On Wed, 11 Mar 2015, William May wrote:
I sent this to Roger Bivand earlier. Posting it here for
posterity, and in case other people have more to add:
---
Hi Roger,
I'm taking a spatial econometrics class, and we've been
On Thu, 12 Mar 2015, William May wrote:
Here's the R LISA map:
http://willonrails.com/images/Lisa_map_R.png
And here's the Geoda version:
http://willonrails.com/images/Lisa_map_geoda.png
I'm using Geoda 1.6.6. Since we were getting inconsistent answers
between R and Geoda, the professor ran
Karl,
You are using a default RasterLayer which has lon/lat coordinates. In
that case the earth is considered spherical (or similar), not a plane.
The maximum possible distance in longitude is 180 degrees, and the
distance between -120 and 120 is not 240 degrees, but 60+60= 120
degrees, .
To get
Hi Karl,
I think the underlying shortest.paths algorithm is wrapping around the x
dimension of the raster. I was able to fix by remove vertices in the underlying
adjacency matrix.
library(gdistance)
r - raster(nrows=18, ncols=36)
r[] - 1
t - transition(r,function(x) 1/mean(x),4)
p -
Hi all,
I am seeing confusing behavior from the costDistance function in gdistance.
In general, when cost is constant, cost distance increases linearly with
actual distance. However, in this example, it is not doing that for the
longest few distances. Am I missing something?
Karl
r -
Apologies for the confusing subject line...
-
Karl Jarvis
--
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Sent from the R-sig-geo mailing list archive at Nabble.com.
Dear list,
I recently upgraded the raster library and a script that used to run
perfectly gave me some mistakes. The problem was in the extract function:
r - raster(nrows=180, ncols=360, xmn=-180, xmx=180, ymn=-90, ymx=90)
r[] - 1
extract(x = r, y = world_map, weights=T, cellnumber=T)
I've
Robert is right. This example visualizes what is happening.
library(gdistance)r - raster(nrows=18, ncols=36) r[] - 1x -
transition(r,function(x) 1/mean(x),4)origin - c(-120,0)goal - c(120,0)sl -
shortestPath(x, origin, goal)plot(raster(sl))
On Thursday, 12 March 2015, 14:50, Robert J.
Great! Thank you all.
On Mar 12, 2015, at 4:35 PM, Jacob van Etten jacobvanet...@yahoo.com wrote:
Robert is right. This example visualizes what is happening.
library(gdistance)
r - raster(nrows=18, ncols=36)
r[] - 1
x - transition(r,function(x) 1/mean(x),4)
origin - c(-120,0)
goal -
