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Comment by ErroneousBosh | Hacker News Reader

I absolutely love how full Wikipedia is of completely useless pages like the Vincenty's Formulae one, where someone has just gone "look this is what it says in my maths textbook" without any explanation.

No discussion of why you'd use this over for example the Haversine function, of course, just a straight out copypasta and a demonstration of how clever someone is at the mathematical notation markup.

Incidentally you'd use this instead of Haversine if you wanted to be really really accurate down to millimetres across a long baseline, as opposed to lots and lots of "it's ten miles that way in a straight line" very quickly and simply.

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Writing full articles takes time and effort. But the effort is cumulative, so these stub articles are really just the start. Some of the comment you made here would definitely improve the article. You are always welcome to edit and improve Wikipedia. I mean this literally and sincerely, it is one of the few places on the internet where you might benefit from posting.

it is quite telling that wikipedia has pages upon pages documenting pokemon, but relatively limited context about maths or science, beyond what's in textbooks.

Telling what? STEM academics are busier than Pokémon fans to contribute to Wikipedia? Or they care less about the cause of Wikipedia? That as a society we produce more of the latter than the former? There’s no definitive rationale to be told simply by that observation.

It's not a "stub article" though, it's just a paragraph and then a bunch of stuff plagiarised from a maths textbook.

I already edit quite a bit on Wikipedia. I stay away from the maths bits, because it's a little outside my area of expertise - and because it's just things like "it's a function to calculate distance, and here's ten pages of algebra with no explanation" I can't really improve that on Wikipedia.

It would sure be better if it had some concrete explanations and examples why vincenty is preferred. It's also barely any more computational load on modern computers so very little reason not to use it.

Haversine is strongly deprecated in even short distance applications like planning a 35 km point to point licensed band radio microwave link, because you risk having both slightly the wrong distance and the azimuth figure being off by a tenth of a degree.

Vincenty in python form is quite compact. Karney by comparison is something like 1000 lines of code. And the difference is going between like a few mm precision to nanometers.

I've actually implemented Haversine in a SQL query to find what can be summed up as "which of these moving things is closest to this thing right now". It's not the tidiest, and I had to ask someone better at SQL than I am to make it entirely work, but it looks like it is easier than doing Vincenty.

I should try it, right?

Edit: I also wonder what's to be gained by being accurate to nanometres over the surface of a fairly inaccurate planet.

My application was to locate movable things to identify which was nearest to a moorland wildfire, where you need to be accurate to within about 1km at best - you don't need to drop the pin right on it, you'll know where you're going when you see it ;-)

For that application you needn't have bothered. On a sphere arc-length and Euclidean distance are monotonically related, so the minimizer would not have changed.

You might enjoy the much longer and more detailed article https://en.wikipedia.org/wiki/Geodesics_on_an_ellipsoid which discusses the context.

I've read that, quite some time ago, which is how I understand how the Haversine function works. Kind of. A bit. Enough to make it work, anyway.

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