Implement to_spatial_segmentation

[agila5]

Showcase of the new spatial morpher:

# packages
library(sf)
library(tidygraph)
library(spatstat)
library(sfnetworks)

# simulated data
my_sfc <- st_sfc(
  st_linestring(rbind(c(-1, 0), c(1, 0), c(1, 1), c(1, 2), c(3, 2))), 
  st_linestring(rbind(c(3, 2), c(3, 3))), 
  st_linestring(rbind(c(3, 3), c(3, 4), c(4, 4))), 
  st_linestring(rbind(c(5, 0), c(5, 2), c(5, 5))), 
  st_linestring(rbind(c(0.5, 0.5), c(1.5, 0.5))) 
)
my_sfn <- as_sfnetwork(my_sfc)
par(mfrow = c(1, 2))
plot(my_sfn, graticule = TRUE, axes = TRUE, xlim = c(-2, 6), lwd = 2, cex = 2)
plot(as.linnet(my_sfn), main = "", vertices = TRUE, axes = TRUE, lwd = 2)
#> Warning: Network is not connected

# Run the new morpher and plot
my_sfn1 <- convert(my_sfn, to_spatial_dump_segments, .clean = TRUE)
plot(my_sfn1, graticule = TRUE, axes = TRUE, xlim = c(-2, 6), lwd = 2, cex = 2)
plot(as.linnet(my_sfn1), main = "", vertices = TRUE, axes = TRUE, lwd = 2)
#> Warning: Network is not connected

# Add two fields, CRS and precision
my_sf <- st_sf(
  data.frame(x = c("A", "B", "C", "D", "E"), y = runif(5)), 
  geometry = my_sfc, 
  agr = c(x = "constant"), 
  crs = 3003, 
  precision = 1
)
my_sfn <- as_sfnetwork(my_sf)
my_sfn1 <- convert(my_sfn, to_spatial_dump_segments, .clean = TRUE)
#> Warning: to_spatial_subdivision assumes attributes are constant over geometries

identical(st_crs(my_sfn, "edges"), st_crs(my_sfn1, "edges"))
#> [1] TRUE
identical(st_agr(my_sfn, "edges"), st_agr(my_sfn1, "edges"))
#> [1] TRUE

^{Created on 2022-06-08 by the reprex package (v2.0.1)}

I know that the approach is not perfect (since we could also infer the new nodes without running as_sfnetwork() again), but I think it's good enough for the moment. If you don't have any particular comments, I will add examples and tests as soon as possible.

cc @mkvasnicka

[luukvdmeer]

One question: since the network is recreated with as_sfnetwork this would also connect edges that share an interior point right, like to_spatial_subdivision does? I am not sure if that is expected or not

I see the name comes from PostGIS, but I think to_spatial_segmentation would be clearer, considering our other morpher names

[agila5]

I see the name comes from PostGIS, but I think to_spatial_segmentation would be clearer, considering our other morpher names

Fixed

One question: since the network is recreated with as_sfnetwork this would also connect edges that share an interior point right, like to_spatial_subdivision does? I am not sure if that is expected or not

Do you mean something like the following example?

# packages
library(sf)
library(tidygraph)
library(sfnetworks)


# data
my_sfc <- st_sfc(
  st_linestring(rbind(c(-1, 0), c(0, 0), c(1, 0))), 
  st_linestring(rbind(c(0, -1), c(0, 0), c(0, 1))) 
)
my_sfn <- as_sfnetwork(my_sfc)
my_sfn1 <- convert(my_sfn, to_spatial_segmentation, .clean = TRUE)

# plot
par(mfrow = c(1, 2), mar = rep(0, 4))
plot(my_sfn)
plot(my_sfn1)

^{Created on 2022-09-08 by the reprex package (v2.0.1)}

We can notice that the morpher creates a new "link" between the existing edges (i.e. the new dot in the middle of the map).

I'm not 100% sure that this is expected but:

1. this is something that will never happen as long as you run the to_spatial_subdivision morpher before this other morpher (and this is particularly relevant for OSM data);
2. I think we can merge this PR, document this behaviour, and then adjust it if someone explicitly complains (and, meanwhile, create a new issue so we don't forget about it).

[codecov-commenter]

Codecov Report

Patch coverage: 25.00% and project coverage change: -0.63 :warning:

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Additional details and impacted files

@@            Coverage Diff             @@
##             main     #210      +/-   ##
==========================================
- Coverage   67.92%   67.29%   -0.63%     
==========================================
  Files          21       21              
  Lines        1593     1581      -12     
==========================================
- Hits         1082     1064      -18     
- Misses        511      517       +6     

Impacted Files	Coverage Δ
R/morphers.R	70.04% <0.00%> (-4.70%)	:arrow_down:
R/spatstat.R	50.00% <ø> (ø)
R/sf.R	66.03% <61.11%> (+2.83%)	:arrow_up:

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