Osório

Osório is a city in the Grande Porto Alegre region of Rio Grande do Sul.

Osório

Understand

Get in

By car

Get around

See
Lagoa Pinguela
Osório Falls
  • Balneário Atlântida Sul. 
  • Balneário Mariápolis. 
  • Lagoa Pinguela. 
  • Leonel Montovani Anthropology Museum of Osório (Museu Antropológico de Osório Leonel Montovani). 
  • Marechal Manoel Luis Osório Historical Park (Parque Histórico Marechal Manoel Luis Osório). 
  • Osório Falls (Cascata Osório). 
  • Praça das Carretas. 
  • Railroad Museum (Museu da Via Férrea). 

Do

Buy

Eat

Drink

Sleep

Connect

Go next
Routes through Osório

São José do Norte ← Palmares do Sul ←  S  N  → Maquiné → Criciúma
Uruguaiana ← Porto Alegre ←  W  E  → Start of Road
Start of Road ←  W  SE  → Tramandaí


gollark: It allocates memory and doesn't consider it a side effect.
gollark: I didn't do any horrible homoglyph hacks with THAT.
gollark: It uses the function, yes.
gollark: So, I finished that to highly dubious demand. I'd like to know how #11 and such work.
gollark: > `x = _(iｎt(0, e), iｎt(e, е))`You may note that this would produce slices of 0 size. However, one of the `e`s is a homoglyph; it contains `2 * e`.`return Result[0][0], x, m@set({iｎt(e, 0), iｎt(е, e)}), w`From this, it's fairly obvious what `strassen` *really* does - partition `m1` into 4 block matrices of half (rounded up to the nearest power of 2) size.> `E = typing(lookup[2])`I forgot what this is meant to contain. It probably isn't important.> `def exponentiate(m1, m2):`This is the actual multiplication bit.> `if m1.n == 1: return Mаtrix([[m1.bigData[0] * m2.bigData[0]]])`Recursion base case. 1-sized matrices are merely multiplied scalarly.> `aa, ab, ac, ad = strassen(m1)`> `аa, аb, аc, аd = strassen(m2)`More use of homoglyph confusion here. The matrices are quartered.> `m = m1.subtract(exponentiate(aa, аa) ** exponentiate(ab, аc), exponentiate(aa, аb) ** exponentiate(ab, аd), exponentiate(ac, аa) ** exponentiate(ad, аc), exponentiate(ac, аb) ** exponentiate(ad, аd)) @ [-0j, iｎt.abs(m2.n * 3, m1.n)]`This does matrix multiplication in an inefficient *recursive* way; the Strassen algorithm could save one of eight multiplications here, which is more efficient (on big matrices). It also removes the zero padding.> `m = exponentiate(Mаtrix(m1), Mаtrix(m2)) @ (0j * math.sin(math.asin(math.sin(math.asin(math.sin(math.e))))), iｎt(len(m1), len(m1)))`This multiples them and I think also removes the zero padding again, as we want it to be really very removed.> `i += 1`This was added as a counter used to ensure that it was usably performant during development.> `math.factorial = math.sinh`Unfortunately, Python's factorial function has really rather restrictive size limits.> `for row in range(m.n):`This converts back into the 2D array format.> `for performance in sorted(dir(gc)): getattr(gc, performance)()`Do random fun things to the GC.
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