#Include librarieslibrary(dggridR)library(collapse)#Construct a global grid with cells approximately 1000 miles acrossdggs<-dgconstruct(spacing=1000,metric=FALSE,resround='down')#Load included test data setdata(dgquakes)#Get the corresponding grid cells for each earthquake epicenter (lat-long pair)dgquakes$cell<-dgGEO_to_SEQNUM(dggs,dgquakes$lon,dgquakes$lat)$seqnum#Converting SEQNUM to GEO gives the center coordinates of the cellscellcenters<-dgSEQNUM_to_GEO(dggs,dgquakes$cell)#Get the number of earthquakes in each cellquakecounts<- dgquakes|>fcount(cell,name ="count")#Get the grid cell boundaries for cells which had quakesgrid<-dgcellstogrid(dggs,quakecounts$cell)#Update the grid cells' properties to include the number of earthquakes#in each cellgrid<-merge(grid,quakecounts,by.x="seqnum",by.y="cell")#Make adjustments so the output is more visually interestinggrid$count<-log(grid$count)cutoff<-fquantile(grid$count,0.9)grid<- grid|>fmutate(count =ifelse(count>cutoff,cutoff,count))#Get polygons for each country of the worldcountries<-map_data("world")

#Plot everything on a flat map# Handle cells that cross 180 degreeswrapped_grid=st_wrap_dateline(grid,options =c("WRAPDATELINE=YES","DATELINEOFFSET=180"),quiet =TRUE)

ggplot()+geom_polygon(data=countries,aes(x=long,y=lat,group=group),fill=NA,color="black")+geom_sf     (data=wrapped_grid,aes(fill=count),color=alpha("white",0.4))+geom_point  (aes(x=cellcenters$lon_deg,y=cellcenters$lat_deg))+scale_fill_gradient(low="blue",high="red")

library(sf)#Get the grid cell boundaries for the whole Earth using this dggs in a form#suitable for printing to a KML filegrid<-dgearthgrid(dggs)#Update the grid cells' properties to include the number of earthquakes#in each cellgrid$count<-merge(grid, quakecounts,by.x="seqnum",by.y="cell",all.x=TRUE)#Write out the gridst_write(grid,"quakes_per_cell.kml",layer="quakes",driver="KML")

#Include librarieslibrary(dggridR)N<-100#How many cells to sample#Distribute the points uniformly on a sphere using equations from#http://mathworld.wolfram.com/SpherePointPicking.htmlu<-runif(N)v<-runif(N)theta<-2*pi*u*180/piphi<-acos(2*v-1)*180/pilon<- theta-180lat<- phi-90df<-data.frame(lat=lat,lon=lon)#Construct a global grid in which every hexagonal cell has an area of#100,000 miles^2. You could, of course, choose a much smaller value, but these#will show up when I map them later.#Note: Cells can only have certain areas, the `dgconstruct()` function below#will tell you which area is closest to the one you want. You can also round#up or down.#Note: 12 cells are actually pentagons with an area 5/6 that of the hexagons#But, with millions and millions of hexes, you are unlikely to choose one#Future versions of the package will make it easier to reject the pentagonsdggs<-dgconstruct(area=100000,metric=FALSE,resround='nearest')#Get the corresponding grid cells for each randomly chosen lat-longdf$cell<-dgGEO_to_SEQNUM(dggs,df$lon,df$lat)$seqnum#Get the hexes for each of these cellsgridfilename<-dgcellstogrid(dggs,df$cell)

#Get the grid in a more convenient formatgrid<-dgcellstogrid(dggs,df$cell)grid<-st_wrap_dateline(grid,options =c("WRAPDATELINE=YES","DATELINEOFFSET=180"),quiet =TRUE)#Get polygons for each country of the worldcountries<-map_data("world")#Plot everything on a flat mapp<-ggplot()+geom_polygon(data=countries,aes(x=long,y=lat,group=group),fill=NA,color="black")+geom_sf(data=grid,fill=alpha("green",alpha=0.4),color=alpha("white",alpha=0.4))p

#Include librarieslibrary(dggridR)N<-100#How many cells to sample#Construct a global grid in which every hexagonal cell has an area of#100,000 miles^2. You could, of course, choose a much smaller value, but these#will show up when I map them later.#Note: Cells can only have certain areas, the `dgconstruct()` function below#will tell you which area is closest to the one you want. You can also round#up or down.#Note: 12 cells are actually pentagons with an area 5/6 that of the hexagons#But, with millions and millions of hexes, you are unlikely to choose one#Future versions of the package will make it easier to reject the pentagonsdggs<-dgconstruct(area=100000,metric=FALSE,resround='nearest')maxcell<-dgmaxcell(dggs)#Get maximum cell idcells<-sample(1:maxcell, N,replace=FALSE)#Choose random cellsgrid<-dgcellstogrid(dggs,cells)#Get grid

#Get the grid in a more convenient formatgrid<-dgcellstogrid(dggs,df$cell)grid<-st_wrap_dateline(grid,options =c("WRAPDATELINE=YES","DATELINEOFFSET=180"),quiet =TRUE)#Get polygons for each country of the worldcountries<-map_data("world")#Plot everything on a flat mapp<-ggplot()+geom_polygon(data=countries,aes(x=long,y=lat,group=group),fill=NA,color="black")+geom_sf(data=grid,fill=alpha("green",0.4),color=alpha("white",0.4))p

library(dggridR)#Generate a global grid whose cells are ~100,000 miles^2dggs<-dgconstruct(area=100000,metric=FALSE,resround='nearest')#Save the cells to a KML file for use in other softwaregridfilename<-dgearthgrid(dggs,savegrid=tempfile())

library(dggridR)#Generate a dggs specifying an intercell spacing of ~25 milesdggs<-dgconstruct(spacing=100,metric=FALSE,resround='nearest')#Read in the South Africa's borders from the shapefilesa_border<-st_read(dg_shpfname_south_africa(),layer="ZAF_adm0")st_crs(sa_border)=4326#Get a grid covering South Africasa_grid<-dgshptogrid(dggs,dg_shpfname_south_africa())#Plot South Africa's borders and the associated gridp<-ggplot()+geom_sf(data=sa_border,fill=NA,color="black")+geom_sf(data=sa_grid,fill=alpha("blue",0.4),color=alpha("white",0.4))p