Clash Royale CLAN TAG#URR8PPP

Fast way to save lines from coordinate groupings in R

I'm generating paths from jogging coordinates. A sample like what I have can be reproduced below:

#Reproduce Data
library(data.table)
library(sf)
dt <- data.table(lon=sample(c(380:390), 1000000, replace = TRUE)/10,lat=sample(c(80:90), 1000000, replace = TRUE)/10, pgrp=rep(c(1:100),10000))
tpathline <- st_as_sf(dt, coords = c("lon","lat"),crs=4326)


The below to compile the points in groups of lines takes FOREVER. I have a bunch of these to do, is there a faster/better way to compile lines than the dplyr pipe below?

#Works but slowest thing ever
library(dplyr)
baseline <- tpathline %>%
dplyr::group_by(pgrp) %>%
dplyr::summarise(do_union=F) %>%
sf::st_cast("MULTILINESTRING")


Thanks in advance!!!

2 Answers
2

This is my general approach when working with sf and data.table, and it's pretty quick too.

sf

data.table

library(data.table)
library(sf)
dt <- data.table(lon=sample(c(380:390), 1000000, replace = TRUE)/10,lat=sample(c(80:90), 1000000, replace = TRUE)/10, pgrp=rep(c(1:100),10000))

sf <- dt[
,
geometry <- sf::st_linestring(x = matrix(c(lon, lat), ncol = 2))
geometry <- sf::st_sfc(geometry)
geometry <- sf::st_sf(geometry = geometry)

, by = pgrp
]

sf <- sf::st_as_sf(sf)


As you're creating LINESTRINGs this assumes your data is ordered.

Maybe this?

library(data.table)
library(sf)
dt <- data.table(lon=sample(c(380:390), 1000000, replace = TRUE)/10,lat=sample(c(80:90), 1000000, replace = TRUE)/10, pgrp=rep(c(1:100),10000))

tpathline <- data.table(st_as_sf(dt, coords = c("lon","lat"),crs=4326))

lns = st_as_sf(tpathline[, list(geometry = st_cast(st_union(geometry), "LINESTRING")), by = pgrp])


lns[['geometry']][[1]] == lns[['geometry']][[2]]

[1] TRUE

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