Thanks very much angain,
I'll check them out.
Best regards
Le jeu. 9 janv. 2020 à 19:05, Ben Tupper a écrit :
> Your assignments that look like...
>
> minx <- rain_data_UTM at bbox[1,1]
>
> are not valid R statements - and that will cause an error. Instead,
> obtain a matrix of the bounding
Your assignments that look like...
minx <- rain_data_UTM at bbox[1,1]
are not valid R statements - and that will cause an error. Instead,
obtain a matrix of the bounding box using the bbox() function. Then
extract your coordinates from that. I think you want...
bb <- bbox(rain_data_UTM)
minx
Thank you for appreciated reply,
I explane you exactly what I want to do with this R code attached.
I want to adapt this code to my data to build an isohyet map.
But i have some difficulties to adapt it to my case.
I will be very happy when you will help my to adapt this R code (attached)
to my
Welcome to r-sig-geo!
I don't think that you haven't provided us enough information so that we
can help. On the other hand, does the example below using expand.grid help?
minx <- 20
maxx <- 25
miny <- 31
maxy <- 36
pixel <- 1
grd <- expand.grid(x = seq(minx, maxx, by=pixel), y = seq(miny, maxy,
Dear,
I'm writing to express my wish to join R-sig-geo list users.
I was doing a search on the net to know how to build an isohyet map and I
came across this R code.
However, I stumbled upon a problem from the line :
grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
by=pixel)),
I
Dear R-Sig-Geo Members,
I have the three hypothetical point process situation (A, B and C) and my
question is: What point distribution (B or C) is more close to A?
For this problem, I make a simple example:
library(spatstat)
set.seed(2023)
A <- rpoispp(30) ## First event
B <- rpoispp(30) ##
