Context
A super fan of Matlab, I’ve used it (mainly the Optimization toolbox) a lot during my PhD study. Later on, after I started my professional job in INRIA and GE, I used mainly C++/C/C#/Python but rarely Matlab. Though Matlab is great, it is, however, too expensive for personal users. That’s why I use often open-source tools such like Numpy, Scipy, Eigen and Maxima in some math-related development works.
I heard the name of Julia in 2017. I felt astonished to learn that this new language combines the interactivity and computational power of Python/Matlab with the speed of C. It is until winter of 2020 that I have time to learn intensively this powerful and promising language. So I would like to share my learning notes here. Stay hungry!
Numbers
For Number
type of Julia, this table in figure below presents the common basic types:
I have made a “Knowldge graph” of all data types in Julia and their relations. Below is a chart of all types (nodes) that are related to Number
type:
My exercise code
1 | # one '#' symbole for a one-line comment, equal to // in C/C++ |
Below is the output that I got:
Official Website:
https://julialang.org/
Cheat sheet:
https://juliadocs.github.io/Julia-Cheat-Sheet/
https://juliadocs.github.io/Julia-Cheat-Sheet/zh-cn/