the third largest contributer is David Cournapeau an electrical engineer and data scientist, etc.

While we don't know who exactly is writing Matlab code, the scientific Python packages are developed in the open, on Github, where you can view the profiles of the individual contributors. The initial core developer of both of those packages was Travis Oliphant, an electrical engineer by training, while he was a graduate student and later as a professor of electrical engineering. NumPy and SciPy were developed by engineers. Do they mean to imply that MATLAB is not designed and documented by advanced programmers? The reality is that many of the Python packages for scientific computing, e.g.

The definition of an advanced programmer is imprecise and subjective. Python functions are typically designed and documented by advanced programmers for other experienced programmers. They shouldn’t have to adapt the way they work to fit their tools. They use the following code examples to illustrate their point and even go as far to claim that their is a mistake in the Python operations.Įngineers and scientists deserve tools that fit the way they work. The first claim is that MATLAB code is more readable to scientists and engineers than Python code that performs a similar task. I'll attempt to counter many of those claims in this post. While a few of the claims in the post are true, the vast majority of them are seriously misleading. It is distributed and used typically through a very polished integrated development environment (IDE) and has many add-on toolboxes for a vast array of scientific computing tasks. MATLAB is a useful and powerful computing language and a lot more.

I was recently made aware of a post on the Mathworks website where they compare MATLAB and Python in an attempt to make the case that MATLAB is a superior language for engineering and scientific computation.

The hyperlink to the original post below has been replaced on the Mathworks website with links to Python/Matlab interoperability features. However, there may be other useful tips contained in the notebook, so I am posting it anyway. UPDATE : Mathworks removed the original post this blog was meant to address around the time I completed writing it.

Matlab vs python in dsp