The title would probably be confusing, but I could not make it better than this. I noticed that most programming languages are limited to the alphanumerical set along with the special characters present in a general keyboard. I wondered if this posed a barrier for developers on what characters they were limited to program in, or if it was intentional from the start that these keys would be the most optimal characters for a program to be coded in by a human and was later adopted as a standard for every user. Basically, are the modern keyboards built around programming languages or are programming languages built around these keyboards?
C supports alternate ways of typing some of its punctuation, for programmers whose keyboards didn’t support them all. For example, if you can’t type
[ ]
you can use??( ??)
instead. (There are other ones that use angle brackets, but I can’t type them here because Lemmy escapes them incorrectly. Irony.)https://en.wikipedia.org/wiki/Digraphs_and_trigraphs#C
The usual example of a programming language using especially unusual characters is APL, where all built-in functions are all represented by single characters, mostly drawn from mathematical notations, Greek alphabet, and so on. For example,
⍋
is the “sort” function.deleted by creator
The core of that Life expression works by taking the array of cells and shifting it in the eight different directions, then summing those arrays to get the population counts.
I tried translating this into Python — but I’ve never written
numpy
code before, so this is probably less efficient than it could be. But it does work and you can see a glider move through a few generations.The array-shifting logic is in the
populations
function, withnp.roll
being the equivalent of the APL rotate operation (written as⌽
and⊖
in the original).import numpy as np def alive(popu, cell): return int(popu == 3 or (popu == 4 and cell)) alive = np.frompyfunc(alive, 2, 1) def populations(grid): return np.array( [ np.roll(r1, shift, 1) for shift in [-1, 0, 1] for r1 in (np.roll(grid, shift, 0) for shift in [-1, 0, 1]) ] ).sum(axis=0) def nextgen(grid): return alive(populations(grid), grid) grid = np.array([[0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 0, 0], [0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]]) for gens in range(5): print(grid) grid = nextgen(grid) print(grid)
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