Hi Jon, thanks for your reply — it solves my issues completely.
Best F On 21 Aug 2014, at 07:58, Jon Skoien <jon.sko...@jrc.ec.europa.eu> wrote: > > Hi Frederico, > > The kriging function seems to come from the kriging package (please give also > the package next time you ask a question), which I dont know. I can therefore > not tell you why it does not give you the correct result. But R has a huge > number of packages which can krige, and autoKrige from automap should fairly > easy be able to give you what you want. > > # You have to create a SpatialPolygon of your house first, from which you can > sample: > pts = cbind(house$x, house$y) > pts = rbind(pts, pts[1,]) # Repeating the first coordinates, just to close > the polygon > house2 = SpatialPolygons( list( Polygons(list(Polygon(pts)), 1))) > housegrid = spsample(house2, 10000, "regular") # Sampling 10000 points on a > regular grid > gridded(housegrid) = TRUE # Defining this to be a grid, not a collection of > points > > # You need to make a SpatialPointsDataFrame of your temperature data, and > then you can interpolate > coordinates(U) = ~x+y > res = autoKrige(temp~1, U, housegrid) > spplot(res$krige_output, col.regions = rev(heat.colors(100))) > # Your result is in the var1.pred-variable of res$krige_output > > You will generally get more and quicker answers to questions about spatial > data and methods from the r-sig-geo list. > > Best wishes, > Jon > > > On 8/20/2014 11:01 PM, Federico Calboli wrote: >> Hi All, >> >> I am trying to do some kriging of a floor, based on a number of heat sensors. >> >> My data looks like this: >> >> sensor temp x y >> 1 1 1.25437406 390 2960 >> 2 2 0.64384594 830 2960 >> 3 3 1.52067733 1420 2960 >> 4 4 1.21441928 3127 2920 >> 5 5 1.04227694 4005 2920 >> 6 6 1.90084852 400 1960 >> 7 7 1.58530250 835 1880 >> 8 8 1.23060971 1130 1960 >> 9 9 0.92749453 1550 1950 >> 10 10 0.76638878 1995 1960 >> 11 11 0.84247092 2540 1950 >> 12 12 0.93999929 3300 1880 >> 13 13 0.61610170 4000 1870 >> 14 14 1.06967332 395 1330 >> 15 15 0.72970917 845 1330 >> 16 16 0.60216970 1135 1300 >> 17 17 0.44648551 1570 1275 >> 18 18 2.49863724 2010 1290 >> 19 19 0.71619206 2540 1320 >> 20 20 1.50984666 3140 1275 >> 21 21 -0.06540552 4000 1258 >> 22 22 1.20017747 400 685 >> 23 23 1.05820693 1575 640 >> 24 24 2.25086655 1830 625 >> 25 25 0.69296059 3120 625 >> 26 26 0.69324786 3990 605 >> >> and the floor plan describes the edges of the floor thus: >> >> x y >> 1 210 3200 >> 2 210 420 >> 3 1510 420 >> 4 1510 100 >> 5 4090 100 >> 6 4090 3200 >> 7 2947 3200 >> 8 2947 2850 >> 9 1647 2850 >> 10 1647 3200 >> 11 210 3200 >> 12 210 3200 >> >> I run these commands: >> >> house2 <- list(data.frame(house$x, house$y)) >> plot(house.y ~house.x, type = 'l', house2[[1]]) >> points(U[,3], U[,4], pch = 20) >> housekrig=kriging(U[,3],U[,4],U[,2],polygons=house2,lags = 5) >> image(housekrig, xlim = extendrange(U[,3]), ylim = extendrange(U[,4]), col = >> rev(heat.colors(100))) >> >> and I noticed that the kriging area does not respect the floor plan. In >> fact, if I do: >> >> points(U[,3], U[,4], pch = 20) >> >> the sensors and not in the same place, and the kriging has ignored the edges >> of the polygons altogether. >> >> So my question is, how do I have a kriging of the *whole* surface, based on >> my sensors? Any suggestion is welcome, especially if the data does not >> require reformatting (or if the reformatting is straightforward)! >> >> Best >> >> F >> >> PS I have contacted the maintainer of the package about the issue but I had >> no reply, and I’d need to solve this one way or another sooner, rather than >> later. >> >> >> >> >> >> ______________________________________________ >> >> R-help@r-project.org >> mailing list >> >> https://stat.ethz.ch/mailman/listinfo/r-help >> >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> >> and provide commented, minimal, self-contained, reproducible code. >> >
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______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
