[please keep discussions on the mailing list]
On 23/01/13 22:23, דור פרידמן wrote:
I forgot to mention that I am using GRASS 6.4.2
These is an issue with some of the v.net.* modules (incl v.net.distance) in 6.4.2: you cannot correctly input arcs in layer 1 and nodes in layer 2. You, therefore, have to use layer 1 for everything, making sure that category values of arcs and nodes do not overlap.
I would really recommend that for serious network analysis you use grass7 in which Markus Metz has not only made the interfaces of the modules more consistent, but also increased their efficiency.
Moritz
2013/1/23 Moritz Lennert <mlennert@club.worldonline.be
<mailto:mlennert@club.worldonline.be>>
On 23/01/13 20:22, דור פרידמן wrote:
I'm trying to build a network in GRASS in order to find the shortest
path from any settlement out of 1120 (points), to one waste
treatment
facility out of 27 (points). I plan to use v.net.distance which is
designated to this purpose, and to define source and destination
points
using a column called "type". In that column I have assigned the
settlements layer with the number 5 and the treatment facilities
with 1.
My problem occurs when I try to create the network using v.net
<http://v.net>
<http://v.net>; If I define nodes layer (nlayer=2) to be 2, I
lose all
the points and can't find it, even by using v.extract.
What is the exact comman line for v.extract that you used ? Did you
set layer=2 ?
What does v.category option=report give you on the file resulting
from v.net <http://v.net> ?
Which version of GRASS are you using ?
Otherwise (when
nlayer=1) the attributes describing type are being auromatically
changed
to 4, which is the type attribute for roads.
v.net <http://v.net> certainly should not (and AFAIK does not)
change attribute data. Actually attribute data of points connected
to the network with v.net <http://v.net> operation=connect is not
kept. As mentioned in the man page you have to reconnect your points
to the attribute data by hand after running v.net <http://v.net>.
Any one has an idea why I'm losing this crucial data and how can I
prevent it from happening?
It would help if you could give a reproducible case description,
including data (possibly from the NC demo dataset), so that we can
see exactly what is going wrong where.
Moritz