R Under development (unstable) (2023-10-29 r85433 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(intamap) Loading required package: sp > > # set up data: > data(meuse) > coordinates(meuse) = ~x+y > meuse$value = log(meuse$zinc) > data(meuse.grid) > gridded(meuse.grid) = ~x+y > proj4string(meuse) = CRS("+init=epsg:28992") Warning message: In CPL_crs_from_input(x) : GDAL Message 1: +init=epsg:XXXX syntax is deprecated. It might return a CRS with a non-EPSG compliant axis order. > proj4string(meuse.grid) = CRS("+init=epsg:28992") > set.seed(13531) > > mgrid = coarsenGrid(meuse.grid,4) > # set up intamap object: > obj = createIntamapObject( + observations = meuse, + predictionLocations = mgrid, + targetCRS = "+init=epsg:3035", + params = list(predictType=list(quantiles=c(0.05,0.5,0.95)),thresh=c(5.5,6.6)), + outputWhat = list(mean = 1, + variance = 1, + quantile = 0.05, + quantile = 0.5, + quantile = 0.95, + excprob = 5.5, + excprob = 6.6, + cumdistr = 5.5, + cumdistr = 6.6, + cumdistr = 7.9) + ) [1] "rgdal has been retired. \n As a result of this, some of the checks on projections in the \n intamap package have disappeared" [1] "createIntamapObject: formulaString is missing, using: value~1" > class(obj) = "linearVariogram" > > # check: > checkSetup(obj) Checking object ... OK > > # do interpolation steps: > obj = preProcess(obj) > obj = estimateParameters(obj) > obj = spatialPredict(obj) > obj = postProcess(obj) > output = obj$predictions > > # generate some output: > summary(obj$predictions) Object of class SpatialPointsDataFrame Coordinates: min max coords.x1 4020598 4023682 coords.x2 3102604 3106476 Is projected: TRUE proj4string : [+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000 +ellps=GRS80 +units=m +no_defs] Number of points: 195 Data attributes: var1.pred var1.var Min. :4.592 Min. : 5.568 1st Qu.:5.194 1st Qu.: 68.524 Median :5.513 Median : 94.766 Mean :5.683 Mean :119.007 3rd Qu.:6.176 3rd Qu.:148.064 Max. :7.364 Max. :438.732 > gridded(output) = FALSE > summary(output) Object of class SpatialPointsDataFrame Coordinates: min max coords.x1 4020598 4023682 coords.x2 3102604 3106476 Is projected: TRUE proj4string : [+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000 +ellps=GRS80 +units=m +no_defs] Number of points: 195 Data attributes: var1.pred var1.var Min. :4.592 Min. : 5.568 1st Qu.:5.194 1st Qu.: 68.524 Median :5.513 Median : 94.766 Mean :5.683 Mean :119.007 3rd Qu.:6.176 3rd Qu.:148.064 Max. :7.364 Max. :438.732 > > proc.time() user system elapsed 2.65 0.48 3.15