od_jitter {od}

Move desire line end points within zone to avoid all trips going to a single centroid

Description

These functions tackle the problem associated with OD data representing movement to and from large zones. Typically the associated desire lines start and end in one point per zone. This function produces desire lines that can start and end anywhere (or at predefined points) within each zone. See issue #11 for details.

Usage

od_jitter(
  od,
  z,
  subpoints = NULL,
  code_append = "_ag",
  population_column = 3,
  max_per_od = 1e+05,
  keep_ids = TRUE,
  integer_outputs = FALSE,
  zd = NULL,
  subpoints_o = NULL,
  subpoints_d = NULL,
  disag = FALSE
)

Arguments

od

An origin-destination data frame

z

Zones representing origins and destinations

subpoints

Points, lines or polygons within the zones. These define the OD data start/end points.

code_append

The name of the column containing aggregate zone names

population_column

The column containing the total population (if it exists)

max_per_od

Maximum flow in the population_column to assign per OD pair. This only comes into effect if there are enough subpoints to choose from.

keep_ids

Should the origin and destination ids be kept? TRUE by default, meaning 2 extra columns are appended, with the names o_agg and d_agg containing IDs from the original OD data.

integer_outputs

Should integer outputs be returned? FALSE by default. Note: there is a known issue when integer results are generated. See https://github.com/ITSLeeds/od/issues/31 for details.

zd

Zones with ids matching the destination codes in input OD data

subpoints_o

Points within origin zones representing possible destinations

subpoints_d

Points within destination zones representing possible destinations

disag

Should the od_disaggregate function be used as a 'back end' where possible? FALSE by default. See https://github.com/ITSLeeds/od/issues/39.

Value

An sf data frame

Examples

# Basic example
od = od_data_df
z = od_data_zones_min
dlr = od_jitter(od, z) # desire_lines_random
desire_lines = od_to_sf(od, z)
plot(z$geometry)
plot(dlr["all"], add = TRUE, lwd = 3)
dlr$all
desire_lines$all
plot(desire_lines["all"], add = TRUE, lwd = 5)

# Example showing use of subpoints
subpoints_o = sf::st_sample(z, 200)
subpoints_d = sf::st_sample(z, 100)
dlr_d = od_jitter(od, z, subpoints_o = subpoints_o, subpoints_d = subpoints_d)
plot(z$geometry)
plot(dlr_d$geometry, add = TRUE)
plot(subpoints_o, add = TRUE)
plot(subpoints_d, col = "red", add = TRUE)
plot(desire_lines, add = TRUE, lwd = 5)
# mapview::mapview(desire_lines) + dlr + z # interactive map
sp = sf::st_sample(z, 100)
dlr2 = od_jitter(desire_lines, z, subpoints_o = sp, subpoints_d = sp)
plot(z$geometry)
plot(sp, add = TRUE)
plot(dlr2, add = TRUE, lwd = 3)
plot(desire_lines, add = TRUE, lwd = 5)

# Example showing jittering with origin and destination zones
od = od_data_df2
z = sf::st_buffer(od_data_centroids2, dist = 1000)
zd = sf::st_buffer(od_data_destinations, dist = 300)
zd = zd[zd[[1]] %in% od[[2]], ]
desire_lines = od_to_sf(od, od_data_centroids2, zd = od_data_destinations)
dlr = od_jitter(od, z, zd = zd)
plot(z$geometry)
plot(od_data_centroids2$geometry, add = TRUE)
plot(od_data_destinations$geometry, add = TRUE)
plot(zd$geometry, add = TRUE)
plot(dlr, add = TRUE, lwd = 3)
plot(desire_lines, add = TRUE, lwd = 5)

# Larger example with only subset of matching zones
# od = od_data_df_medium
# od_sf = od_to_sf(od, od_data_zones)
# dlr3 = od_jitter(od_sf, od_data_zones)
# plot(od_sf[od$all > 200, 1])
# plot(dlr3[od$all > 200, 1])
# mapview::mapview(od_sf$geometry[od$all > 200])