medians for degree measurements

[Nobody]

On Fri, 22 Jan 2010 16:09:03 -0800, Steve Howell wrote:

> I just saw the thread for medians, and it reminded me of a problem
> that I need to solve.  We are writing some Python software for
> sailing, and we need to detect when we've departed from the median
> heading on the leg.  Calculating arithmetic medians is
> straightforward, but compass bearings add a twist.
> 
> The numerical median of 1, 2, 3, 4, 5, 6, 359 is 4.  But for
> navigational purposes you would actually order the numbers 359, 1, 2,
> 3, 4, 5, 6, so the desired median heading of the boat is actually 3.
> 
> Of course, you could express 359 better as -1 degrees to north, then
> the sequence would be -1, 1, 2, 3, 4, 5, and 6.  And you'd be good.
> 
> But that trick does not generalize if you go south instead, as you
> have similar issues with -179, 174, 175, 176, 177, 178, and 179.
> 
> Has anybody solved this in Python, either for compass bearings or a
> different domain?  I can think of kind of a brute force solution where
> you keep rotating the sequence until the endpoints are closest
> together mod 360, but I wonder if there is something more elegant.

First, there isn't always a solution; what would you consider to be the
median of [0, 90, 180, 270]?

In the case where the bearings are clustered, one approach is to
convert each bearing from polar to cartesian coordinates, compute the
centroid, then convert back to polar coordinates, i.e.:

	from math import degrees, radians, sin, cos, atan2
	
	def mean(bearings):
		x = sum(sin(radians(a)) for a in bearings)
		y = sum(cos(radians(a)) for a in bearings)
		return degrees(atan2(x, y))

Then, subtract the mean from each bearing, coerce all angles into the
range -180..+180, calculate the median, add the mean, coerce back to
0..360.

	def median(bearings):
		m = mean(bearings)
		bearings = [(a - m + 180) % 360 - 180 for a in bearings]
		bearings.sort()
		median = bearings[len(bearings) / 2]
		median += m
		median %= 360
		return median