Chris Rackauckas released this excellent cheatsheet (Scientific Modeling Cheatsheet – MATLAB – Python – Julia Quick Reference) which shows, for those who are not already convinced, that Julia not only brings the better of two worlds in terms of user accessibility and syntax (Matlab, Python) but also provides (among others) seamless and advanced automatic differentiation features. I thought that this cheatsheet diserved a new column, as Scilab and Matlab share more features and language idioms than one could think, hence I made an upgraded version with a “Scilab” column which can be found there: Scientific Modeling Cheatsheet – MATLAB – Scilab - Python – Julia Quick Reference. Compared to the original version of the sheet you can easily hide/show columns if you want to compare e.g. only two softwares. As a teaser, here is a screenshot of a section of the sheet:
Hello Stephane, it seems some blanks left during the merge of reference with Chris Rackauckas’s reference, around sort and eigenvalues ,missing gsort and eigs for Scilab ?
I’m happy as well and grateful to Scilab developers for the development of the extension of objects features in Scilab !
At the moment the question arises in my job to translate in Scilab existing Matlab or Python interfaces/gateways to experimental databases and these gateways are using objects features extensively, in Matlab and Python respectively. Then, in order to choose the most straight approach, I’m wondering which from Matlab or Python gateway is likely to deploy the objects features concepts the closest to Scilab ones, and highlighting the differences. And it comes to my minf that it could be more or less an interesting extension to languages’ objects features of the current Matlab/Scilab/Python/Julia cheatsheet : I’m not familiar with Matlab objects philosophy nor Python ones, do someone already have answers about that ?
Part of the the information would also suit well in the Scilab documentation at the Code Matlab => Scilab entry, also to be extended with the new Objects in Scilab features.
