On Mon, 24 Jun 2019, Rolando Valdez wrote:
Dear Andres,
I could follow an example provided with the package, it was a little bit
simple, however, I got this message:
dists <- osrmTable(loc = muns13, measure = "duration")
The OSRM server returned an error:
Error: The public OSRM API does not allow results with a number of
durations
higher than 10000. Ask for fewer durations or use your own server and set
its
--max-table-size option.
My sample size is 2,457
Were you asking for the whole nx(n-1)/2 set of durations in one run? You
see that the API limits the number of interactions (possibly by time and
by unique IP number). So you need to reduce the number of queries. If you
are going to impose a distance threshold anyway, you can do that using the
Great Circle (not Euclidean) distances between your geographical
coordinates and dnearneigh(), and step through the nb list object with
src= being the data frame of the observation coordinates, and dest= the
data frame of the neighbours' coordinates.
library(sf)
nc <- st_read(system.file("shapes/sids.shp", package="spData")[1],
quiet=TRUE)
st_crs(nc) <- "+proj=longlat +datum=NAD27"
nc1 <- st_transform(nc, 32019)
nc2 <- st_centroid(nc1, of_largest_polygon=TRUE)
nc3 <- st_transform(nc2, 4326)
crds <- st_coordinates(st_geometry(nc3))
df <- data.frame(id=nc3$FIPSNO, long=crds[,1], lat=crds[,2])
library(spdep)
nb <- dnearneigh(crds, 0, 50, longlat=TRUE)
library(osrm)
res <- vector(mode="list", length=nrow(df))
for (i in seq(along=res)) res[[i]] <- osrmTable(src=df[i,],
dst=df[nb[[i]],], measure = "duration")
res1 <- lapply(res, function(x) 10/x$duration)
lw <- nb2listw(nb, glist=res1, style="B")
gives general spatial weights based on 10/# minutes travel time between
county centroids (centroids calculated from projected coordinates), for
county centroids closer than 50 km measured by Great Circle.
In your case, you may need to split the for() loop into portions of
cumsum(card(nb)) of less than the limit. If durations are symmetric,
you could also halve the query count by taking only neighbour ids > i,
but you'd have to fold them back afterwards. You also wanted to categorise
the durations into 0,1, which you could do with lapply() instead of using
inverse durations.
Hope this helps,
Roger
El vie., 21 de jun. de 2019 a la(s) 02:53, Andres Diaz Loaiza (
madi...@gmail.com) escribió:
Dear Rolando,
The advantage of using Open Street Maps engine is that you can give the
travel option. This means you can select whether are you traveling by
bike,
car or walking. The previous approach didn't consider this topic. For
this,
you should have added a vector layer depending on your position of the
street you can take (or not). Open Street Maps project allow you two
options: a service in which you give your current position, the position
you want to reach and your transport method (giving you back the fastest
route). Or the option to download the engine/algorithm compile by
yourself
(if I am not wrong is made in C or python) and then you can make your
own
calculation at your own computer. For the first option, the package
OSRM is
an interface in which send a request to the OSM web page and wait for an
answer. With this method, you can send a couple of request at the same
time
but no to many (you should read the manual for this). Of course, also
will
depend on whether the OSM server is down or not (or busy).
I have to say that I used some years ago this app and nowadays I know
that
for some cities OSM has more streets reported than the same google maps.
Also is an open project and they let you download their data for free,
contrary to what google maps do.
All the best,
Andres
El vie., 21 jun. 2019 a las 4:30, Adrian Baddeley (<
adrian.badde...@curtin.edu.au>) escribió:
Rather than converting an object of class 'SpatialLines' or
'SpatialLinesDataFrame' to the spatstat class 'psp' and then
converting it
to the spatstat class 'linnet', it is safer and more efficient to
convert
the SpatialLines* object directly to class linnet using
as.linnet.SpatialLinesDataFrame() from the package 'maptools'.
Prof Adrian Baddeley DSc FAA
John Curtin Distinguished Professor
Department of Mathematics and Statistics
Curtin University, Perth, Western Australia
________________________________
From: Rolf Turner <r.tur...@auckland.ac.nz>
Sent: Friday, 21 June 2019 10:08 AM
To: Rolando Valdez
Cc: r-sig-geo@r-project.org; Adrian Baddeley; Ege Rubak
Subject: Re: [FORGED] [R-sig-Geo] Create a Spatial Weight Matrix based
on
road distance
On 21/06/19 12:26 PM, Rolando Valdez wrote:
Dear community,
Is there any way to create a spatial weight matrix based on road
distance?
I am trying to use the road distance between two points instead of
euclidean distance.
I've seen that there is a package named osrm. Can anyone give some
advice?
I don't know anything about "osrm". Calculating "road distances" can
be
done in the spatstat package reasonably easily, if you take the trouble
to represent your collection of roads as a "linnet" object.
Given that you have done so, suppose that your linnet object is "L" and
that you have vectors "x" and "y" specifying the points on L (i.e. on
your roads) between which you want to know the distances.
Do:
X <- lpp(data.frame(x=x,y=y),L)
dMat <- pairdist(X)
The object "dMat" is a (symmetric) square matrix; dMat[i,j] is the
distance between point i and point j. (Of course the diagonal entries
are all 0.)
If your collection of roads is specified by means of a shapefile,
vignette("shapefiles") will tell you how to turn this collection into a
"psp" ("planar segment pattern") object; the function (method)
as.linnet.psp() can then be used to turn the "psp" object into a
"linnet" object.
HTH
cheers,
Rolf Turner
--
Honorary Research Fellow
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
[[alternative HTML version deleted]]
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
--
Andrés D.
--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: roger.biv...@nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
