plotting Football field ball pattern data
Miguel,
I am not entirely sure about what you need, but this might do it:
#install.packages("raster", repos="http://R-Forge.R-project.org")
require(raster)
# create a new raster. use additional arguments so that it matches
your data (extreme x and y )
r <- newRaster(ncols=36, nrows=18)
# I simulate 1000 points, 3 times (simulating not being able to load
all points, but perhaps you can, in this case)
n <- 1000
for (i in 1:3) {
x <- runif(n)* 360 - 180
y <- runif(n)* 180 - 90
xy <- cbind(x, y)
vals <- rep(1, n)
r <- pointsToRaster(r, xy, vals)
r[is.na(r)] <- 0
if (i == 1) { rs <- r } else { rs <- rs + r }
}
# the plot you do not want:
plot(rs)
# is this the plot you do want?
x11()
plot(density(values(rs)))
Robert
On Fri, Jan 30, 2009 at 3:43 PM, Miguel Eduardo Gil Biraud
<miguel.gil.biraud at ieee.org> wrote:
Hi, I was going to post a similar question as I am also a fresh new user of R. In my case I have between 10 million and 20 million latitude, longitude pairs and want to get an image in which each pixel has a color that is a function of the amount of positions that would fall into the spatial bin corresponding to the pixel size. I understand that this would be akin to a 2D histogram of my data and resemble a density plot. The way I started doing that was importing the table with read.table() and then converting it to a PPP object providing the adequate bounds. The first problem I face is that when I try to put all the points into the PPP object I get a memory failure. To keep experimenting I lowered the number of points I import and played around with the density function available in spatstat but while I can see its uses when you have few points, in my case the patters would get diluded very fast even for small values of sigma and I am afraid it would not represent the data faithfully. On the other hand the function quadratcount returns very fast results for a high number of partitions in the X and Y axis and I could certainly use the results it provides, if it wouldn't be for the fact that when I try to plot it, I get the grid and the point count inside each cell. Is there any way to convert the output of gridcount into a colored plot in the same spirit of the one you get when you do a plot(density())? Hope it wasn't too confusing. As you can see I've tried to take a jab at it on my own, but it is proving more complicated than I expected! :) Cheers, Miguel On Fri, Jan 30, 2009 at 06:09, srinivasa raghavan <srinivasraghav at gmail.com> wrote:
Hi r-sig-geo team,
I am a new user of R 2.8.1 in windows 2003. I have a data set of football
ball pattern data. The data is for multiple matches. The variables are :
match: The code number of the match.
period: First half or second half denotted by 1 or 2.
pitchX: The x co-ordinate of the field.
pitchy: The y-co-ordinate of the field.
seconds: The time point.
I am interested to draw the football graph/diagram and then plot the above
data.
Can any one let me know the right functions/packages which can help me in
this regard.
thanks in advance.
warm regards,
srinivas
statistical analyst.
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