neighborhoodWalking {cholera}

Compute walking path pump neighborhoods.

Description

Group cases into neighborhoods based on walking distance.

Usage

neighborhoodWalking(pump.select = NULL, vestry = FALSE, weighted = TRUE,
  case.set = "observed", multi.core = TRUE, dev.mode = FALSE)

Arguments

pump.select

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.

vestry

Logical. TRUE uses the 14 pumps from the Vestry report. FALSE uses the 13 in the original map.

weighted

Logical. TRUE computes shortest path weighted by road length. FALSE computes shortest path in terms of the number of nodes.

case.set

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.

multi.core

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.

dev.mode

Logical. Development mode uses parallel::parLapply().

Value

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.

Examples

## Not run: 
neighborhoodWalking()
neighborhoodWalking(pump.select = -6)

## End(Not run)