r - 根据 gps 坐标列表更改基于开放街道 map 的 igraph 中路径边缘的权重

Question

我想根据 gps 坐标更改路线部分的重量。
为此，我想获取计算路线边缘的 gps 坐标，然后将它们与我拥有的坐标列表进行比较，如果我的列表中的坐标与路线末端的坐标匹配，我想更改权重那个边缘。
目前我有计算路线并改变整条路线权重的代码。
我得到了路线的坐标，但我无法获得返回图表所需的步骤..我的大脑刚刚关闭:)

library(osmar)
library(igraph)

### Get data ----
src <- osmsource_api(url = "https://api.openstreetmap.org/api/0.6/")
muc_bbox <- center_bbox(11.575278, 48.137222, 1000, 1000)
muc <- get_osm(muc_bbox, src)

### Reduce to highways: ----
hways <- subset(muc, way_ids = find(muc, way(tags(k == "highway"))))
hways <- find(hways, way(tags(k == "name")))
hways <- find_down(muc, way(hways))
hways <- subset(muc, ids = hways)

#### Plot data ----
## Plot complete data and highways on top:
plot(muc)
plot_ways(muc, col = "lightgrey")
plot_ways(hways, col = "coral", add = TRUE)

### Define route start and end nodes: ----
id<-find(muc, node(tags(v %agrep% "Sendlinger Tor")))[1]
hway_start_node <-find_nearest_node(muc, id, way(tags(k == "highway"))) 
hway_start <- subset(muc, node(hway_start_node))

id <- find(muc, node(attrs(lon > 11.58 & lat > 48.15)))[1]
hway_end_node <- find_nearest_node(muc, id, way(tags(k == "highway")))
hway_end <- subset(muc, node(hway_end_node))

## Add the route start and and nodes to the plot:
plot_nodes(hway_start, add = TRUE, col = "red", pch = 19, cex = 2)
plot_nodes(hway_end, add = TRUE, col = "red", pch = 19, cex = 2)

### Create street graph ----
gr <- as.undirected(as_igraph(hways))

### Compute shortest route: ----
# Calculate route
route <- function(start_node,end_node) {
  get.shortest.paths(gr,
                     from = as.character(start_node),
                     to = as.character(end_node), 
                     mode = "all")[[1]][[1]]}
# Plot route
plot.route <- function(r,color) {
  r.nodes.names <- as.numeric(V(gr)[r]$name)
  r.ways <- subset(hways, ids = osmar::find_up(hways, node(r.nodes.names)))
  plot_ways(r.ways, add = TRUE, col = color, lwd = 2)
}


r <- route(hway_start_node,hway_end_node)
color <- colorRampPalette(c("springgreen","royalblue"))(nways)[numway]
plot.route(r,color)

route_nodes <- as.numeric(V(gr)[r]$name)
#We construct a newosmarobject containing only elements 
#related to the nodes defining the route:

route_ids <- find_up(hways, node(route_nodes))
route_muc <- subset(hways, ids = route_ids)

#Route details.
#In order to present route details like street names,
#distances, and directions we have to work directly on the internals of the osmar objects.
#We start by extracting the route’s node IDs (which are in the correct order) 
#and the way IDs       (whichwe have to order)
#where the nodes are members:

node_ids <- route_muc$nodes$attrs$id

way_ids <- local({
  w <- match(node_ids, route_muc$ways$refs$ref)
  route_muc$ways$refs$id[w]
})

#Then we extract the names of the ways in the correct order:>
way_names <- local({
  n <- subset(route_muc$ways$tags, k == "name")
  n[match(way_ids, n$id), "v"]
})

#The next step is to extract the nodes’ coordinates,>
node_coords <- route_muc$nodes$attrs[, c("lon", "lat")]

#and to compute the distances (meters) and the bearings (degrees) 
#between successive nodes (using thepackagegeosphere):

node_dirs <- local({
      n <- nrow(node_coords)
      from <- 1:(n - 1)
      to <- 2:n
      cbind(dist = c(0, distHaversine(node_coords[from,], node_coords[to,])),
            bear = c(0, bearing(node_coords[from,], node_coords[to,])))
    })



#Finally, we pack together all the information, 
#and additionally compute the cumulative distance

route_details <- data.frame(way_names, node_dirs)
route_details$cdist <- cumsum(route_details$dist)
route_details$coord <- node_coords
route_details$id <- node_ids
print(route_details)

#here we select randomly parts from the route

gps_points<-route_details[sample(1:nrow(route_details), 10,replace=FALSE),] 

在这里，我想根据选定的 gps 坐标更改图形部分的权重。
我得到了获得 gps 坐标的方法，但我只是在这里挂断了精神，回到图表以更改那里的权重。

# Currently i can only Modify current route weight
E(gr)[r]$weight <- E(gr)[r]$weight * 2

谢谢你的帮助!
此致。

Answer 1

以下脚本查找与坐标列表 ( wished.coord ) 相邻的边的 id，以便您可以修改权重:

library(osmar)
library(igraph)
library(tidyr)
library(dplyr)

### Get data ----
src <- osmsource_api(url = "https://api.openstreetmap.org/api/0.6/")
muc_bbox <- center_bbox(11.575278, 48.137222, 1000, 1000)
muc <- get_osm(muc_bbox, src)

### Reduce to highways: ----
hways <- subset(muc, way_ids = find(muc, way(tags(k == "highway"))))
hways <- find(hways, way(tags(k == "name")))
hways <- find_down(muc, way(hways))
hways <- subset(muc, ids = hways)

#### Plot data ----
## Plot complete data and highways on top:
plot(muc)
plot_ways(muc, col = "lightgrey")
plot_ways(hways, col = "coral", add = TRUE)

### Define route start and end nodes: ----
id<-find(muc, node(tags(v %agrep% "Sendlinger Tor")))[1]
hway_start_node <-find_nearest_node(muc, id, way(tags(k == "highway"))) 
hway_start <- subset(muc, node(hway_start_node))

id <- find(muc, node(attrs(lon > 11.58 & lat > 48.15)))[1]
hway_end_node <- find_nearest_node(muc, id, way(tags(k == "highway")))
hway_end <- subset(muc, node(hway_end_node))

## Add the route start and and nodes to the plot:
plot_nodes(hway_start, add = TRUE, col = "red", pch = 19, cex = 2)
plot_nodes(hway_end, add = TRUE, col = "red", pch = 19, cex = 2)

### Create street graph ----
gr <- as.undirected(as_igraph(hways))

### Compute shortest route: ----
# Calculate route
route <- function(start_node,end_node) {
  get.shortest.paths(gr,
                     from = as.character(start_node),
                     to = as.character(end_node), 
                     mode = "all")[[1]][[1]]}
# Plot route
plot.route <- function(r,color) {
  r.nodes.names <- as.numeric(V(gr)[r]$name)
  r.ways <- subset(hways, ids = osmar::find_up(hways, node(r.nodes.names)))
  plot_ways(r.ways, add = TRUE, col = color, lwd = 2)
}
nways <-  1
numway <- 1
r <- route(hway_start_node,hway_end_node)

# Plot route

color <- colorRampPalette(c("springgreen","royalblue"))(nways)[numway]
plot.route(r,color)


## Route details ----
# Construct a new osmar object containing only elements 
# related to the nodes defining the route:
route_nodes <- as.numeric(V(gr)[r]$name)
route_ids <- find_up(hways, node(route_nodes))

osmar.route <- subset(hways, ids = route_ids)
osmar.nodes.ids <- osmar.route$nodes$attrs$id

# Extract the nodes’ coordinates,
osmar.nodes.coords <- osmar.route$nodes$attrs[, c("lon", "lat")]
osmar.nodes <- cbind(data.frame(ids = osmar.nodes.ids),
                     data.frame(ids_igraph = as.numeric(V(gr)[r]) ),
                     osmar.nodes.coords) 


## Find edges ids containing points of interest ----
wished.coords <- data.frame(wlon = c(11.57631),
                            wlat = c(48.14016)) 


# Calculate all distances
distances <- crossing(osmar.nodes,wished.coords) %>%
             mutate(dist = geosphere::distHaversine(cbind(lon,lat),cbind(wlon,wlat)))


# Select nodes below maximum distance :
mindist <- 50 #m

wished.nodes <- distances %>% filter(dist < mindist)

# Select edges incident to these nodes :
selected.edges <- unlist(incident_edges(gr,V(gr)[wished.nodes$ids_igraph]))

# Weight of selected edges
E(gr)[selected.edges]$weight