如何使用R选择/查找与列表（X/Y）距离内的坐标

我有一个数据框，其中X/Y位置列表>2000行。我想要的是根据最大距离选择或查找所有行/位置。例如，从数据框中选择彼此距离在1-100公里之间的所有位置。有什么建议吗？

您需要以某种方式确定每对行之间的距离。 最简单的方法是使用相应的距离矩阵

# Assuming Thresh is your threshold
thresh <- 10

# create some sample data
set.seed(123)
DT <- data.table(X=sample(-10:10, 5, TRUE), Y=sample(-10:10, 5, TRUE))

# create the disance matrix
distTable <- matrix(apply(createTable(DT), 1, distance), nrow=nrow(DT))

# remove the lower.triangle since we have symmetry (we don't want duplicates)
distTable[lower.tri(distTable)] <- NA

# Show which rows are above the threshold
pairedRows <- which(distTable >= thresh, arr.ind=TRUE)
colnames(pairedRows) <- c("RowA", "RowB")  # clean up the names

# pair-up all of the rows
createTable <- function(DT)   
  expand.grid(apply(DT, 1, list), apply(DT, 1, list))

# simple cartesian/pythagorean distance 
distance <- function(CoordPair)
  sqrt(sum((CoordPair[[2]][[1]] - CoordPair[[1]][[1]])^2, na.rm=FALSE))

我们得到：

> pairedRows
     RowA RowB
[1,]    1    2
[2,]    1    3
[3,]    2    3
[4,]    1    4
[5,]    3    4
[6,]    1    5
[7,]    3    5

这是用于创建距离矩阵的两个函数

# Assuming Thresh is your threshold
thresh <- 10

# create some sample data
set.seed(123)
DT <- data.table(X=sample(-10:10, 5, TRUE), Y=sample(-10:10, 5, TRUE))

# create the disance matrix
distTable <- matrix(apply(createTable(DT), 1, distance), nrow=nrow(DT))

# remove the lower.triangle since we have symmetry (we don't want duplicates)
distTable[lower.tri(distTable)] <- NA

# Show which rows are above the threshold
pairedRows <- which(distTable >= thresh, arr.ind=TRUE)
colnames(pairedRows) <- c("RowA", "RowB")  # clean up the names

# pair-up all of the rows
createTable <- function(DT)   
  expand.grid(apply(DT, 1, list), apply(DT, 1, list))

# simple cartesian/pythagorean distance 
distance <- function(CoordPair)
  sqrt(sum((CoordPair[[2]][[1]] - CoordPair[[1]][[1]])^2, na.rm=FALSE))

---

我对你的问题不太清楚，但假设你的意思是，你想获取每一行坐标，并找到坐标在一定距离内的所有其他行：

# Create data set for example

set.seed(42)
x <- sample(-100:100, 10)
set.seed(456)
y <- sample(-100:100, 10)

coords <- data.frame(
  "x" = x,
  "y" = y)

# Loop through all rows

lapply(1:nrow(coords), function(i) {
  dis <- sqrt(
    (coords[i,"x"] - coords[, "x"])^2 + # insert your preferred 
    (coords[i,"y"] - coords[, "y"])^2   # distance calculation here
  ) 
  names(dis) <- 1:nrow(coords)          # replace this part with an index or 
                                        # row names if you have them
  dis[dis > 0 & dis <= 100]             # change numbers to preferred threshold
})

[[1]]
2        6        7        9       10 
25.31798 95.01579 40.01250 30.87070 73.75636 

[[2]]
1         6         7         9        10 
25.317978 89.022469 51.107729  9.486833 60.539243 

[[3]]
5        6        8 
70.71068 91.78780 94.86833 

[[4]]
5       10 
40.16217 99.32774 

[[5]]
3        4        6       10 
70.71068 40.16217 93.40771 82.49242 

[[6]]
1        2        3        5        7        8        9       10 
95.01579 89.02247 91.78780 93.40771 64.53681 75.66373 97.08244 34.92850 

[[7]]
1        2        6        9       10 
40.01250 51.10773 64.53681 60.41523 57.55867 

[[8]]
3        6 
94.86833 75.66373 

[[9]]
1         2         6         7        10 
30.870698  9.486833 97.082439 60.415230 67.119297 

[[10]]
1        2        4        5        6        7        9 
73.75636 60.53924 99.32774 82.49242 34.92850 57.55867 67.11930 

---

这些是纬度/经度还是在其他笛卡尔空间中？它们是投影坐标稍微澄清一下-您想如何定义簇/输出？e、 例如，如果沿着直线样带有位置A、B、C、D，相隔60公里，你是否返回一个{A、B、C、D}列表，因为它们都在一个连接的簇中？或者{A，B}，{B，C}，{C，D}？你能举一个可复制的例子吗。。。是的，我很抱歉。我意识到这需要更多的澄清，但我不确定什么是最好的解决办法。例如，我最初创建了一个距离矩阵，其中包含位置/栖息地之间的最小和最大距离，如下所示：sitesfossil包可能会提供一些帮助？地球距离