[GRASS-dev] How to calculate mean coordinates from big point datasets?

[Moritz Lennert]

On 18/09/13 10:51, Luca Delucchi wrote:
> On 17 September 2013 22:10, Markus Neteler<neteler at osgeo.org>  wrote:
>> Hi,
>>
>> I came across this question:
>>
>> http://gis.stackexchange.com/questions/71734/how-to-calculate-mean-coordinates-from-big-point-datasets
>>
>> and wondered if this approach would be the fasted:
>>
>> # http://grass.osgeo.org/sampledata/north_carolina/points.las
>> v.in.lidar input=points.las output=lidarpoints -o
>> ...
>> Number of points: 1287775
>> ...
>>
>> Now I would use
>> v.univar -d lidarpoints type=point
>>
>> (still calculating here...)
>>
>> Is it the best way?
>>
>
> maybe v.median [0] could help?
>
>
> [1] http://trac.osgeo.org/grass/browser/grass-addons/grass7/vector/v.median

Right.

Here's a little test:

$time v.median in=elev_lid792_randpts
638648.500000|220378.500000

real	0m0.249s
user	0m0.180s
sys	0m0.044s

$time v.to.db elev_lid792_randpts op=coor -p | awk -F'|' 'BEGIN{SUMX=0; 
SUMY=0; N=0} {N+=1;SUMX+=$2;SUMY+=$3} END{print SUMX/N, SUMY/N}'
Reading features...
  100%
638544 220339

real	0m0.106s
user	0m0.100s
sys	0m0.020s

Would be interesting to see results for big data. And AFAIK median is a 
bit more difficult to do in awk. I imagine that replacing the median by 
the mean in numpy is no problem (might be a flag to add to v.median).


I didn't try v.points.cog as that actually creates a new vector map.

Moritz