clinic.r

library(httr)
library(jsonlite)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(leaflet)
library(sp)
library(deldir)

## deldir 0.1-12

# 공공보건포털 xhr
url <- "http://www.g-health.kr/portal/health/pubHealthSearch/get_list.do"

# 보건기관 코드에 따라 데이터 가져오기
getMedIns <- function(code) {
  # code 71, 72, 73 Bogeonso
  # code 81 Pharmacy
  pl <- list(cl_cd=code, rows=10000, cpage=1)
  r <- POST(url, 
            body = pl, 
            add_headers(
              'Content_Type' = 
                'application/x-www-form-urlencoded; charset=UTF-8' 
            )
  )
  res <- content(r,"text")
  df <- jsonlite::fromJSON(res)
  # 경위도 없는 데이터 제외
  df <- df %>%
    filter(x_pos != '') %>%
    filter(y_pos != '') %>%
    filter(cl_cd != '')
  df$x_pos <- as.numeric(df$x_pos)
  df$y_pos <- as.numeric(df$y_pos)
  return(df)
}

# 보건소, 보건지소, 보건진료소
bg71 <- getMedIns(71)
bg72 <- getMedIns(72) 
bg73 <- getMedIns(73) 
bg <- bind_rows(bg71, bg72, bg73)

# 약국
pharm <- getMedIns(81)

m <- leaflet() %>% 
  addTiles('http://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png') %>% 
  setView(lng = 127.5, lat = 36, zoom = 7)

pal <- colorFactor(c("red", "green", "yellow", "orange"), 
                   domain = c("71", "72", "73", "81"))

addCircleMarkers(m, lng = bg$x_pos, lat=bg$y_pos, 
                 radius = 2,
                 color = pal(bg$cl_cd),
                 stroke = FALSE, 
                 fillOpacity = 0.4)

addCircleMarkers(m, lng = pharm$x_pos, lat=pharm$y_pos, 
                 radius = 2,
                 color = pal(pharm$cl_cd),
                 stroke = FALSE, 
                 fillOpacity = 0.4)

df_to_voronoi_polygon <- function(df) {
  
  
  vor_data <- df %>% select(x_pos, y_pos)
  sp <- SpatialPointsDataFrame(cbind(vor_data$x_pos,
                                     vor_data$y_pos),
                                     vor_data, match.ID=TRUE)
  
  # tile.list extracts the polygon data from the deldir computation
  vor_desc <- tile.list(deldir(sp@coords[,1], sp@coords[,2]))
  
  lapply(1:(length(vor_desc)), function(i) {
    
    # tile.list gets us the points for the polygons but we
    # still have to close them, hence the need for the rbind
    tmp <- cbind(vor_desc[[i]]$x, vor_desc[[i]]$y)
    tmp <- rbind(tmp, tmp[1,])
    
    # now we can make the Polygon(s)
    Polygons(list(Polygon(tmp)), ID=i)
    
  }) -> vor_polygons
  
  vor_gons <- SpatialPolygons(vor_polygons)
  
  pid <- sapply(slot(vor_gons, "polygons"), function(x) slot(x, "ID"))
  p.df <- data.frame( ID=1:length(vor_gons), row.names = pid)    
  
  vor.spdf<-SpatialPolygonsDataFrame(vor_gons, data=p.df)
  return(vor.spdf)
  }


## Voronoi diagram for bogeonso

bg.spdf <- df_to_voronoi_polygon(bg)

## 
##      PLEASE NOTE:  The components "delsgs" and "summary" of the
##  object returned by deldir() are now DATA FRAMES rather than
##  matrices (as they were prior to release 0.0-18).
##  See help("deldir").
##  
##      PLEASE NOTE: The process that deldir() uses for determining
##  duplicated points has changed from that used in version
##  0.0-9 of this package (and previously). See help("deldir").

addPolygons(m, data=bg.spdf,
            stroke=TRUE, color="green", weight=0.5,
            fill=TRUE, fillOpacity = 0.0,
            smoothFactor=0.5)

## Voronoi diagram for pharm

pharm.spdf <- df_to_voronoi_polygon(pharm)
addPolygons(m, data=pharm.spdf,
            stroke=TRUE, color="orange", weight=0.5,
            fill=TRUE, fillOpacity = 0.0,
            smoothFactor=0.5)