[GRASS-dev] About v.distance, v.what.vect (wrt "count points within...").

[Moritz Lennert]

On 10/08/10 15:17, Moritz Lennert wrote:
> On 10/08/10 13:49, Nikos Alexandris wrote:
>> Markus M:
>>
>>> If a point is inside an area (the polygon composed of the area's
>>> boundaries), the distance is 0 (zero):
>>
>> This sentence makes me think that it is a priori known (based on
>> something
>> else - related to topology?) when a point is inside an area. Why all
>> the need
>> to measure distances then in order to count how many points are inside?
>
> As you can see in the code referenced by Markus, there is a
> Vect_point_in_area(), so yes, it is possible to more directly check if
> points are in areas. It all depends on which modules were written using
> this function. At this stage all point-in-polygon attempts in GRASS are
> scripts using workarounds...

As a follow-up:

The counting points in polygons algorithm I prefer at this stage is 
(using municipal boundaries and hospitals in the NC data set with an 
SQLite backend - DBF won't work):

g.copy hospitals,myhospitals
v.db.addcol myhospitals col="cat_municip int"
v.distance from=myhospitals at sqlite to=boundary_municp at PERMANENT 
upload=cat column=cat_municip dmax=0.0
db.select sql="select cat_municip, count(*) from myhospitals group by 
cat_municip"

If your hospital attribute table contains number of beds (nbeds), the 
you could sum the number of beds as such:

db.select sql="select cat_municip, sum(nbeds) from myhospitals group by 
cat_municip"

etc...

Using 6.5 to test a similar case to yours (I assume):

g.region vect=boundary_municp

v.random out=mypoints n=600000

v.db.addtable mypoints col="cat int, cat_municip int" (that's veeeeery 
slow, probably because of 600000 update statements to the database in 
the v.to.db call...)


time v.distance from=mypoints at sqlite to=boundary_municp at PERMANENT 
upload=cat column=cat_municip dmax=0.0

real	2m2.119s <= not so bad

db.select sql="select cat_municip, count(*) from mypoints group by 
cat_municip"

So, using the combination of v.distance and db.select I cannot reproduce 
your problem with 600,000 points, but maybe the number and nature of 
polygons can also play a role...

Moritz