Hover treemap in a shinyapp not showing the right values

[manolo20]

I am trying to replicate the hover plot from the "treemap" library examples in the following shinyapp:

library(shiny)
library(treemap)
library(dplyr)
library(gridBase)


weights <- readRDS("/home/R projects/treemap1.rds")

### Handle cliks on a treemap

tmLocate <-
  function(coor, tmSave) {
    tm <- tmSave$tm

# retrieve selected rectangle
    rectInd <- which(tm$x0 < coor[1] & (tm$x0 + tm$w) > coor[1] &
                       tm$y0 < coor[2] & (tm$y0 + tm$h) > coor[2])
    return(tm[rectInd[1], ])   
  }

ui = fluidPage(pageWithSidebar(
  headerPanel("Interactive treemap"),
  sidebarPanel(
    selectInput("prov", "Select province:", choices = unique(weights$Region)), width = 2
  ),
  mainPanel(
    plotOutput("plot", hover="hover", height = 700, width = 900), 
    tableOutput("record")
  ))
)

server = function(input, output){
  sel1 <- reactive({
    weights %>% filter(Region %in% input$prov)
  })

  getRecord <- reactive({
    x <- input$hover$x
    y <- input$hover$y

    x <- (x - .tm$vpCoorX[1]) / (.tm$vpCoorX[2] - .tm$vpCoorX[1])
    y <- (y - .tm$vpCoorY[1]) / (.tm$vpCoorY[2] - .tm$vpCoorY[1])

    l <- tmLocate(list(x=x, y=y), .tm)
    l[, 1:(ncol(l)-9)]            
  })

  output$plot <- renderPlot({ 
    #cat(input$hover$x, "\n")
    par(mar=c(0,0,0,0), xaxs='i', yaxs='i') 
    plot(c(0,1), c(0,1),axes=F, col="white")
    vps <- baseViewports()

    .tm <<- treemap(sel1(), 
                    index=c("Level.0","Level.1"),
                    vSize="X2015", vp=vps$plot)

  })
  output$record <- renderTable({
    getRecord()
  })
}

shinyApp(ui=ui, server=server)

Unfortunately, for some variables (like Shelter or Transportation) the hover treemap shows only the values only for the "Level.0" and for other variables it show the values for Level.1 how it should be.

I am trying to show only the values of Level.1 when hovering the treemap and I think that the issue is within the tmLocate function (or maybe the getRecord one) which I don't fully understand.

The dataset can be found here