similar to: Histogram plots in Lattice with spatialgrid dataframe data

Hello all, After more digging I was able to find out how to do this. The answer came from an example here: https://stackoverflow.com/questions/3541713/how-to-plot-two-histograms-together-in-r yr_1997<-data.frame(bias=ann_bias$bias1997) yr_1998<-data.frame(bias=ann_bias$bias1998) yr_1999<-data.frame(bias=ann_bias$bias1999) yr_2000<-data.frame(bias=ann_bias$bias2000)

Glad you found an answer, though it looks more self-educational than efficient (see suggestions below). In the future, follow the recommendations of the Posting Guide: use plain text, and provide a reproducible example. Some elaborations on what "reproducible" means are [1][2][3]. One issue here was that you did not include sample data to work with (I have assumed below that ann_bias has

List, In order to get rid of some old, unreadable S3 code in package sp, I'm trying to rewrite things using S4 methods. Somewhere I fail, and I cannot sort out why. In order to isolate the problem, I created two functions, doNothing<- and dosth, and both should do nothing. The issue is that in most cases they do nothing, but in some cases dosth(obj) changes the class of obj and breaks with

Hi ALL, Can you please help me on how to determine the prediction error for ordinary kriging?Below are all the commands i used to generate the OK plot: rsa2 <- readShapeSpatial("residentialsa", CRS("+proj=tmerc +lat_0=39.66666666666666 +lon_0=-8.131906111111112 +k=1 +x_0=0 +y_0=0 +ellps=intl +units=m +no_defs")) x2 <- readShapeSpatial("ptna2",

I'd like to evaluate a function at each point on a 2 or 3-D grid. Is there some function that already does this, or generates the grid of points? My search has led me to the grid and lattice packages, and I found a reference to the sp package (e.g., SpatialGrid) for this. There are things in there that might be relevant, but at first blush many of them are embedded in other concepts (grobs,

Hi all, I have made a plot with ssplot, using a SpatialPointsDataFrame. The content is quite simple, as I have 9 grid points with lon/lat coordinates and 9 values attached to these coordinates. They are in a square area of 3 by 3 gridboxes. I would like to lay a map from maps() over these values, but when I try this, the grids of the maps (smaller) do not overlap with the grids I have

Dear all, I'd like to change a point pattern to a grid of cells and use one of the variables as the output. e.g. The point pattern is of a window of (500*500) and several features such as pH, SoilType etc. I like to divide it into a grid with cell size 5*5, and use the mean of the point values falling inside the cell as the output. Is there any package in R working with this? Thanks in

Dear Happy R-users & experts, I am in need of advice, While working with spatial data (x & y coordinates of seed locations) I have come accross the problem that I need to convert my point data into a matrix or grid system. I then need to count how often a point falls into a certain position in the matrix or grid. I have searched all day online, asked collegeas but nothing works. Sadly

Hello 'R' Users, I have a monthly mean CO2 necdf data file defined on 1x1 lat by lon coordinate. I want to sub-sample this variable CO2 on the coordinates of another ASCII data file. The coordinates of another ASCII data file are as: -24.01 152.06 -18.58 150.19 -13.46 148.35 -8.29 147.03 -3.14 146.19 1.53 145.59 7.08 145.33 12.25 145.02 17.46 144.31 22.44 142.35 27.53 141.26 33.04

R Users: ...been working with the sp and gstat packages for the past couple of days in an effort to analyze a set of ~ 200 soil samples collected from various eastings, northings, and depths and containing a wide range of measured hydrocarbon concentrations. Thus far, I've managed to import the data, log-transform the concentrations, assign coordinates, generate and fit a variogram model and

Now I have the forest plot data with x, y locations, and I measured the DBH for every indivicuals. The data looks like that: x=runif(100,0,100) y=runif(100,0,100) dbh=runif(100,1,100) rdata=data.frame(x,y,dbh) > rdata[1:5,] x y dbh 1 99.5354145 1.412844 34.10112 2 0.8259361 87.737036 39.12914 3 6.5678613 65.699032 22.55990 4 67.2987881 72.053877 45.83978 5 2.2491372

I imported the attached tiff file and converted the coordinate system to long lat and graphed it: californiatiff<- readGDAL("california1.tif") proj4string(californiatiff) > rasterprojection <- spTransform(californiatiff, CRS("+proj=longlat") however, when using the plot command for rasterprojection, I get a blob. I can see the outline of the state of california and

Hi, I am stuck in a looping problem. It might be an easy problem for experienced R users but I have been unable to do it. Any kind of help or advice will be great appreciated. I am creating a spatial grid and have a list of spatial points in a folder. I can read the spatial points separately and get a count of the points in the spatial grid in R. The output should be a table showing the counts of

Hello, I have been exploring the possibility to transition some code that currently uses image() to use the new rasterImage(). To date, I haven't been able to specify a color look-up strategy that works. For example... nx <- 100 ny <- 100 m <- matrix(data = rep(seq(0,1, length = nx), ny), ncol = nx, nrow = ny, byrow = TRUE) plot(1:nx, 1:ny, type = "n") my.color