spacetimeLPP is a R package facilitating the analysis of point patterns
on planar networks over time, as usually considered in history or
archaeology, either by qualitative periods (e.g. 1820-1835 or the
Augustan period) or by time steps (e.g. 1820 and 1835). In input,
spatial data are considered in sf format and outputs are in tidy or
sf formats to simplify the use of the package. However, main
calculations, as distance matrices between points on network, are
performed using spatstat package for its computational speed.
It is strongly recommended to users who wish to have a precise understanding of the package to refer to the two publications on which the functions are based:
-
A. Okabe and K. Sugihara, Spatial Analysis along Networks: Statistical and Computational Methods. Oxford: John Wiley & Sons, 2012. doi: 10.1002/9781119967101.
-
A. Baddeley, E. Rubak, et R. Turner, Spatial Point Patterns. Methodology and Applications with R. Boca Raton, Floride: Taylor & Francis Group, 2015. doi: 10.1201/b19708.
Package currently exist as development on github.
Install package from github:
library(remotes)
install_github(repo = "soduco/space_time_lpp")A point pattern on planar network
library(spacetimeLPP)
library(ggplot2)
ggplot() +
geom_sf(data = paris_network, color = "grey30") +
geom_sf(data = pharmacy, color = "red", alpha = 0.5)
Computing shortest paths distances between pharmacies on network and 2 simulated point patterns
distances <- dist_with_sims(pp = pharmacy, network = paris_network, nsim = 2)
distances## # A tibble: 28,359 × 5
## Pi P dist_pi_p sim type
## <int> <chr> <dbl> <int> <chr>
## 1 2 1 1016. 1 simulation
## 2 3 1 2006. 1 simulation
## 3 3 2 2313. 1 simulation
## 4 4 1 2717. 1 simulation
## 5 4 2 2836. 1 simulation
## 6 4 3 1042. 1 simulation
## 7 5 1 1987. 1 simulation
## 8 5 2 2212. 1 simulation
## 9 5 3 837. 1 simulation
## 10 5 4 738. 1 simulation
## # … with 28,349 more rows
Visualisation of distances
ggplot(data = distances, mapping = aes(x = dist_pi_p, color = type)) +
geom_density()