contactsimulator: Contact model simulator

# data(bbtv)
# attach(bbtv)
# Dat<- bbtv[,c(2:6,8,10)]     # Coonsidering the essential part of the data
# Dat1<-subset(Dat,Dat$latitude> -27.3 & Dat$processedbananas%in%c("P&I","P", "NI") )  # data up in queensland (noth of brisbane)
# Dat1$treatmentdate[is.na(Dat1$treatmentdate)]<- Dat1$date[is.na(Dat1$treatmentdate)] # When NA, consider removal date as
# Dat1$detection<-as.numeric(difftime(as.Date(Dat1$date), as.Date("2011/01/01"), unit="days")) + runif(1)
# Dat1$removal<-as.numeric(difftime(as.Date(Dat1$treatmentdate), as.Date("2011/01/01"), unit="days"))
# Datt<-Dat1[,c(3,4,7,8,2)]
# Datt$detection=Datt$detection + runif(nrow(Datt))
# Datt=Datt[with(Datt,order(Datt$detection)),]
#
#
# # Australian reference system
# sp::coordinates(Datt) <- c("longitude", "latitude")
# sp::proj4string(Datt) <- sp::CRS("+init=epsg:4326")
# australianCRS <- sp::CRS("+init=epsg:3577")
#
# pointsinaustraliangrid = sp::spTransform(Datt,australianCRS)
#
# pointsinaustraliangridextent = raster::extent(pointsinaustraliangrid)
#
# pointsinaustraliangridextent@xmin=floor(as.numeric(pointsinaustraliangridextent@xmin)/5000)*5000
# pointsinaustraliangridextent@ymin=floor(as.numeric(pointsinaustraliangridextent@ymin)/5000)*5000
# pointsinaustraliangridextent@xmax=ceiling(as.numeric(pointsinaustraliangridextent@xmax)/5000)*5000
# pointsinaustraliangridextent@ymax=ceiling(as.numeric(pointsinaustraliangridextent@ymax)/5000)*5000
#
#
# #Raster
# rast <- raster::raster()
# raster::extent(rast) <- raster::extent(pointsinaustraliangrid) # Set same extent
#
# raster::res(rast)=5000 #Set resolution
#
# # And then ... rasterize it! This creates a grid version
# # of your points using the cells of rast,
#
# rast2 <- raster::rasterize(pointsinaustraliangrid, rast, 1, fun=sum)
#
# # Extract infos on the grid
#
#
# n_row_grid=nrow_grid=raster::nrow(rast)
# n_col_grid=ncol_grid=raster::ncol(rast)
# grid_size=raster::res(rast)[1]     # Resolution
#
# n_line=(nrow_grid+1) + (ncol_grid +1)  # Number of grid  lines
#
# x_min=raster::xmin(rast)  # min max of the bounding box
# x_max=raster::xmax(rast)
#
# y_min=raster::ymin(rast)
# y_max=raster::ymax(rast)
#
# da=as.data.frame(pointsinaustraliangrid)
#
# pop_per_grid=raster::values(rast2)
# pop_per_grid[is.na(pop_per_grid)]=0
# mat=matrix(pop_per_grid,nrow = nrow_grid, byrow = TRUE)
# pop_grid=apply(mat,2,rev)     # population per grid
#
# # Structure of the grid
# x=seq(x_min,x_max,grid_size)
# y=seq(y_min,y_max,grid_size)
#
# grid_lines=array(0,c(n_line,6))
# for(i in 1:n_line){
#   if(i<=(nrow_grid +1)){
#     grid_lines[i,]=c(i,1,x[1],y[i],x[length(x)],y[i])
#   }
#   else{
#     grid_lines[i,]=c(i,2,x[i-length(y)],y[1],x[i-length(y)],y[length(y)])
#   }
# }
#
# grid_lines=as.data.frame(grid_lines)
# colnames(grid_lines)<- c("indx","orient_line","coor_x_1","coor_y_1","coor_x_2","coor_y_2")
# circle_x=2022230
# circle_y=-3123109
# r=10000
#
# detach(bbtv)
#