R语言sfnetworks包，st_network_cost()

R语言sfnetworks包，st_network_cost()#计算空间网络的成本矩阵

# Mon Jul 26 16:59:02 2021 -

# 字符编码：UTF-8
# R 版本：R x64 4.1 for window 11
# cgh163email@163.com
# 个人笔记不负责任，拎了个梨🍐🍈
#.rs.restartR()
require(sfnetworks)
rm(list = ls());gc()

?st_network_cost()#计算空间网络的成本矩阵

library(sf, quietly = TRUE)
library(tidygraph, quietly = TRUE)

#创建以边长度作为权重的网络。
#这些权重将自动用于最短路径计算。
net = as_sfnetwork(roxel, directed = FALSE) %>%
  st_transform(3035) %>%
  activate("edges") %>%
  mutate(weight = edge_length())

#提供节点索引。
st_network_cost(net, from = c(495, 121), to = c(495, 121))
#>          [,1]     [,2]
#> [1,]    0.000 2094.555
#> [2,] 2094.555    0.000
# Providing nodes as spatial points.
# Points that don't equal a node will be snapped to their nearest node.
p1 = st_geometry(net, "nodes")[495] + st_sfc(st_point(c(50, -50)))
st_crs(p1) = st_crs(net)
p2 = st_geometry(net, "nodes")[121] + st_sfc(st_point(c(-10, 100)))
st_crs(p2) = st_crs(net)

st_network_cost(net, from = c(p1, p2), to = c(p1, p2))
#>          [,1]     [,2]
#> [1,]    0.000 2094.555
#> [2,] 2094.555    0.000
# Using another column for weights.
net %>%
  activate("edges") %>%
  mutate(foo = runif(n(), min = 0, max = 1)) %>%
  st_network_cost(c(p1, p2), c(p1, p2), weights = "foo")
#>          [,1]     [,2]
#> [1,]  0.00000 10.29983
#> [2,] 10.29983  0.00000
# Not providing any from or to points includes all nodes by default.
with_graph(net, graph_order()) # Our network has 701 nodes.
cost_matrix = st_network_cost(net)
dim(cost_matrix)
#> [1] 701 701