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
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