Aggregate od pairs they become non-directional
For example, sum total travel in both directions.
od_oneway( x, attrib = names(x[-c(1:2)])[vapply(x[-c(1:2)], is.numeric, TRUE)], id1 = names(x)[1], id2 = names(x)[2], stplanr.key = NULL )
x |
A data frame or SpatialLinesDataFrame, representing an OD matrix |
attrib |
A vector of column numbers or names, representing variables to be aggregated. By default, all numeric variables are selected. aggregate |
id1 |
Optional (it is assumed to be the first column) text string referring to the name of the variable containing the unique id of the origin |
id2 |
Optional (it is assumed to be the second column) text string referring to the name of the variable containing the unique id of the destination |
stplanr.key |
Optional key of unique OD pairs regardless of the order,
e.g., as generated by |
Flow data often contains movement in two directions: from point A to point B
and then from B to A. This can be problematic for transport planning, because
the magnitude of flow along a route can be masked by flows the other direction.
If only the largest flow in either direction is captured in an analysis, for
example, the true extent of travel will by heavily under-estimated for
OD pairs which have similar amounts of travel in both directions.
Flows in both direction are often represented by overlapping lines with
identical geometries (see flowlines()) which can be confusing
for users and are difficult to plot.
oneway outputs a data frame (or sf data frame) with rows containing
results for the user-selected attribute values that have been aggregated.
Other od:
dist_google(),
od2line(),
od2odf(),
od_aggregate_from(),
od_aggregate_to(),
od_coords2line(),
od_coords(),
od_dist(),
od_id,
od_to_odmatrix(),
odmatrix_to_od(),
points2flow(),
points2odf()
(od_min <- od_data_sample[c(1, 2, 9), 1:6]) (od_oneway <- od_oneway(od_min)) # (od_oneway_old = onewayid(od_min, attrib = 3:6)) # old implementation nrow(od_oneway) < nrow(od_min) # result has fewer rows sum(od_min$all) == sum(od_oneway$all) # but the same total flow od_oneway(od_min, attrib = "all") attrib <- which(vapply(flow, is.numeric, TRUE)) flow_oneway <- od_oneway(flow, attrib = attrib) colSums(flow_oneway[attrib]) == colSums(flow[attrib]) # test if the colSums are equal # Demonstrate the results from oneway and onewaygeo are identical flow_oneway_geo <- onewaygeo(flowlines, attrib = attrib) flow_oneway_sf <- od_oneway(flowlines_sf) par(mfrow = c(1, 2)) plot(flow_oneway_geo, lwd = flow_oneway_geo$All / mean(flow_oneway_geo$All)) plot(flow_oneway_sf$geometry, lwd = flow_oneway_sf$All / mean(flow_oneway_sf$All)) par(mfrow = c(1, 1)) od_max_min <- od_oneway(od_min, stplanr.key = od_id_character(od_min[[1]], od_min[[2]])) cor(od_max_min$all, od_oneway$all) # benchmark performance # bench::mark(check = FALSE, iterations = 3, # onewayid(flowlines_sf, attrib), # od_oneway(flowlines_sf) # )
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