## ----Loading_library,include=FALSE,echo=FALSE--------------------------------- library(RGeostats) constant.define("asp",1) rm(list=ls()) ## ----Loading Data------------------------------------------------------------- rg.load("Exdemo_Filter","grid") ## ----Statistics--------------------------------------------------------------- subdiv = 2 grid = db.grid.refine(grid, nmult = c(subdiv, subdiv), flag.refine = F, flag.copy = T) plot(grid,name="Cr") ## ----Correlation_Cr_P--------------------------------------------------------- correlation(grid,"Cr","P",title="Correlation between P and Cr") ## ----Correlation_Ni_P--------------------------------------------------------- correlation(grid,"Ni","P",title="Correlation between P and Ni") ## ----Correlation_Ni_Cr-------------------------------------------------------- correlation(grid,"Ni","Cr",title="Correlation between Cr and Ni") ## ----Completing P------------------------------------------------------------- grid = db.locate(grid,"P","z") grid = db.grid.fill(grid,radix="P.Fill") ## ----Locate P----------------------------------------------------------------- grid = db.locate(grid,"P.Fill*","z") ## ----Monovariate_Variogram_calculation---------------------------------------- varioP = vario.grid(grid,nlag=40) modelP = model.auto(varioP,struct=c(1,2,12), auth.aniso = FALSE,flag.noreduce=TRUE) print(modelP) ## ----Visualize_P-------------------------------------------------------------- plot(grid,pos.legend=1,title="P after completion") ## ----Neighborhood Definition-------------------------------------------------- neigh = neigh.create(ndim=2,type=3,radimg=c(10,10)) ## ----Performing the monovariate FKA------------------------------------------- means = db.stat(grid,flag.mono=TRUE,names="P.Fill*") mono = krimage(grid,modelP,neigh,cov.extract = c(2,3),uc="", mean = means) ## ----Visualize_P_after_FKA_monovariate---------------------------------------- plot(mono,pos.legend=1,title="P denoised (monovariate)", zlim=c(0,150)) ## ----Locate Multivariate------------------------------------------------------ grid = db.locate(grid,c("P.Fill*","Cr","Ni"),"z") ## ----Multivariate_Variogram_calculation--------------------------------------- varioM = vario.grid(grid,nlag=40) modelM = model.auto(varioM,struct=c(1,2,12), auth.aniso = FALSE,flag.noreduce=TRUE) modelM ## ----Perform multivariate FKA------------------------------------------------- means = db.stat(grid,flag.mono=TRUE,names=c("P.Fill*","Cr","Ni")) multi = krimage(grid,modelM,neigh,cov.extract = c(2,3),uc="", mean = means) ## ----Visualize_P_after_FKA_multivariate--------------------------------------- plot(multi,pos.legend=1,title="P denoised (multivariate)", zlim=c(0,150))