α₁ \alpha<TAB>\_1<TAB>
vₓ v\_x<TAB>
H₀ H\_0<TAB>
χ² \chi<TAB>\^2<TAB>
Aᵀ A\^T<TAB>
When I went to do the python demo above, IPython also tab-completed the `\alpha` above... but to get the ₁ the quickest and easiest way for me to get it was in my Julia editor.Fair enough in some contexts, but I don’t find that to be the nicest general-audience feature. YMMV.
help?> α
"α" can be typed by \alpha<tab>
Code is for reading much more than writing — especially for a new person. I maintain that matching the canonical form of
the algorithm I'm implementing will help them gain their feet faster.Good example:
https://github.com/JuliaStats/Distances.jl/blob/c21aab0fae30...
vs.
https://www.npmjs.com/package/haversine-geolocation#introduc... (note the mathematical formula on that page and the JS code compared to Julia's)
Sure someone can pattern-match the code to the already-derived line in a reference book somewhere, but that doesn’t help at all with reasoning about the geometrical relationships or developing new algorithms, following control flow, building abstractions, improving precision, handling edge cases, ...
It’s mostly helpful when you want to treat your formulas as an externally defined black box.
* * *
Aside: The problem in this particular example is that spherical coordinates and spherical trigonometry are just not a very good formalism for calculating anything, in either theory or practice. Unfortunately cartography, geodesy, etc. are bound by tradition and there hasn’t been much effort to switch them to better tools.
I’ve been trying to read a spherical trigonometry textbook (Todhunter, 1878) the last few days and following along is a huge pain.
Much better is to switch to cartesian coordinates or stereographically projected coordinates, and then use vector methods (and skip writing explicit coordinates in your code to the extent possible). All of the proofs and derivations get nicer, with geometrically meaningful steps and conclusions. Now your points can just be called p and q or a and b (or if you have a lot of them and aren’t pressed for space in each expression, points[i] and points[i+1]), and the coordinates stay internal.
In addition to using clearer code, the calculations will also be faster, more precise, with better numerical stability, take up less memory/bandwidth, ...
Here’s some general math for an arbitrary-dimensional sphere; for just the 2-sphere everything is simpler. http://geocalc.clas.asu.edu/pdf/CompGeom-ch3.pdf
The point isn't the algorithm itself. The point is just how using unicode allows you to match the style of an arbitrary algorithm out of a textbook.
In general I see code or explanations relying on Greek letters as no better than ones with English words for names.
That's a lot of information for such a compact representation. And that's mostly unconscious, which is great. I really found the Julia example above to be far, far easier to understand than the linked JS (though I think that JS was not particularly great).
To me, it seems like it'd be nice-to-have, but alone, I don't think it would be enough to make me switch languages.
I mean everyone who uses my python code is going to have to be trained in pip, virtualenv, mypy, sphinx, and git. Anyone editing code written by and for mathematicians or scientists is going to know LaTeX, it's like the html of academia.
And as pointed out, you don't need any IDEs, this is even supported in the REPL. And using a specialized editor for a language/environment is hardly unusual (not that it's needed).