在 data.table 上使用 geosphere distm 函数计算距离 [英] Using the geosphere distm function on a data.table to calculate distances

问题描述

我创建了一个包含 6 列的 data.table.我的 data.table 有一列比较两个位置:位置 1 和位置 2.我正在尝试使用 distm 函数计算每行位置之间的距离，创建第 7 列.geosphere 包中的 distm 包需要两个不同的向量来计算每个纬度/经度组合.我下面的代码不起作用，所以我想弄清楚如何为函数提供向量.

I've created a data.table in that has 6 columns. My data.table has a columns compairing two locations: Location 1 and Location 2. I'm trying to use the distm function to calculate the distance between the locations on each row, creating a 7th column. The distm package in the geosphere package requires two different vectors for each lat/long combo to be calculated against. My code below does not work, so I'm trying to figure out how to provide vectors to the function.

LOC_1_ID LOC1_LAT_CORD LOC1_LONG_CORD LOC_2_ID LOC2_LAT_CORD LOC2_LONG_CORD
 1       35.68440        -80.48090        70624    34.86752   -82.46632
 6       35.49770        -80.62870        70624    34.86752   -82.46632
10       35.66042        -80.50053        70624    34.86752   -82.46632

假设 res 保存了 data.table，下面的代码不起作用.

Assuming res holds the data.table the below code does not work.

 res[,DISTANCE := distm(c(LOC1_LAT_CORD, LOC1_LONG_CORD),c(LOC2_LAT_CORD, LOC2_LONG_CORD), fun=distHaversine)*0.000621371]

如果我要提取每个向量，则该函数可以正常工作.

If I were to pull out each vector the function works fine.

loc1 <- res[LOC1_ID == 1,.(LOC1_LAT_CORD, LOC1_LONG_CORD)]
loc2 <- res[LOC2_ID==70624,.(LOC2_LAT_CORD, LOC2_LONG_CORD)]
distm(loc1, loc2, fun=distHaversine)

真的，我的问题是当该函数需要向量作为参数时，如何应用函数来选择 data.table 中的列.

Really, my question is how to apply functions to select columns within a data.table when that function requires vectors as parameters.

推荐答案

distm 函数生成一组点的距离矩阵.如果您只是比较每一行上的点并添加一列，您确定这是您想要的功能吗?

The distm fucntion generates a Distance matrix of a set of points. Are you sure this is the function you want if you're just comparing the points on each row, and adding one column?

听起来您实际上想要 distHaversine 或 distGeo

It sounds like you actually want either distHaversine or distGeo

library(data.table)
library(geosphere)

dt <- read.table(text = "LOC_1_ID LOC1_LAT_CORD LOC1_LONG_CORD LOC_2_ID LOC2_LAT_CORD LOC2_LONG_CORD
1       35.68440        -80.48090        70624    34.86752   -82.46632
6       35.49770        -80.62870        70624    34.86752   -82.46632
10       35.66042        -80.50053        70624    34.86752   -82.46632", header = T)

setDT(dt)
dt[, distance_hav := distHaversine(matrix(c(LOC1_LONG_CORD, LOC1_LAT_CORD), ncol = 2),
                                   matrix(c(LOC2_LONG_CORD, LOC2_LAT_CORD), ncol = 2))]

#     LOC_1_ID LOC1_LAT_CORD LOC1_LONG_CORD LOC_2_ID LOC2_LAT_CORD LOC2_LONG_CORD distance_hav
# 1:        1      35.68440      -80.48090    70624      34.86752      -82.46632     202046.3
# 2:        6      35.49770      -80.62870    70624      34.86752      -82.46632     181310.0
# 3:       10      35.66042      -80.50053    70624      34.86752      -82.46632     199282.1

<小时>

更新:这个答案提供了一个更高效的 distHaversine 版本，用于 >data.table

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Update: This answer gives a more efficient version of distHaversine for use in data.table

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