Question

我有一个sf数据框，其中包含标记沿许多单向街道的交叉点的位置的点。除了“几何”列外，一列包含街道名称，另一列包含交叉路口在单向街道上的相对位置。

下面是一个玩具示例。第一行是Arch St.的第一个交集，第二行是Arch St.的第二个交集，依此类推。

library(sf)

intersections <- structure(list(street = c("ARCH ST", "ARCH ST", "ARCH ST", "SANSOM ST", 
"SANSOM ST", "SANSOM ST"), number = c(1L, 2L, 3L, 1L, 2L, 3L), 
    geometry = structure(list(structure(c(2699665.2606043, 236074.947200272
    ), class = c("XY", "POINT", "sfg")), structure(c(2699402.74765515, 
    236109.729280198), class = c("XY", "POINT", "sfg")), structure(c(2699202.95996668, 
    236136.613760229), class = c("XY", "POINT", "sfg")), structure(c(2699431.38476158, 
    234437.663731016), class = c("XY", "POINT", "sfg")), structure(c(2699162.09261096, 
    234476.514355583), class = c("XY", "POINT", "sfg")), structure(c(2697100.77148795, 
    234809.605567052), class = c("XY", "POINT", "sfg"))), precision = 0, bbox = structure(c(xmin = 2697100.77148795, 
    ymin = 234437.663731016, xmax = 2699665.2606043, ymax = 236136.613760229
    ), class = "bbox"), crs = structure(list(epsg = 2272L, proj4string = "+proj=lcc +lat_1=40.96666666666667 +lat_2=39.93333333333333 +lat_0=39.33333333333334 +lon_0=-77.75 +x_0=600000 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=us-ft +no_defs"), class = "crs"), n_empty = 0L, class = c("sfc_POINT", 
    "sfc"))), row.names = c(NA, -6L), class = c("sf", "tbl_df", 
"tbl", "data.frame"), sf_column = "geometry", agr = structure(c(street = NA_integer_, 
number = NA_integer_), class = "factor", .Label = c("constant", 
"aggregate", "identity")))

> intersections
Simple feature collection with 6 features and 2 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: 2697101 ymin: 234437.7 xmax: 2699665 ymax: 236136.6
epsg (SRID):    2272
proj4string:    +proj=lcc +lat_1=40.96666666666667 +lat_2=39.93333333333333 +lat_0=39.33333333333334 +lon_0=-77.75 +x_0=600000 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=us-ft +no_defs

# A tibble: 6 x 3
  street    number                 geometry
  <chr>      <int> <POINT [US_survey_foot]>
1 ARCH ST        1       (2699665 236074.9)
2 ARCH ST        2       (2699403 236109.7)
3 ARCH ST        3       (2699203 236136.6)
4 SANSOM ST      1       (2699431 234437.7)
5 SANSOM ST      2       (2699162 234476.5)
6 SANSOM ST      3       (2697101 234809.6)

我使用mp_matrix()包中的mp_get_matrix()和mapsapi，添加一列来显示从每个十字路口到该街道上下一个十字路口的行驶时间（最后一个路口，则得到NA）。

理想的情况是，如下所示：

     street number travel_time_sec                 geometry
1   ARCH ST      1             210 POINT (2699665 236074.9)
2   ARCH ST      2             180 POINT (2699403 236109.7)
3   ARCH ST      3              NA POINT (2699203 236136.6)
4 SANSOM ST      1             150 POINT (2699431 234437.7)
5 SANSOM ST      2             175 POINT (2699162 234476.5)
6 SANSOM ST      3              NA POINT (2697101 234809.6)

如何按组（即街道）遍历sf数据帧中的行，告诉每一行对该组中的下一行执行操作以填充新列，如果没有，则返回NA是否存在下一行？

最后，由于mp_matrix()调用了Google Maps API（该工具需要付费），因此请改用st_distance()中的sf函数来生成以下内容。

     street number travel_distance                 geometry
1   ARCH ST      1             576 POINT (2699665 236074.9)
2   ARCH ST      2             397 POINT (2699403 236109.7)
3   ARCH ST      3              NA POINT (2699203 236136.6)
4 SANSOM ST      1             410 POINT (2699431 234437.7)
5 SANSOM ST      2             440 POINT (2699162 234476.5)
6 SANSOM ST      3              NA POINT (2697101 234809.6)

非常感谢您的帮助。

Answer 1

我正在处理您的示例，但无法使用travel distance函数获得相同的st_distance。

st_distance(intersections$geometry[1], intersections$geometry[2])

Units: [US_survey_foot]
         [,1]
[1,] 264.8072

使用这些代码可以完成遍历行本身的循环或矢量化操作

# used librarys
library(units)
library(tidyverse)
library(sf)

# find distance function
find_Distance <- function(x) {

  # create lead list
  x_lead <- x[2:length(x)]

  # create distance matrix
  distance_matrix <- st_distance(x, x_lead)

  # diagonal of the distance matrix is your desired output, fill last entry with NA and 
  # unit
  c(diag(distance_matrix), set_units(NA, "US_survey_foot"))

}

# group by street and calculate distance
intersections <- group_by(intersections, street) %>%
  mutate(travel_distance = find_Distance(geometry))

# if needed, set unit of travel distance
units(intersections$travel_distance) <- as_units("US_survey_foot")

按组将功能应用于每一行和后续行

1 个答案: