Improve random sorting algorithm

[DingDongSoLong4]

This implements a new random sorting algorithm, which is both faster and "more random" than the previous implementation.

These are performance numbers I get for the initial SQL query of a random sort on the images page, using a database of ~2.5M images:

	Time	SQL
Before	650-680ms	SELECT DISTINCT images.id FROM images ORDER BY (substr(images.id * 0.1583058238029480, length(images.id) + 2)) ASC, COALESCE(images.title, images.id) COLLATE NATURAL_CI ASC LIMIT 40 OFFSET 0
After	250-280ms	SELECT DISTINCT images.id FROM images ORDER BY mod((images.id + 15830583) * (images.id + 15830583) * 52959209 + (images.id + 15830583) * 1047483763, 2147483647) ASC, COALESCE(images.title, images.id) COLLATE NATURAL_CI ASC LIMIT 40 OFFSET 0
Created At	150-170ms	SELECT DISTINCT images.id FROM images ORDER BY images.created_at ASC, COALESCE(images.title, images.id) COLLATE NATURAL_CI ASC LIMIT 40 OFFSET 0

I've included a sort on Created At as comparison, since that column is not indexed and thus SQLite needs to do a full table scan, like it does for a random sort.

As for the randomness, the previous algorithm was effectively doing rand = images.id * seed % 100000000. If you plot a graph of id vs rand, the pattern that results from this is extremely obvious. As a result, many seed values produce terrible results. Some particularly bad seeds I found: 10000005, 11111111, 55555555, 99999995 (use in e.g. http://localhost:9999/scenes?sortby=random_{seed}). Those are admittedly a bit contrived, but I've definitely come across bad seeds randomly while using stash normally several times.

I've "borrowed" the new algorithm from a comment on StackOverflow here. Its values are far more random when plotted, and give far better output, with no "broken" seed values.

As I mention in a comment, ideally we'd be using a custom function, since that would allow the use of uints and overflow rather than floats, but that was much slower than even the previous algorithm in my testing.