tmap.R

# tmap package, thematic maps can be generated


# install.packages("tmap")

# install.packages("devtools")

# library(devtools)
# install_github("username/repo")


library(tmap)
library(sf)
library(readr)
library(tidyverse)
library(tigris)


admin2 <- st_read("shapefiles/LGAs/LGAs.shp")
roads <- st_read("shapefiles/shapefiles/Accessibility Roads/All_new_roads.shp")
towns <- st_read("shapefiles/shapefiles/Accessibility Points/All_new_points.shp")
test <- read.csv("data.csv")
inso <- st_read("shapefiles/shapefiles/inso/inso.shp") %>%  filter(inso$Location_3 == c("Borno", "Adamawa", "Yobe"))
admin2 <- st_read("shapefiles/LGAs/LGAs.shp")


data <- read.csv("shapefiles/shapefiles/partners/partners.csv") |>
  
# convert a csv table into a spacial object using st_as_sf() from the sf package
  st_as_sf(
           
           # Columns 
           coords = c("long", "lat"),
           
           remove = FALSE,
           
           # Projection
           crs = 4326
           
           )


tm_shape(admin2) +
  tm_polygons() +
  tm_text("ADM2_EN", size = 0.6) +
tm_shape(data) + 
  tm_dots(size = "partners_2" , col = "partners_2", palette = "PRGn" )


# Static map 
tmap_mode("plot")


# interactive  map 
tmap_mode("view")

tm_shape(admin2)+
tm_fill("yellow"
        
        
) +
tm_borders(alpha = .5) +

tm_text("ADM2_EN", size = 0.6) +

tm_shape(shp = inso)+
  tm_dots(alpha = 0.8, col = "Act_1", palette = "PRGn",
          stretch.palette = TRUE, size = 0.07)


map <- tm_shape(admin2) +

  
  # fill color 
  tm_fill("TARGET_FID",
              
          title="individuals per sqm"
          ) +
  
  # add boundaries
  tm_borders(alpha = .5) +
  
  #tm_polygons()  boundaries + fill
  
  # Add labels
  tm_text("ADM2_EN", size = 0.6)+
  
  # Create multiple polygons
  #tm_facets(by="ADM1_EN") +
  
  
  # remove box
  tm_layout(frame = FALSE)



map


# Add multiple layers

# Polygon

tm_shape(admin2)+
  tm_polygons(col = "purple")+
  tm_add_legend(type = "fill" , labels = "State", col = "purple", title = "Legend")+

  # Lines
tm_shape( shp = roads) +
  tm_lines(col = "red", lty = "solid") +
  tm_add_legend(type = "line", labels = "Roads", col = "red", lty = "solid") +
  
  # Points
  
  tm_shape(shp = towns) +
  tm_dots(col = "green") +
  tm_add_legend(type = "symbol", labels = "Town", col = "green", shape = 18) 
  
  # remove box
 # tm_layout(frame = TRUE) +
 # tm_legend(Position = c("left", "top"))
  

library(readr)

dtm <- read_csv("/Users/hany/Desktop/RLeaflet/data/dtm_data.csv")

library(sf)

adm2 <- st_read("/Users/hany/Desktop/adm2/nga_admbnda_adm2_osgof_20190417_WFP.shp")

library(tmap)
dtm_sf <- st_as_sf(dtm, coords = c("lon", "lat"), crs = 4326)

tm_shape(dtm_sf) +   
  tm_dots(size = "ind")

tm_shape(dtm_sf) +   
  tm_dots(alpha = 0.8, col = "ind", palette = "PRGn",
          stretch.palette = TRUE,size = 0.01)

#point to polygon
library(spatialEco)

dtm_lga <- point.in.poly(dtm_sf,adm2)

dtmlgadf <-
  as.data.frame(dtm_lga) # Creates the table to see how many individuals in each lga

library(dplyr)
ind_dtm <-
  dtmlgadf %>%
  filter(!is.na(ADM1_EN))%>%
  group_by(ADM2_EN) %>%
  summarise(tot_ind = sum(ind)) 

library(tigris)

dtm_pol <- geo_join(adm2,
                    ind_dtm,
                    "ADM2_EN",
                    "ADM2_EN",
                    how = "left") # Joins the rwi average to the LGA shapefile
#polygon map
tm_shape(dtm_pol) +
  tm_fill("blue")

#add data - color
tm_shape(dtm_pol) +
  tm_fill(col = "tot_ind")

#convert to density
tm_shape(dtm_pol) +
  tm_fill(col = "tot_ind", convert2density=TRUE,
          style="kmeans",
          title="individuals by sqm")

#Add borders
tm_shape(dtm_pol) +
  tm_fill(col = "tot_ind", convert2density=TRUE,
          style="kmeans",
          title="individuals by sqm")+
  tm_borders(alpha = .5) 


#Add text
tm_shape(dtm_pol) +
  tm_fill(col = "tot_ind", convert2density=TRUE,
          style="kmeans",
          title="individuals by sqm")+
  tm_borders(alpha = .5) +
  tm_text("ADM2_EN",
          size = 0.4) 


#Add facets
tm_shape(dtm_pol) +
  tm_fill(col = "tot_ind", convert2density=TRUE,
          style="kmeans",
          title="individuals by sqm")+
  tm_borders(alpha = .5) +
  tm_text("ADM2_EN",
          size = 0.4) +
  tm_facets(by="ADM1_EN") +
  tm_layout(legend.show = FALSE,
            outer.margins=0)