Group cases into neighborhoods based on walking distance.
neighborhoodWalking(pump.select = NULL, vestry = FALSE, weighted = TRUE,
case.set = "observed", multi.core = TRUE, dev.mode = FALSE)
An R list with 7 objects:
paths
: list of paths to nearest or selected pump(s).
cases
: list of cases by pump.
vestry
: "vestry" from neighborhoodWalking().
observed
: "observed" from neighborhoodWalking().
pump.select
: "pump.select" from neighborhoodWalking().
cores
: number of cores to use for parallel implementation.
metric
: incremental metric used to find cut point on split road segments.
Numeric. Vector of numeric pump IDs to define pump neighborhoods (i.e., the "population"). Negative selection possible. NULL
selects all pumps. Note that you can't just select the pump on Adam and Eve Court (#2) because it's technically an isolate.
Logical. TRUE
uses the 14 pumps from the Vestry report. FALSE
uses the 13 in the original map.
Logical. TRUE
computes shortest path weighted by road length. FALSE
computes shortest path in terms of the number of nodes.
Character. "observed", "expected" or "snow". "snow" captures John Snow's annotation of the Broad Street pump neighborhood printed in the Vestry report version of the map.
Logical or Numeric. TRUE
uses parallel::detectCores()
. FALSE
uses one, single core. You can also specify the number logical cores. See vignette("Parallelization")
for details.
Logical. Development mode uses parallel::parLapply().
if (FALSE) {
neighborhoodWalking()
neighborhoodWalking(pump.select = -6)
}
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