The problem is that a lot of the people that attend sporting events come from the 905 areas outside of TTC service. There are commuter trains to those areas, but they taper off as the limits of “working late” are hit.

Oh, maybe! I didn’t understand how it chose the points, but it does look like the random convergence approach.

Nice, thanks!

I’m disappointed that none of them seem to have gone with the random convergence approach.

Set the three corners of an equilateral triangle. Pick a random starting point on the canvas. Every iteration, pick a random corner from the triangle and your next point is the midpoint between the current point and that corner. While the original point is almost guaranteed not to be a point in Sierpinski’s triangle, each iteration cuts the distance between the new point and the nearest Sierpinski point in half.

If you start plotting points starting with (say) the 50th one, every pixel is “close enough” to a Sierpinski point that you see the triangle materialize out of nothing. The whole thing could be programmed in about 20 lines of QBasic on DOS 30 years ago.

I may be remembering incorrectly, but after the 2019 Supreme Court ruling that federal courts can’t address partisan gerrymandering, a couple of blue states (New York and Illinois maybe?) tried doing some gerrymanders after the 2020 census. Then their state courts struck them down.

Several blue states – I think Washington and Oregon are among them – created non-partisan redistricting commissions before 2019, so they can’t be gerrymandered.

They installed efficiency modules to reduce biter expansion?

The article summary in the post explains that it will be transferred to the Trump Presidential Library Foundation just before he leaves office. So it won’t be available for future presidents.