Glynn Clements wrote:
>
> Markus Metz wrote:
>
>> Please try the new addon v.centerpoint [0]. It calculates various
>> center points for point clouds, lines, and areas. Standard options are
>> the geometric mean (center of gravity)
>
> That's the arithmetic mean.
>
> The geometric mean of a set of
Markus Metz wrote:
> Please try the new addon v.centerpoint [0]. It calculates various
> center points for point clouds, lines, and areas. Standard options are
> the geometric mean (center of gravity)
That's the arithmetic mean.
The geometric mean of a set of N values is the Nth root of the pro
On 22/09/13 17:06, Markus Metz wrote:
Markus Neteler wrote:
Hi,
I came across this question:
http://gis.stackexchange.com/questions/71734/how-to-calculate-mean-coordinates-from-big-point-datasets
Please try the new addon v.centerpoint [0]. It calculates various
center points for point clouds
Moritz:
> 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).
see the old r.univar.sh shell script for an idea of how to get a me
Hamish wrote:
> see also the v.points.cog addons script:
> http://grasswiki.osgeo.org/wiki/AddOns/GRASS_6#v.points.cog
>
> although I haven't tried it for anything as big as lidar data.
oops, I completely forgot to mention the r.cog addon script too:
https://trac.osgeo.org/grass/browser/gr
Markus Neteler wrote:
> Hi,
>
> I came across this question:
>
> http://gis.stackexchange.com/questions/71734/how-to-calculate-mean-coordinates-from-big-point-datasets
Please try the new addon v.centerpoint [0]. It calculates various
center points for point clouds, lines, and areas. Standard optio
On Fri, Sep 20, 2013 at 5:38 PM, Markus Metz
wrote:
> Glynn Clements wrote:
>>
>> Luca Delucchi wrote:
>>
>>> maybe v.median [0] could help?
>>
>> Not for large datasets. First, it requires that the data will fit into
>> RAM. Second, numpy.median() sorts the entire array and takes the
>> middle va
Glynn Clements wrote:
>
> Luca Delucchi wrote:
>
>> maybe v.median [0] could help?
>
> Not for large datasets. First, it requires that the data will fit into
> RAM. Second, numpy.median() sorts the entire array and takes the
> middle value, which is somewhere between O(n.log(n)) for the typical
> c
Luca Delucchi wrote:
> maybe v.median [0] could help?
Not for large datasets. First, it requires that the data will fit into
RAM. Second, numpy.median() sorts the entire array and takes the
middle value, which is somewhere between O(n.log(n)) for the typical
case and O(n^2) for the worst case (n
On Thu, Sep 19, 2013 at 2:32 PM, Markus Metz
wrote:
...
> I am not sure. For areas without isles, there is a faster alternative.
> For areas with isles, the current approach is fast, but the centroids
> might be placed at somewhat unexpected locations (the next best
> location inside the area, out
On Thu, Sep 19, 2013 at 9:15 AM, Moritz Lennert
wrote:
> On 18/09/13 16:24, Markus Metz wrote:
>>
>> Moritz Lennert wrote:
>>> Here's a little test:
>>>
>>> $time v.median in=elev_lid792_randpts
>>> 638648.50|220378.50
>>
>>
>> Should be 638648|220378. It seems that numpy gets the median
On 18/09/13 16:24, Markus Metz wrote:
On Wed, Sep 18, 2013 at 11:41 AM, Moritz Lennert
wrote:
On 18/09/13 10:51, Luca Delucchi wrote:
On 17 September 2013 22:10, Markus Neteler wrote:
Hi,
I came across this question:
http://gis.stackexchange.com/questions/71734/how-to-calculate-mean-c
On Wed, Sep 18, 2013 at 11:41 AM, Moritz Lennert
wrote:
> On 18/09/13 10:51, Luca Delucchi wrote:
>>
>> On 17 September 2013 22:10, Markus Neteler wrote:
>>>
>>> Hi,
>>>
>>> I came across this question:
>>>
>>>
>>> http://gis.stackexchange.com/questions/71734/how-to-calculate-mean-coordinates-fro
On 18/09/13 10:51, Luca Delucchi wrote:
On 17 September 2013 22:10, Markus Neteler 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
On 17 September 2013 22:10, Markus Neteler 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_c
On 18/09/13 00:10, Markus Neteler 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.i
Markus Neteler wrote:
> I came across this question:
>
> http://gis.stackexchange.com/questions/71734/how-to-calculate-mean-coordinates-from-big-point-datasets
so wants to find the average coordinate?
> and wondered if this approach would be the fasted:
>
> # http://grass.osgeo.org/sampledata/
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
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