Julia: a New Alternative to Python and Matlab

The two dominant dynamic programming language environments for numerical computing and graphics are

• the open-source combination of Python with Numpy, Matplotlib, SciPy and other packages, as usef in this course, and

• the older, commercial product Matlab(TM).

Though I generally recommend the former, Matlab is long-established, especially in engineering fields, and arguably has a few advantages, like somewhat simpler notation for matrices and vectors.

One more recent innovation is the Julia language, which for one thing combines many of the virtues of both:

• Like Python, it is open source with some nice modern programming language features (some newer and improving on Python), while also being

• more compatability in its syntax and notation with existing Matlab code and standard linear algebra notation Also, Julia code usually runs faster that either Python or Matlab.

Thus I have started developing a parallel version of this course and book that uses Julia in place of Python, and this section shows off a few drafts of sections of this conversion.

P.S. What does Jupyter mean? e “JuPyteR” is a portmanteau of the names of the three most imortant modern open-source programming tools for scientific computing:

• Julia,

• Python, and

• R (which is for statistical computing).

So in particular, Jupyter notebooks and Jupyter books work fine with Julia, and even with a mix of these languages.

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