In king4k1/seoulsubway: Information about subway in Seoul
library(sp)
library(sf)
library(maptools)
library(rgdal)
library(rgeos)
library(seoulsubway)
setwd(paste0("D:/workspace/seoulsubway/rmd"))
data(subway_data_DT)
data(subway_data)
load(file="shape_data/subwayline_fty.RData")
dist_sht <- function(df, line_choose, departure, arrival){
df <- df %>% rbind(subway_data[[line_choose]] %>% filter(Name %in% c(departure, arrival)) %>%
select(long, lat, Name) %>% rename(group_id = Name))
df1 <- df %>% arrange(long) %>% arrange(lat)
df2 <- df %>% arrange(lat) %>% arrange(long)
df3 <- df %>% arrange(lat)
df4 <- df %>% arrange(long)
df1_dist <- sum(sapply(1:(nrow(df1)-1),
function(x){geosphere::distGeo(p1=c(df1$long[x], df1$lat[x]),
p2=c(df1$long[x+1], df1$lat[x+1]))}))
df2_dist <- sum(sapply(1:(nrow(df2)-1),
function(x){geosphere::distGeo(p1=c(df2$long[x], df2$lat[x]),
p2=c(df2$long[x+1], df2$lat[x+1]))}))
df3_dist <- sum(sapply(1:(nrow(df3)-1),
function(x){geosphere::distGeo(p1=c(df3$long[x], df3$lat[x]),
p2=c(df3$long[x+1], df3$lat[x+1]))}))
df4_dist <- sum(sapply(1:(nrow(df4)-1),
function(x){geosphere::distGeo(p1=c(df4$long[x], df4$lat[x]),
p2=c(df4$long[x+1], df4$lat[x+1]))}))
min(df1_dist, df2_dist, df3_dist, df4_dist)
}
line_compare <- function(line_select){
subway_data[[line_select]] %>% rename(St_dist = Dist) %>%
mutate(Dist = get_section(line_choose = line_select)$dist,
diff = Dist - St_dist)
}
get_unit_section <- function(line_choose, departure, arrival){
line_1_fty <- subwayline_fty[[line_choose]]
line_1_nms <- subway_data_DT %>% filter(Line %in% line_choose) %>% filter(Name%in%c(departure, arrival))
stn_shp_fty_line1 <- stn_shp_fty_trim_mean %>%
mutate(group_id = str_remove(group_id, ".[1-9]")) %>%
filter(long <= max(line_1_nms$long), lat <= max(line_1_nms$lat)) %>%
filter(group_id %in% line_1_nms$Name) %>% filter(!duplicated(group_id))
ind <- setdiff(line_1_nms$Name, stn_shp_fty_line1$group_id)
stn_shp_fty_line1 <- stn_shp_fty_line1 %>%
rbind(line_1_nms %>%
filter(Name %in% ind) %>%
select(Name, long, lat) %>%
mutate(Name = factor(Name)) %>% rename(group_id=Name))
long_select <- stn_shp_fty_line1$long # stn_shp_fty_line1[c(i, i+1),]
lat_select <- stn_shp_fty_line1$lat
section <- line_1_fty %>% select(long, lat, id) %>% rename(group_id=id) %>%
filter(long >= min(long_select), long <= max(long_select)) %>%
filter(lat >= min(lat_select), lat <= max(lat_select)) %>%
mutate(long = round(long, 4), lat = round(lat, 4)) %>%
filter(!duplicated(long, lat))
stn_shp_fty_line1[1,] %>% select(long, lat, group_id) %>%
rbind(section) %>%
rbind(stn_shp_fty_line1[2,] %>% select(long, lat, group_id)) %>%
rename(Name = group_id) %>%
mutate(dist = dist_sht(section, line_choose, departure, arrival))
}
make_shape_line <- function(line_choose){
line_data <- subway_data[[line_choose]]
stn_vec <- line_data$Name
Spline <- list()
for(i in 1:(length(stn_vec))){
departure = stn_vec[i]
arrival = ifelse(is.na(stn_vec[i+1]) & line_choose %in% c("2", "6_A"),
stn_vec[1], stn_vec[i+1])
if(!is.na(arrival)){
# get_unit_section(line_choose, departure, arrival) %>% ggplot(aes(x=long, y=lat)) + geom_point()
ll <- get_unit_section(line_choose, departure, arrival) %>%
dplyr::select(long, lat) %>%
arrange(long, lat) %>% mutate_all(as.numeric) %>% as.matrix()
departure_excode <- subway_data[[line_choose]] %>% filter(Name==departure)
arrival_excode <- subway_data[[line_choose]] %>% filter(Name==arrival)
for(j in 2:nrow(ll)){
nms <- paste0(departure_excode$ExCode, "___", arrival_excode$ExCode, "___", (j-1))
Sl <- Line(ll[c(j-1, j), ])
s1 <- Lines(list(Sl), ID = nms)
Spline[[paste0(i,"_",j)]] <- s1
}
}
}
Splineset <- SpatialLines(Spline)
df <- data.frame(len = sapply(1:length(Splineset), function(i) gLength(Splineset[i, ])))
rownames(df) <- sapply(1:length(Splineset), function(i) Splineset@lines[[i]]@ID)
## SpatialLines to SpatialLinesDataFrame
Sldf <- SpatialLinesDataFrame(Splineset, data = df)
Sldf
}
get_section <- function(line_choose){
line_1_fty <- subwayline_fty[[line_choose]]
line_1_nms <- subway_data_DT %>% filter(Line %in% line_choose) %>% filter(!duplicated(Name))
stn_shp_fty_line1 <- stn_shp_fty_trim_mean %>%
filter(long <= max(line_1_nms$long), lat <= max(line_1_nms$lat)) %>%
mutate(group_id = str_remove(group_id, ".[1-9]")) %>%
filter(group_id %in% line_1_nms$Name) %>% filter(!duplicated(group_id))
ind <- setdiff(line_1_nms$Name, stn_shp_fty_line1$group_id)
stn_shp_fty_line1 <- stn_shp_fty_line1 %>%
rbind(line_1_nms %>%
filter(Name %in% ind) %>%
select(Name, long, lat) %>%
mutate(Name = factor(Name)) %>% rename(group_id=Name))
stn_shp_fty_line1 <- stn_shp_fty_line1 %>%
mutate(group_id = factor(group_id, levels=line_1_nms$Name),
station_lev = as.numeric(group_id)) %>% arrange(station_lev)
section_select <- c()
for(i in 1:(nrow(stn_shp_fty_line1)-1)){
long_select <- stn_shp_fty_line1[c(i, i+1),]$long # stn_shp_fty_line1[c(33, 34),]
lat_select <- stn_shp_fty_line1[c(i, i+1),]$lat
section <- line_1_fty %>% select(long, lat, id) %>% rename(group_id=id) %>%
filter(long >= min(long_select), long <= max(long_select)) %>%
filter(lat >= min(lat_select), lat <= max(lat_select))
section <- section %>% mutate(long = round(long, 4),
lat = round(lat, 4)) %>%
filter(!duplicated(long, lat))
group_index <- unique(section$group_id)
#section %>% ggplot(aes(x=long, y=lat, col=group_id)) + geom_point()
if(length(group_index) == 0){
section_select[i] <-
geosphere::distGeo(p1 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric(),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric())
### 두 역이 직선거리여서 선이 정의되지 않는 경우
}
if(length(group_index) == 1){
if(nrow(section) > 1){
sum_section <- sum(sapply(1:(nrow(section)-1),function(x){
geosphere::distGeo(p1=c(section$long[x], section$lat[x]),
p2=c(section$long[x+1], section$lat[x+1]))}))
section_select[i] <- sum_section +
min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) +
min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()))
}else{
section_select[i] <- min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) +
min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()))
}
}
if(length(group_index) == 2){
section_list_i <- list()
for(j in seq_along(group_index)){
section_i <- section %>% filter(group_id == group_index[j])
## 2개 shp line으로 두 역 사이가 선택되는 경우
if(nrow(section_i) > 1){
if(sum(sapply(1:(nrow(section_i)-1), function(x){
geosphere::distGeo(p1=c(section_i$long[x], section_i$lat[x]),
p2=c(section_i$long[x+1], section_i$lat[x+1]))
}) >= 300)==1){
section_i <- section_i %>% arrange(long, lat)
sum_section <- sum(sapply(1:(nrow(section_i)-1), function(x){
geosphere::distGeo(p1=c(section_i$long[x], section_i$lat[x]),
p2=c(section_i$long[x+1], section_i$lat[x+1]))}))
}else{
sum_section <- sum(sapply(1:(nrow(section_i)-1), function(x){
geosphere::distGeo(p1=c(section_i$long[x], section_i$lat[x]),
p2=c(section_i$long[x+1], section_i$lat[x+1]))
}))
}
section_list_i[[j]] <- sum_section +
min(
geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()))
}else{
section_list_i[[j]] <- min(
geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()))
}
}
shortest_list <- c()
for(k in 1:nrow(section[which(section$group_id == group_index[1]),])){
shortest_list[k] <- min(geosphere::distGeo(p1 = section[which(section$group_id == group_index[1])[k],],
p2 = section[which(section$group_id == group_index[2]),]))
}
section_select[i] <- min(shortest_list) + (section_list_i %>% unlist() %>% sum())
}
if(length(group_index) > 2){
section <- section %>% arrange(long, lat)
sum_section <- sum(sapply(1:(nrow(section)-1), function(x){
geosphere::distGeo(p1=c(section$long[x], section$lat[x]),
p2=c(section$long[x+1], section$lat[x+1]))}))
section_select[i] <- sum_section +
min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]),
p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) +
min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()),
geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]),
p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()))
}# stn_shp_fty_line1[c(i, i+1),]i
section_select[i] <- min(dist_sht(section, line_choose,
departure = stn_shp_fty_line1[i,]$group_id %>% as.character(),
arrival = stn_shp_fty_line1[(i+1),]$group_id %>% as.character()),
max(section_select[i],
geosphere::distGeo(p1 = c(stn_shp_fty_line1[i, c("long", "lat")] %>% as.numeric()),
p2 = c(stn_shp_fty_line1[(i+1), c("long", "lat")] %>% as.numeric()))))
}
stn_shp_fty_line1 %>% select(group_id, long, lat) %>%
mutate(dist = c(0, section_select)) %>% rename(Name = group_id)
}
raw_shp <- rgdal::readOGR("shape_data/TL_SPSB_RLWAY.shp")
stn_shp <- rgdal::readOGR("shape_data/TL_SPSB_STATN.shp")
line_subway <- c('1호선', '2호선', '3호선', '4호선', '5호선', '6호선',
'7호선', '8호선', '9호선', '경의중앙선', '우이신설선',
'분당선', '신분당선', '공항선')
seoul_subwayline <- raw_shp[raw_shp@data$KOR_SBR_NM%in%line_subway,]
seoul_subwayline <- spTransform(seoul_subwayline, "+proj=longlat")
seoul_subwayline <- seoul_subwayline[str_detect(seoul_subwayline@data$SIG_CD, "^1|^4|^28"),]
dep_name <- stn_shp@data$KOR_SUB_NM
dep_name_index <- which(str_detect(dep_name, "[(]"))
dep_name_index_nm <- str_locate(dep_name[dep_name_index], "[(]")
dep_name <- as.character(dep_name)
dep_name[dep_name_index] <- str_sub(dep_name[dep_name_index], 1, dep_name_index_nm[, 1] - 1)
length_index <- str_length(dep_name[str_detect(dep_name, "역$")])
dep_name[str_detect(dep_name, "역$")] <- str_sub(dep_name[str_detect(dep_name, "역$")], 1, length_index-1)
stn_shp@data$KOR_SUB_NM <- dep_name
stn_shp <- spTransform(stn_shp, "+proj=longlat")
stn_shp_edit <- stn_shp[stn_shp@data$KOR_SUB_NM %in% subway_data_DT$Name,]
stn_shp_edit <- stn_shp_edit[str_detect(stn_shp_edit@data$SIG_CD, "^1|^4|^28"),]
get_section
seoul_subwayline_fty <- seoul_subwayline %>% fortify(region="KOR_SBR_NM")
stn_shp_fty <- stn_shp_edit %>% fortify(region='KOR_SUB_NM')
stn_shp_fty$group_id <- stn_shp_fty$group
stn_shp_fty_trim_mean <- stn_shp_fty %>% group_by(group_id) %>%
summarise(long = mean(long, trim=0.3), lat=mean(lat, trim=0.3))
line_choose <- "5"
line_1_fty <- subwayline_fty[[line_choose]]
line_1_fty %>% ggplot(aes(x=long, y=lat)) + geom_point()
line_1_fty %>% ggplot(aes(x=long, y=lat)) + geom_point()
ggplot() + geom_point(aes(x=subway_data[["1"]]$Dist, y=get_section(line_choose = "1")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["1_P"]]$Dist, y=get_section(line_choose = "1_P")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["1_A"]]$Dist, y=get_section(line_choose = "1_A")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["1_B"]]$Dist, y=get_section(line_choose = "1_B")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["2"]]$Dist, y=get_section(line_choose = "2")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["2_A"]]$Dist, y=get_section(line_choose = "2_A")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["2_B"]]$Dist, y=get_section(line_choose = "2_B")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["3"]]$Dist, y=get_section(line_choose = "3")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["4"]]$Dist, y=get_section(line_choose = "4")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["5"]]$Dist, y=get_section(line_choose = "5")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["5_A"]]$Dist, y=get_section(line_choose = "5_A")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["6"]]$Dist, y=get_section(line_choose = "6")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["6_A"]]$Dist, y=get_section(line_choose = "6_A")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["7"]]$Dist, y=get_section(line_choose = "7")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["8"]]$Dist, y=get_section(line_choose = "8")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["9"]]$Dist, y=get_section(line_choose = "9")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["K"]]$Dist, y=get_section(line_choose = "K")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["B"]]$Dist, y=get_section(line_choose = "B")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["S"]]$Dist, y=get_section(line_choose = "S")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["UI"]]$Dist, y=get_section(line_choose = "UI")$dist)) + theme_bw()
ggplot() + geom_point(aes(x=subway_data[["A"]]$Dist, y=get_section(line_choose = "A")$dist)) + theme_bw()
name_vec <- names(subwayline_fty)
compare_list <- list()
for(i in seq_along(name_vec)){
compare_list[[name_vec[i]]] <- line_compare(name_vec[i]) %>%
mutate(Time = Dist * 60 / 34000) %>%
mutate(Time = round(Time, 2),
Dist = round(Dist, 2)) %>%
select(-St_dist, -diff)
}
compare_list$`2`[1,"Dist"] <- get_unit_section(line_choose = "2", departure = "충정로", arrival="시청")$dist[1] %>% round(2)
compare_list$`2`[1,"Time"] <- (compare_list$`2`[1,"Dist"] * 60 / 34000) %>% round(2)
for(i in seq_along(name_vec)){
subway_data[[name_vec[i]]] <- compare_list[[name_vec[i]]]
}
subway_data_DT <- subway_data[[name_vec[1]]]
for(i in 2:length(name_vec)){
subway_data_DT <- rbind(subway_data_DT, subway_data[[name_vec[i]]])
}
#save(file="../data/subway_data.RData", subway_data)
#save(file="../data/subway_data_DT.RData", subway_data_DT)
make_shape_line("2") %>% plot
make_shape_line("3") %>% plot
make_shape_line("4") %>% plot
make_shape_line("5") %>% plot
make_shape_line("6") %>% plot
make_shape_line("7") %>% plot
make_shape_line("8") %>% plot
compare section
line_choose <- "1"
line_1_fty <- subwayline_fty[[line_choose]]
line_1_nms <- subway_data_DT %>% filter(Line %in% line_choose) %>% filter(!duplicated(Name))
stn_shp_fty_line1 <- stn_shp_fty_trim_mean %>%
filter(long <= max(line_1_nms$long), lat <= max(line_1_nms$lat)) %>%
mutate(group_id = str_remove(group_id, ".[1-9]")) %>%
filter(group_id %in% line_1_nms$Name) %>% filter(!duplicated(group_id))
ind <- setdiff(line_1_nms$Name, stn_shp_fty_line1$group_id)
stn_shp_fty_line1 <- stn_shp_fty_line1 %>%
rbind(line_1_nms %>%
filter(Name %in% ind) %>%
dplyr::select(Name, long, lat) %>%
mutate(Name = factor(Name)) %>% rename(group_id=Name))
stn_shp_fty_line1 <- stn_shp_fty_line1 %>%
mutate(group_id = factor(group_id, levels=line_1_nms$Name),
station_lev = as.numeric(group_id)) %>% arrange(station_lev)
stn_shp_fty_line1[30:35,]
i <- 32
section_select <- c()
long_select <- stn_shp_fty_line1[c(i, i+1),]$long # stn_shp_fty_line1[c(33, 34),]
lat_select <- stn_shp_fty_line1[c(i, i+1),]$lat
section <- line_1_fty %>% dplyr::select(long, lat, id) %>% rename(group_id=id) %>%
filter(long >= min(long_select), long <= max(long_select)) %>%
filter(lat >= min(lat_select), lat <= max(lat_select))
section <- section %>% mutate(long = round(long, 4),
lat = round(lat, 4)) %>%
filter(!duplicated(long, lat)) %>%
mutate(Name = c("종각", rep(NA, 5), "시청", NA))
section %>% ggplot(aes(x=long, y=lat)) + geom_point() +
geom_line(size=1) + geom_point(size=ifelse(is.na(section$Name), 3, 3),
shape=ifelse(is.na(section$Name), 16, 17), col="blue") +
geom_text(aes(label=Name), vjust=1.5, size=5) + ylim(c(37.5635, 37.5705)) +
xlim(c(126.976, 126.984)) + theme_bw() + xlab("경도") + ylab("위도") + scale_fill_viridis_c() + scale_color_viridis_d()
#ggsave(filename="shape_distance_ex.pdf", path="D:/workspace/seoulsubway_G/line_G/figure")
king4k1/seoulsubway documentation built on Nov. 18, 2019, 3:38 p.m.
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library(sp) library(sf) library(maptools) library(rgdal) library(rgeos) library(seoulsubway) setwd(paste0("D:/workspace/seoulsubway/rmd")) data(subway_data_DT) data(subway_data) load(file="shape_data/subwayline_fty.RData") dist_sht <- function(df, line_choose, departure, arrival){ df <- df %>% rbind(subway_data[[line_choose]] %>% filter(Name %in% c(departure, arrival)) %>% select(long, lat, Name) %>% rename(group_id = Name)) df1 <- df %>% arrange(long) %>% arrange(lat) df2 <- df %>% arrange(lat) %>% arrange(long) df3 <- df %>% arrange(lat) df4 <- df %>% arrange(long) df1_dist <- sum(sapply(1:(nrow(df1)-1), function(x){geosphere::distGeo(p1=c(df1$long[x], df1$lat[x]), p2=c(df1$long[x+1], df1$lat[x+1]))})) df2_dist <- sum(sapply(1:(nrow(df2)-1), function(x){geosphere::distGeo(p1=c(df2$long[x], df2$lat[x]), p2=c(df2$long[x+1], df2$lat[x+1]))})) df3_dist <- sum(sapply(1:(nrow(df3)-1), function(x){geosphere::distGeo(p1=c(df3$long[x], df3$lat[x]), p2=c(df3$long[x+1], df3$lat[x+1]))})) df4_dist <- sum(sapply(1:(nrow(df4)-1), function(x){geosphere::distGeo(p1=c(df4$long[x], df4$lat[x]), p2=c(df4$long[x+1], df4$lat[x+1]))})) min(df1_dist, df2_dist, df3_dist, df4_dist) } line_compare <- function(line_select){ subway_data[[line_select]] %>% rename(St_dist = Dist) %>% mutate(Dist = get_section(line_choose = line_select)$dist, diff = Dist - St_dist) } get_unit_section <- function(line_choose, departure, arrival){ line_1_fty <- subwayline_fty[[line_choose]] line_1_nms <- subway_data_DT %>% filter(Line %in% line_choose) %>% filter(Name%in%c(departure, arrival)) stn_shp_fty_line1 <- stn_shp_fty_trim_mean %>% mutate(group_id = str_remove(group_id, ".[1-9]")) %>% filter(long <= max(line_1_nms$long), lat <= max(line_1_nms$lat)) %>% filter(group_id %in% line_1_nms$Name) %>% filter(!duplicated(group_id)) ind <- setdiff(line_1_nms$Name, stn_shp_fty_line1$group_id) stn_shp_fty_line1 <- stn_shp_fty_line1 %>% rbind(line_1_nms %>% filter(Name %in% ind) %>% select(Name, long, lat) %>% mutate(Name = factor(Name)) %>% rename(group_id=Name)) long_select <- stn_shp_fty_line1$long # stn_shp_fty_line1[c(i, i+1),] lat_select <- stn_shp_fty_line1$lat section <- line_1_fty %>% select(long, lat, id) %>% rename(group_id=id) %>% filter(long >= min(long_select), long <= max(long_select)) %>% filter(lat >= min(lat_select), lat <= max(lat_select)) %>% mutate(long = round(long, 4), lat = round(lat, 4)) %>% filter(!duplicated(long, lat)) stn_shp_fty_line1[1,] %>% select(long, lat, group_id) %>% rbind(section) %>% rbind(stn_shp_fty_line1[2,] %>% select(long, lat, group_id)) %>% rename(Name = group_id) %>% mutate(dist = dist_sht(section, line_choose, departure, arrival)) } make_shape_line <- function(line_choose){ line_data <- subway_data[[line_choose]] stn_vec <- line_data$Name Spline <- list() for(i in 1:(length(stn_vec))){ departure = stn_vec[i] arrival = ifelse(is.na(stn_vec[i+1]) & line_choose %in% c("2", "6_A"), stn_vec[1], stn_vec[i+1]) if(!is.na(arrival)){ # get_unit_section(line_choose, departure, arrival) %>% ggplot(aes(x=long, y=lat)) + geom_point() ll <- get_unit_section(line_choose, departure, arrival) %>% dplyr::select(long, lat) %>% arrange(long, lat) %>% mutate_all(as.numeric) %>% as.matrix() departure_excode <- subway_data[[line_choose]] %>% filter(Name==departure) arrival_excode <- subway_data[[line_choose]] %>% filter(Name==arrival) for(j in 2:nrow(ll)){ nms <- paste0(departure_excode$ExCode, "___", arrival_excode$ExCode, "___", (j-1)) Sl <- Line(ll[c(j-1, j), ]) s1 <- Lines(list(Sl), ID = nms) Spline[[paste0(i,"_",j)]] <- s1 } } } Splineset <- SpatialLines(Spline) df <- data.frame(len = sapply(1:length(Splineset), function(i) gLength(Splineset[i, ]))) rownames(df) <- sapply(1:length(Splineset), function(i) Splineset@lines[[i]]@ID) ## SpatialLines to SpatialLinesDataFrame Sldf <- SpatialLinesDataFrame(Splineset, data = df) Sldf } get_section <- function(line_choose){ line_1_fty <- subwayline_fty[[line_choose]] line_1_nms <- subway_data_DT %>% filter(Line %in% line_choose) %>% filter(!duplicated(Name)) stn_shp_fty_line1 <- stn_shp_fty_trim_mean %>% filter(long <= max(line_1_nms$long), lat <= max(line_1_nms$lat)) %>% mutate(group_id = str_remove(group_id, ".[1-9]")) %>% filter(group_id %in% line_1_nms$Name) %>% filter(!duplicated(group_id)) ind <- setdiff(line_1_nms$Name, stn_shp_fty_line1$group_id) stn_shp_fty_line1 <- stn_shp_fty_line1 %>% rbind(line_1_nms %>% filter(Name %in% ind) %>% select(Name, long, lat) %>% mutate(Name = factor(Name)) %>% rename(group_id=Name)) stn_shp_fty_line1 <- stn_shp_fty_line1 %>% mutate(group_id = factor(group_id, levels=line_1_nms$Name), station_lev = as.numeric(group_id)) %>% arrange(station_lev) section_select <- c() for(i in 1:(nrow(stn_shp_fty_line1)-1)){ long_select <- stn_shp_fty_line1[c(i, i+1),]$long # stn_shp_fty_line1[c(33, 34),] lat_select <- stn_shp_fty_line1[c(i, i+1),]$lat section <- line_1_fty %>% select(long, lat, id) %>% rename(group_id=id) %>% filter(long >= min(long_select), long <= max(long_select)) %>% filter(lat >= min(lat_select), lat <= max(lat_select)) section <- section %>% mutate(long = round(long, 4), lat = round(lat, 4)) %>% filter(!duplicated(long, lat)) group_index <- unique(section$group_id) #section %>% ggplot(aes(x=long, y=lat, col=group_id)) + geom_point() if(length(group_index) == 0){ section_select[i] <- geosphere::distGeo(p1 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric(), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()) ### 두 역이 직선거리여서 선이 정의되지 않는 경우 } if(length(group_index) == 1){ if(nrow(section) > 1){ sum_section <- sum(sapply(1:(nrow(section)-1),function(x){ geosphere::distGeo(p1=c(section$long[x], section$lat[x]), p2=c(section$long[x+1], section$lat[x+1]))})) section_select[i] <- sum_section + min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) + min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric())) }else{ section_select[i] <- min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) + min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric())) } } if(length(group_index) == 2){ section_list_i <- list() for(j in seq_along(group_index)){ section_i <- section %>% filter(group_id == group_index[j]) ## 2개 shp line으로 두 역 사이가 선택되는 경우 if(nrow(section_i) > 1){ if(sum(sapply(1:(nrow(section_i)-1), function(x){ geosphere::distGeo(p1=c(section_i$long[x], section_i$lat[x]), p2=c(section_i$long[x+1], section_i$lat[x+1])) }) >= 300)==1){ section_i <- section_i %>% arrange(long, lat) sum_section <- sum(sapply(1:(nrow(section_i)-1), function(x){ geosphere::distGeo(p1=c(section_i$long[x], section_i$lat[x]), p2=c(section_i$long[x+1], section_i$lat[x+1]))})) }else{ sum_section <- sum(sapply(1:(nrow(section_i)-1), function(x){ geosphere::distGeo(p1=c(section_i$long[x], section_i$lat[x]), p2=c(section_i$long[x+1], section_i$lat[x+1])) })) } section_list_i[[j]] <- sum_section + min( geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) }else{ section_list_i[[j]] <- min( geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section_i[1,"long"], section_i[1,"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section_i[nrow(section_i),"long"], section_i[nrow(section_i),"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) } } shortest_list <- c() for(k in 1:nrow(section[which(section$group_id == group_index[1]),])){ shortest_list[k] <- min(geosphere::distGeo(p1 = section[which(section$group_id == group_index[1])[k],], p2 = section[which(section$group_id == group_index[2]),])) } section_select[i] <- min(shortest_list) + (section_list_i %>% unlist() %>% sum()) } if(length(group_index) > 2){ section <- section %>% arrange(long, lat) sum_section <- sum(sapply(1:(nrow(section)-1), function(x){ geosphere::distGeo(p1=c(section$long[x], section$lat[x]), p2=c(section$long[x+1], section$lat[x+1]))})) section_select[i] <- sum_section + min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]), p2 = stn_shp_fty_line1[c(i),c("long", "lat")] %>% as.numeric())) + min(geosphere::distGeo(p1 = c(section[1,"long"], section[1,"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric()), geosphere::distGeo(p1 = c(section[nrow(section),"long"], section[nrow(section),"lat"]), p2 = stn_shp_fty_line1[c(i+1),c("long", "lat")] %>% as.numeric())) }# stn_shp_fty_line1[c(i, i+1),]i section_select[i] <- min(dist_sht(section, line_choose, departure = stn_shp_fty_line1[i,]$group_id %>% as.character(), arrival = stn_shp_fty_line1[(i+1),]$group_id %>% as.character()), max(section_select[i], geosphere::distGeo(p1 = c(stn_shp_fty_line1[i, c("long", "lat")] %>% as.numeric()), p2 = c(stn_shp_fty_line1[(i+1), c("long", "lat")] %>% as.numeric())))) } stn_shp_fty_line1 %>% select(group_id, long, lat) %>% mutate(dist = c(0, section_select)) %>% rename(Name = group_id) } raw_shp <- rgdal::readOGR("shape_data/TL_SPSB_RLWAY.shp") stn_shp <- rgdal::readOGR("shape_data/TL_SPSB_STATN.shp") line_subway <- c('1호선', '2호선', '3호선', '4호선', '5호선', '6호선', '7호선', '8호선', '9호선', '경의중앙선', '우이신설선', '분당선', '신분당선', '공항선') seoul_subwayline <- raw_shp[raw_shp@data$KOR_SBR_NM%in%line_subway,] seoul_subwayline <- spTransform(seoul_subwayline, "+proj=longlat") seoul_subwayline <- seoul_subwayline[str_detect(seoul_subwayline@data$SIG_CD, "^1|^4|^28"),] dep_name <- stn_shp@data$KOR_SUB_NM dep_name_index <- which(str_detect(dep_name, "[(]")) dep_name_index_nm <- str_locate(dep_name[dep_name_index], "[(]") dep_name <- as.character(dep_name) dep_name[dep_name_index] <- str_sub(dep_name[dep_name_index], 1, dep_name_index_nm[, 1] - 1) length_index <- str_length(dep_name[str_detect(dep_name, "역$")]) dep_name[str_detect(dep_name, "역$")] <- str_sub(dep_name[str_detect(dep_name, "역$")], 1, length_index-1) stn_shp@data$KOR_SUB_NM <- dep_name stn_shp <- spTransform(stn_shp, "+proj=longlat") stn_shp_edit <- stn_shp[stn_shp@data$KOR_SUB_NM %in% subway_data_DT$Name,] stn_shp_edit <- stn_shp_edit[str_detect(stn_shp_edit@data$SIG_CD, "^1|^4|^28"),]
get_section
seoul_subwayline_fty <- seoul_subwayline %>% fortify(region="KOR_SBR_NM") stn_shp_fty <- stn_shp_edit %>% fortify(region='KOR_SUB_NM') stn_shp_fty$group_id <- stn_shp_fty$group stn_shp_fty_trim_mean <- stn_shp_fty %>% group_by(group_id) %>% summarise(long = mean(long, trim=0.3), lat=mean(lat, trim=0.3)) line_choose <- "5" line_1_fty <- subwayline_fty[[line_choose]] line_1_fty %>% ggplot(aes(x=long, y=lat)) + geom_point() line_1_fty %>% ggplot(aes(x=long, y=lat)) + geom_point() ggplot() + geom_point(aes(x=subway_data[["1"]]$Dist, y=get_section(line_choose = "1")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["1_P"]]$Dist, y=get_section(line_choose = "1_P")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["1_A"]]$Dist, y=get_section(line_choose = "1_A")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["1_B"]]$Dist, y=get_section(line_choose = "1_B")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["2"]]$Dist, y=get_section(line_choose = "2")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["2_A"]]$Dist, y=get_section(line_choose = "2_A")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["2_B"]]$Dist, y=get_section(line_choose = "2_B")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["3"]]$Dist, y=get_section(line_choose = "3")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["4"]]$Dist, y=get_section(line_choose = "4")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["5"]]$Dist, y=get_section(line_choose = "5")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["5_A"]]$Dist, y=get_section(line_choose = "5_A")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["6"]]$Dist, y=get_section(line_choose = "6")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["6_A"]]$Dist, y=get_section(line_choose = "6_A")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["7"]]$Dist, y=get_section(line_choose = "7")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["8"]]$Dist, y=get_section(line_choose = "8")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["9"]]$Dist, y=get_section(line_choose = "9")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["K"]]$Dist, y=get_section(line_choose = "K")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["B"]]$Dist, y=get_section(line_choose = "B")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["S"]]$Dist, y=get_section(line_choose = "S")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["UI"]]$Dist, y=get_section(line_choose = "UI")$dist)) + theme_bw() ggplot() + geom_point(aes(x=subway_data[["A"]]$Dist, y=get_section(line_choose = "A")$dist)) + theme_bw() name_vec <- names(subwayline_fty) compare_list <- list() for(i in seq_along(name_vec)){ compare_list[[name_vec[i]]] <- line_compare(name_vec[i]) %>% mutate(Time = Dist * 60 / 34000) %>% mutate(Time = round(Time, 2), Dist = round(Dist, 2)) %>% select(-St_dist, -diff) } compare_list$`2`[1,"Dist"] <- get_unit_section(line_choose = "2", departure = "충정로", arrival="시청")$dist[1] %>% round(2) compare_list$`2`[1,"Time"] <- (compare_list$`2`[1,"Dist"] * 60 / 34000) %>% round(2) for(i in seq_along(name_vec)){ subway_data[[name_vec[i]]] <- compare_list[[name_vec[i]]] } subway_data_DT <- subway_data[[name_vec[1]]] for(i in 2:length(name_vec)){ subway_data_DT <- rbind(subway_data_DT, subway_data[[name_vec[i]]]) } #save(file="../data/subway_data.RData", subway_data) #save(file="../data/subway_data_DT.RData", subway_data_DT)
make_shape_line("2") %>% plot make_shape_line("3") %>% plot make_shape_line("4") %>% plot make_shape_line("5") %>% plot make_shape_line("6") %>% plot make_shape_line("7") %>% plot make_shape_line("8") %>% plot
compare section
line_choose <- "1" line_1_fty <- subwayline_fty[[line_choose]] line_1_nms <- subway_data_DT %>% filter(Line %in% line_choose) %>% filter(!duplicated(Name)) stn_shp_fty_line1 <- stn_shp_fty_trim_mean %>% filter(long <= max(line_1_nms$long), lat <= max(line_1_nms$lat)) %>% mutate(group_id = str_remove(group_id, ".[1-9]")) %>% filter(group_id %in% line_1_nms$Name) %>% filter(!duplicated(group_id)) ind <- setdiff(line_1_nms$Name, stn_shp_fty_line1$group_id) stn_shp_fty_line1 <- stn_shp_fty_line1 %>% rbind(line_1_nms %>% filter(Name %in% ind) %>% dplyr::select(Name, long, lat) %>% mutate(Name = factor(Name)) %>% rename(group_id=Name)) stn_shp_fty_line1 <- stn_shp_fty_line1 %>% mutate(group_id = factor(group_id, levels=line_1_nms$Name), station_lev = as.numeric(group_id)) %>% arrange(station_lev) stn_shp_fty_line1[30:35,] i <- 32 section_select <- c() long_select <- stn_shp_fty_line1[c(i, i+1),]$long # stn_shp_fty_line1[c(33, 34),] lat_select <- stn_shp_fty_line1[c(i, i+1),]$lat section <- line_1_fty %>% dplyr::select(long, lat, id) %>% rename(group_id=id) %>% filter(long >= min(long_select), long <= max(long_select)) %>% filter(lat >= min(lat_select), lat <= max(lat_select)) section <- section %>% mutate(long = round(long, 4), lat = round(lat, 4)) %>% filter(!duplicated(long, lat)) %>% mutate(Name = c("종각", rep(NA, 5), "시청", NA)) section %>% ggplot(aes(x=long, y=lat)) + geom_point() + geom_line(size=1) + geom_point(size=ifelse(is.na(section$Name), 3, 3), shape=ifelse(is.na(section$Name), 16, 17), col="blue") + geom_text(aes(label=Name), vjust=1.5, size=5) + ylim(c(37.5635, 37.5705)) + xlim(c(126.976, 126.984)) + theme_bw() + xlab("경도") + ylab("위도") + scale_fill_viridis_c() + scale_color_viridis_d() #ggsave(filename="shape_distance_ex.pdf", path="D:/workspace/seoulsubway_G/line_G/figure")
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