Apply uniform distribution with location jiggle #3

Manually merged

hloth merged 1 commit from smiludon/grindr-always-online:smiludon-patch-1 into main

2026-07-14 00:18:20 +02:00

smiludon commented

2026-07-13 21:08:42 +02:00

Contributor

The code calculates distance using a uniform linear distribution:
let distance = rand::random_range(0.0..=max_meters);

Because the area of a circle scales with the square of the radius, picking a random radius linearly results in a heavy concentration of points near the center origin. If an algorithm analyzes the cluster of requests, the spatial distribution will look like a highly artificial bullseye rather than realistic human drift.To achieve a uniform distribution across the 5 meter radius disk, the distance calculation must use the square root of a random float between 0 and 1:

let distance = max_meters * rand::random_range(0.0..=1.0_f64).sqrt();

The code calculates distance using a uniform linear distribution: `let distance = rand::random_range(0.0..=max_meters);` Because the area of a circle scales with the square of the radius, picking a random radius linearly results in a heavy concentration of points near the center origin. If an algorithm analyzes the cluster of requests, the spatial distribution will look like a highly artificial bullseye rather than realistic human drift.To achieve a uniform distribution across the 5 meter radius disk, the distance calculation must use the square root of a random float between 0 and 1: `let distance = max_meters * rand::random_range(0.0..=1.0_f64).sqrt();`

smiludon added 1 commit

2026-07-13 21:08:43 +02:00

Apply uniform distribution with location jiggle 09ea20e160

The code calculates distance using a uniform linear distribution:
`let distance = rand::random_range(0.0..=max_meters);`

Because the area of a circle scales with the square of the radius, picking a random radius linearly results in a heavy concentration of points near the center origin. If an algorithm analyzes the cluster of requests, the spatial distribution will look like a highly artificial bullseye rather than realistic human drift.To achieve a uniform distribution across the 5 meter radius disk, the distance calculation must use the square root of a random float between 0 and 1:

`let distance = max_meters * rand::random_range(0.0..=1.0_f64).sqrt();`