Because it seems to be an arc and not a circle issue that you can solve
the problem by
picking arbitrary two points of your assumed "arc" then construct
(calculate) the perpendicular bisector of
the line between them and do so for another arbitrary two points of the
assumed "arc".
The intersection of the perpendicular lines is the assumed center of the
arc.
If you iterate over all points this should be a pretty good estimation
of the real center.
cheers Chris
Am 18.03.2016 um 18:36 schrieb Barry Rowlingson:
On Fri, Mar 18, 2016 at 2:43 PM, Alex Mandel <tech_...@wildintellect.com> wrote:
library(rgeos)
gCentroid
http://www.rdocumentation.org/packages/rgeos/functions/topo-unary-gCentroid
Assuming its a circle that would be the center.
Only if you have points uniformly (or uniform-randomly) distributed
round the full extent of the circle. From Adrien's plot it looks like
he's got an arc there.
It seems more like a three-parameter optimisation problem. Find x, y,
and r that define the circle that minimises the sum of squared
distances from data points to the circle.
I'm not sure how you'd choose a good initial x,y,r for your optimiser
since I suspect the surface you're optimising over is not unimodal...
You could try taking lots of random samples of three points from your
data and computing the unique circle that fits those points, then
using the mean (or possibly median, there's a fair chance of massive
outliers) value as the initial values.
A quick googling has actually found this little paper on the subject:
http://www.spaceroots.org/documents/circle/circle-fitting.pdf
So I'll shut up now.
Barry
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
