cholera

Description

Amend errors, augment data and aid analysis of John Snow's map of the 1854 London cholera outbreak.

Details

• Fixes two sets of errors in Dodson and Tobler's 1992 digitization of Snow's map: 1) three misplaced cases/fatalities and 2) one missing road segment (part of Clifford Street).

• "Unstacks" the data in two ways to make analysis and visualization easier and more meaningful.

• Computes and visualizes "pump neighborhoods" based on Voronoi tessellation, Euclidean distance, and walking distance.

• Overlay graphical elements and features like kernel density estimates, Voronoi diagrams, Snow's Broad Street neighborhood, and notable landmarks (John Snow's residence, the Lion Brewery, etc.) via 'add*()' functions.

• Includes a variety of functions to highlight specific cases, roads, pumps and paths.

• Appends actual street names to roads data.

• Includes the revised pump data used in the second version of Snow's map from the Vestry report, which includes the "correct" location of the Broad Street pump.

• Adds two different aggregate time series fatalities data sets, taken from the Vestry report.

• Support for parallel computation on Linux and macOS; limited support for Windows.

• Version >= 0.9.0, offers provisional support for (georeferenced) longitude and latitude for practically all data and functions.

To learn more, see the vignettes:

vignette("duplicate.missing.cases")

vignette("kernel.density")

vignette("parallelization")

vignette("pump.neighborhoods")

vignette("roads")

vignette("tiles.polygons")

vignette("time.series")

vignette("unstacking.bars")

Author(s)

Maintainer: Peter Li lindbrook@gmail.com

See Also

Useful links:

• https://github.com/lindbrook/cholera

• Report bugs at https://github.com/lindbrook/cholera/issues

Add observed case(s) to plot.

Description

Add case(s), as "anchor", "fatality" or "orthogonal" as points or IDs, to a plot.

Usage

addCase(case = 1, latlong = FALSE, type = "observed", token = "both",
  text.size = 0.5, pch = 1, cex = 1, point.lwd = 2, col = "black",
  pos = 1)

Arguments

Note

type, token, text.size, pch, cex, point.lwd and pos relevant only when case is numeric.

Examples

## Not run: 
snowMap(add.cases = FALSE)
addCase(1)

snowMap(add.cases = FALSE)
addCase(100)

## End(Not run)

Add Delaunay triangles.

Description

Add Delaunay triangles.

Usage

addDelaunay(pump.select = NULL, vestry = FALSE, color = "black",
  line.type = "solid", line.width = 1, latlong = FALSE)

Arguments

Note

This function uses deldir::deldir().

Examples

snowMap()
addDelaunay()

Add Euclidean path from case/landmark to nearest or selected pump. (prototype)

Description

Add Euclidean path from case/landmark to nearest or selected pump. (prototype)

Usage

addEuclideanPath(origin = 1, destination = NULL, type = "case-pump",
  vestry = FALSE, latlong = FALSE, case.set = "observed",
  location = "nominal", weighted = TRUE, distance.unit = "meter",
  time.unit = "second", walking.speed = 5, include.landmarks = TRUE,
  long.title = FALSE, mileposts = TRUE, milepost.unit = "distance",
  milepost.interval = NULL, alpha.level = 1)

Arguments

Highlight index case at 40 Broad Street.

Description

Highlight index case at 40 Broad Street.

Usage

addIndexCase(latlong = FALSE, cex = 2, col = "red", pch = 1,
  add.label = FALSE, text.size = 0.5)

Arguments

Value

Add base R point and (optionally) text to a graphics plot.

Examples

segmentLocator("216-1")
addIndexCase()

Add 2D kernel density contours.

Description

Add 2D kernel density contours based on selected sets of observations.

Usage

addKernelDensity(pump.subset = "pooled", pump.select = NULL,
  neighborhood.type = "walking", data = "unstacked", bandwidth = 0.5,
  color = "black", line.type = "solid", multi.core = FALSE,
  latlong = FALSE)

Arguments

Value

Add contours to a graphics plot.

Note

This function uses KernSmooth::bkde2D().

Examples

## Not run: 
snowMap()
addKernelDensity()

snowMap()
addKernelDensity("individual")

snowMap()
addKernelDensity(c(6, 8))

snowMap()
addKernelDensity(pump.select = c(6, 8))

## End(Not run)

Add Golden and Soho Squares to plot.

Description

Add Golden and Soho Squares to plot.

Usage

addLandmarkSquares(latlong = FALSE, text.size = 0.5, text.col = "black")

Arguments

Value

Base R points and text.

Examples

snowMap()
addLandmarkSquares()

Add landmarks to plot.

Description

Add landmarks to plot.

Usage

addLandmarks(text.size = 0.5, text.col = "black",
  highlight.perimeter = TRUE, latlong = FALSE)

Arguments

Value

Base R points and text.

Note

The location of 18 Sackville Street and 28 Dean Street are approximate. Falconberg Court & Mews form an isolate: they are not part of the network of roads and are technically unreachable. Adam and Eve Court and its pump also form an isolate.

Examples

snowMap(add.landmarks = FALSE)
addLandmarks()

Add observed neighborhood cases.

Description

Add cases to a plot as "nominal" or "fatalities" and as points or IDs.

Usage

addNeighborhoodCases(pump.subset = NULL, pump.select = NULL,
  metric = "walking", case.set = "observed", location = "nominal",
  token = "point", text.size = 0.5, pch = 16, point.size = 0.5,
  vestry = FALSE, weighted = TRUE, color = NULL, alpha.level = 0.5,
  latlong = FALSE, multi.core = FALSE)

Arguments

Examples

## Not run: 
snowMap(add.cases = FALSE)
addNeighborhoodCases()

snowMap(add.cases = FALSE)
addNeighborhoodCases(pump.subset = c(6, 10))

snowMap(add.cases = FALSE)
addNeighborhoodCases(pump.select = c(6, 10))

snowMap(add.cases = FALSE, latlong = TRUE)
addNeighborhoodCases(latlong = TRUE)

snowMap(add.cases = FALSE, latlong = TRUE)
addNeighborhoodCases(pump.subset = c(6, 10), latlong = TRUE)

snowMap(add.cases = FALSE, latlong = TRUE)
addNeighborhoodCases(pump.select = c(6, 10), latlong = TRUE)

## End(Not run)

Add expected Euclidean pump neighborhoods.

Description

Plots star graph from pump to its cases.

Usage

addNeighborhoodEuclidean(pump.select = NULL, vestry = FALSE,
  case.set = "observed", case.select = "address", latlong = FALSE,
  location = "nominal", brute.force = FALSE, type = "star",
  add.observed.points = TRUE, alpha.level = 0.25, polygon.type = "solid",
  multi.core = FALSE, dev.mode = FALSE)

Arguments

Value

R graphic elements.

Examples

## Not run: 
streetNameLocator("marshall street", zoom = 0.5, highlight = FALSE,
  add.subtitle = FALSE)
addNeighborhoodEuclidean()

streetNameLocator("marshall street", zoom = -50, highlight = FALSE)
addNeighborhoodEuclidean(case.set = "expected", type = "area.polygons")

## End(Not run)

Adds Snow's graphical annotation of the Broad Street pump walking neighborhood.

Description

Adds Snow's graphical annotation of the Broad Street pump walking neighborhood.

Usage

addNeighborhoodSnow(latlong = FALSE, type = "area.polygons",
  non.snow.cases = FALSE, alpha.level = 1/3, polygon.type = "solid",
  polygon.col = NULL, polygon.lwd = NULL)

Arguments

Examples

## Not run: 
plot(neighborhoodVoronoi())
addNeighborhoodSnow()

## End(Not run)

Add walking neighborhoods.

Description

Add walking neighborhoods.

Usage

addNeighborhoodWalking(pump.select = NULL, vestry = FALSE,
  weighted = TRUE, case.set = "expected", latlong = FALSE,
  type = "area.polygons", tsp.method = "repetitive_nn", path.width = 2,
  alpha.level = 0.5, polygon.type = "solid", polygon.col = NULL,
  polygon.lwd = 2, multi.core = FALSE)

Arguments

Examples

## Not run: 
streetNameLocator("marshall street", zoom = 0.5)
addNeighborhoodWalking()

## End(Not run)

Add plague pit (Marshall Street).

Description

Draws a polygon that approximates the plague pit located around Marshall Street. From Vestry Report map.

Usage

addPlaguePit(latlong = FALSE, color = "black", line.type = "solid")

Arguments

Value

Adds a polygon to a graphics plot.

Note

In progress.

Examples

snowMap(add.landmarks = FALSE)
addPlaguePit()

Add selected pump(s) to plot.

Description

Add selected pump(s) to plot.

Usage

addPump(pump.select = NULL, vestry = FALSE, col = NULL, pch = 24,
  label = TRUE, pos = 1, cex = 1, latlong = FALSE)

Arguments

Add all streets and roads to plot.

Description

Add all streets and roads to plot.

Usage

addRoads(latlong = FALSE, col = "gray")

Arguments

Add Voronoi cells.

Description

Add Voronoi cells.

Usage

addVoronoi(pump.select = NULL, vestry = FALSE, case.location = "nominal",
  color = "black", line.type = "solid", line.width = 1,
  latlong = FALSE)

Arguments

Note

This function uses deldir::deldir().

Examples

snowMap()
# addVoronoi()

Add walking path from case/landmark to nearest or selected pump. (prototype)

Description

Add walking path from case/landmark to nearest or selected pump. (prototype)

Usage

addWalkingPath(origin = 1, destination = NULL, type = "case-pump",
  vestry = FALSE, latlong = FALSE, case.set = "observed",
  location = "nominal", weighted = TRUE, distance.unit = "meter",
  time.unit = "second", walking.speed = 5, include.landmarks = TRUE,
  long.title = FALSE, mileposts = TRUE, milepost.unit = "distance",
  milepost.interval = NULL, alpha.level = 1, ...)

Arguments

Add Rev. Henry Whitehead's Broad Street pump neighborhood.

Description

A circle (polygon), centered around a desired pump with a radius of 210 yards. The Broad Street pump is the default.

Usage

addWhitehead(pump = "Broad Street", radius = 210, distance.unit = "yard",
  latlong = FALSE, color = "black", line.type = "solid",
  vestry = FALSE, add.title = FALSE, add.subtitle = FALSE,
  walking.speed = 5)

Arguments

Value

Adds a circle (polygon) to a graphics plot.

Examples

snowMap()
addWhitehead()

Anchor or base case of each stack of fatalities.

Description

Data frame that links a fatality to its stack, a stack's base case. For use with caseLocator.

Usage

anchor.case

Format

case

numerical case ID

anchor

numerical case ID of anchor.case

Note

unstackFatalities documents the code for these data.

Numeric IDs of line segments that create the map's border frame.

Description

Vector of ordered numbers that identify the line segments that make up the frame of the map. For use with sp::Polygon().

Usage

border

Format

border

numerical ID

Locate case by numerical ID.

Description

Highlight selected observed or simulated case and its home road segment.

Usage

caseLocator(case = 1, zoom = FALSE, observed = TRUE, latlong = FALSE,
  add.title = TRUE, highlight.segment = TRUE, data = FALSE,
  add = FALSE, col = "red", vestry = FALSE)

Arguments

Value

A base R graphics plot.

Examples

caseLocator(290)
caseLocator(290, zoom = TRUE)
caseLocator(290, observed = FALSE)
caseLocator(290, latlong = TRUE, zoom = TRUE)

Compute Euclidean path coordinates from observed case/landmark to nearest/selected pump.

Description

Compute Euclidean path coordinates from observed case/landmark to nearest/selected pump.

Usage

euclideanPath(origin = 1, destination = NULL, type = "case-pump",
  vestry = FALSE, latlong = FALSE, case.set = "observed",
  location = "nominal", weighted = TRUE, distance.unit = "meter",
  time.unit = "second", walking.speed = 5, include.landmarks = TRUE)

Arguments

Amended Dodson and Tobler's cholera data.

Description

An amended version of Dodson and Tobler's digitization of John Snow's map of the 1854 London cholera outbreak. It removes 3 duplicate observations and imputes the location for 3 "missing" observation. This information is also available in HistData::Snow.deaths2 (>= ver. 0.7-8).

Usage

fatalities

Format

A data frame with 3 variable that records the position and the nearest pump for the 578 bars on Snow's map.

case

numeric case ID

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Note

fixFatalities() documents the code for these data. For details, see vignette("duplicate.missing.cases").

See Also

caseLocator

streetNameLocator

streetNumberLocator

caseLocator

streetNameLocator

streetNumberLocator

"Unstacked" amended cholera data with address as unit of observation.

Description

An "unstacked" version of the fatalities dataset. It changes the unit of observation from the case (bar) to the "address", the x-y coordinates of the case at the base of a stack, and makes the number of fatalities an attribute of the "address".

Usage

fatalities.address

Format

A data frame with 4 variables for 321 addresses

anchor

numerical case ID of address

x

x-coordinate

y

y-coordinate

case.count

number of fatalities at address

lon

longitude

lat

latitude

Note

unstackFatalities documents the code for these data. For details, see vignette("unstacking.fatalities").

See Also

caseLocator

streetNameLocator

streetNumberLocator

"Unstacked" amended cholera fatalities data with fatality as unit of observation.

Description

An "unstacked" version of the fatalities dataset. It changes the unit of observation from the case (bar) to the "address", the x-y coordinates of the case at the base of a stack, and assigns the base case's coordinates to all cases in the stack.

Usage

fatalities.unstacked

Format

A data frame with 3 variable that records the position of the 578 bars on Snow's map.

case

numerical case ID

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Note

unstackFatalities documents the code for these data. For details, see vignette("unstacking.fatalities").

See Also

caseLocator

streetNameLocator

streetNumberLocator

Map frame data c("x", "y") and c("lon", "lat").

Description

Map frame data c("x", "y") and c("lon", "lat").

Usage

frame.data

Format

A data frame with 106 observations (points) and 8 variables.

street

street number

n

street street component number

x

native x-coordinate

y

native y-coordinate

id

segment numeric ID

name

street name

lon

longitude

lat

latitude

Partitioned map frame points (segment endpoints).

Description

Partitioned map frame points (segment endpoints).

Usage

frame.sample

Format

A list of 3 vectors length 19, 19 and 18 from cholera::roads$id.

frame.sample

cholera::roads$id

Dodson and Tobler's "Map Frame" street data transformed into road segments.

Description

This data set transforms Dodson and Tobler's street data to give each straight line segment of a "road" a unique ID.

Usage

frame.segments

Format

A data frame with 658 observations and 7 variables. The data describe the straight line segments used to recreate the roads on Snow's map.

street

numeric street ID

id

character segment ID

name

road name

x1

x-coordinate of first endpoint

y1

y-coordinate of first endpoint

x2

x-coordinate of second endpoint

y2

y-coordinate of second endpoint

lon1

longitude of first endpoint

lat1

latitude of first endpoint

lon2

longitude of second endpoint

lat2

latitude of second endpoint

Note

'frameSegments()' documents the code for these data.

Isochrone and isodistance vertices (prototype)

Description

Isochrone and isodistance vertices (prototype)

Usage

isoVertices(post = 50, post.type = "distance", multi.core = FALSE,
  dev.mode = FALSE)

Arguments

Centers of city squares.

Description

Centers of city squares.

Usage

landmark.squares

Format

A data frame with 2 observations and 6 variables that records the position of landmark square labels.

case

numeric case ID

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

name

square name

Landmark coordinates.

Description

Landmark coordinates.

Usage

landmarks

Format

A data frame of landmark coordinates with 20 observations and 11 variables.

case

numeric case ID

road.segment

"address" road segment

x

nominal x-coordinate

y

nominal y-coordinate

x.lab

label x-coordinate

y.lab

label y-coordinate

lon

longitude

lat

latitude

lon.lab

label longitude

lat.lab

label latitude

name

landmark name

Orthogonal projection of observed address (latlong) cases onto road network.

Description

Orthogonal projection of observed address (latlong) cases onto road network.

Usage

latlong.ortho.addr

Format

A data frame with 7 variables that records the position of the orthogonal projection of the 321 cases onto the network of roads.

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

ortho.dist

orthogonal distance to home road segment

case

numeric case ID

lon

longitude

lat

latitude

Note

unstackFatalities documents the code for these data.

Orthogonal projection of 13 original pumps (latlong).

Description

Orthogonal projection of 13 original pumps (latlong).

Usage

latlong.ortho.pump

Format

A data frame with 7 variables that records the position of the orthogonal projection of the 13 original pumps onto the network of roads.

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

ortho.dist

orthogonal distance to home road segment

id

numeric ID

lon

longitude

lat

latitude

Note

pumpData documents the code for these data.

Orthogonal projection of the 14 pumps from the Vestry Report (latlong).

Description

Orthogonal projection of the 14 pumps from the Vestry Report (latlong).

Usage

latlong.ortho.pump.vestry

Format

A data frame with 7 variables that records the position of the orthogonal projection of the 14 pumps onto the network of roads.

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

ortho.dist

orthogonal distance to home road segment

id

numeric ID

lon

longitude

lat

latitude

Note

pumpData documents the code for these data.

"Expected" cases (latlong).

Description

The result of using sp::spsample() and sp::Polygon() to generate 19,993 regularly spaced simulated Cartesian/geodesic cases within the map's borders.

Usage

latlong.regular.cases

Format

A data frame with 4 variables that records the position of 19,993 "expected" cases fitted by sp::spsample().

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Road "address" of simulated (i.e., "expected") cases (latlong).

Description

Road "address" of simulated (i.e., "expected") cases (latlong).

Usage

latlong.sim.ortho.proj

Format

A data frame with 8 variables that records the "address" of 19,993 regularly spaced simulated Cartesian/geodesic cases regularly spaced across map.

case

numeric case ID

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

dist

Euclidean or orthogonal distance to home road segment

type

type of projection: Euclidean ("eucl") or orthogonal ("ortho")

lon

longitude

lat

latitude

Compute xlim and ylim of Snow's map.

Description

Compute xlim and ylim of Snow's map.

Usage

mapRange(latlong = FALSE)

Arguments

Meter to yard conversion factor.

Description

Meter to yard conversion factor.

Usage

meter.to.yard

Format

A vector of length one.

meter.to.yard

conversion factor = 1.093613

Compute Euclidean path pump neighborhoods.

Description

Plots star graph from pump to its cases.

Usage

neighborhoodEuclidean(pump.select = NULL, vestry = FALSE,
  case.set = "observed", case.select = "address", latlong = FALSE,
  location = "nominal", brute.force = FALSE, multi.core = FALSE,
  dev.mode = FALSE)

Arguments

Value

An R list.

Compute Snow's graphical annotation of Broad Street pump neighborhood.

Description

Computational approximation.

Usage

neighborhoodSnow(latlong = FALSE)

Arguments

Compute Voronoi pump neighborhoods.

Description

Group cases into neighborhoods using Voronoi tessellation.

Usage

neighborhoodVoronoi(pump.select = NULL, vestry = FALSE, latlong = FALSE,
  location = "nominal", polygon.vertices = FALSE)

Arguments

Value

An R list with 12 objects.

• pump.id: vector of selected pumps

• voronoi: output from deldir::deldir().

• snow.colors: neighborhood color based on snowColors().

• x.rng: range of x for plot.

• y.rng: range of y for plot.

• select.string: description of "pump.select" for plot title.

• expected.data: expected neighborhood fatality counts, based on Voronoi cell area.

• coordinates: polygon vertices of Voronoi cells.

• statistic.data: observed neighborhood fatality counts.

• pump.select: "pump.select" from neighborhoodVoronoi().

• statistic: "statistic" from neighborhoodVoronoi().

• vestry: "vestry" from neighborhoodVoronoi().

Examples

## Not run: 
neighborhoodVoronoi()
neighborhoodVoronoi(vestry = TRUE)
neighborhoodVoronoi(pump.select = 6:7)
neighborhoodVoronoi(pump.select = -6)
neighborhoodVoronoi(pump.select = -6, polygon.vertices = TRUE)

# coordinates for vertices also available in the returned object.
dat <- neighborhoodVoronoi(pump.select = -6)
dat$coordinates

## End(Not run)

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", latlong = FALSE, multi.core = FALSE)

Arguments

Orthogonal projection of observed cases onto road network.

Description

Orthogonal projection of observed cases onto road network.

Usage

ortho.proj

Format

A data frame with 5 variables that records the position of the orthogonal projection of the 578 cases onto the network of roads.

case

numeric case ID

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

dist

distance to home road segment

type

type of distance: orthogonal to road or Euclidean to endpoint

Note

unstackFatalities documents the code for these data.

Orthogonal projection of 13 original pumps.

Description

Orthogonal projection of 13 original pumps.

Usage

ortho.proj.pump

Format

A data frame with 6 variables that records the position of the orthogonal projection of the 13 original pumps onto the network of roads.

pump.id

numeric ID

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

ortho.dist

orthogonal distance to home road segment

node

node ID

Note

pumpData documents the code for these data.

Orthogonal projection of the 14 pumps from the Vestry Report.

Description

Orthogonal projection of the 14 pumps from the Vestry Report.

Usage

ortho.proj.pump.vestry

Format

A data frame with 6 variables that records the position of the orthogonal projection of the 14 pumps onto the network of roads.

pump.id

numeric ID

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

ortho.dist

orthogonal distance to home road segment

node

node ID

Note

pumpData documents the code for these data.

Compute Pearson Residuals (prototype)

Description

Compute Pearson Residuals (prototype)

Usage

pearsonResiduals(x)

Arguments

Value

An R vector.

Examples

## Not run: 
pearsonResiduals(neighborhoodEuclidean())
pearsonResiduals(neighborhoodVoronoi())
pearsonResiduals(neighborhoodWalking())

## End(Not run)

Plague pit coordinates.

Description

Coordinates for polygon() or sp::Polygon(). In progress.

Usage

plague.pit

Format

A data frame with 13 observations and 2 variables.

id

integers 1 through 13

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Plot method for neighborhoodEuclidean().

Description

Plot method for neighborhoodEuclidean().

Usage

## S3 method for class 'euclidean'
plot(x, type = "star", add = FALSE,
  add.observed.points = TRUE, alpha.level = 0.75, polygon.type = "solid",
  ...)

Arguments

Value

A base R plot.

Note

This uses an approximate computation of polygons, using the 'TSP' package, that may produce non-simple and/or overlapping polygons.

Examples

## Not run: 
plot(neighborhoodEuclidean())
plot(neighborhoodEuclidean(-6))
plot(neighborhoodEuclidean(pump.select = 6:7))
plot(neighborhoodEuclidean(case.set = "expected"), type = "area.points")
plot(neighborhoodEuclidean(case.set = "expected"), type = "area.polygons")

## End(Not run)

Plot method for euclideanLatlong()

Description

Plot method for euclideanLatlong()

Usage

## S3 method for class 'euclideanLatlong'
plot(x, type = "star", add = FALSE,
  add.observed.points = TRUE, alpha.level = 0.75, polygon.type = "solid",
  ...)

Arguments

Plot the path of the Euclidean distance between cases and/or pumps.

Description

Plot the path of the Euclidean distance between cases and/or pumps.

Usage

## S3 method for class 'euclidean_path'
plot(x, zoom = TRUE, add = FALSE,
  long.title = TRUE, mileposts = TRUE, milepost.unit = "distance",
  milepost.interval = NULL, alpha.level = 1, ...)

Arguments

Value

A base R plot.

Plot method for isoVertices().

Description

Plot method for isoVertices().

Usage

## S3 method for class 'iso_vertices'
plot(x, selected.post = "all", palette = "plasma",
  alpha.level = 1/2, add = FALSE, ...)

Arguments

Value

A vector with observed counts.

Plot method for profilePerspective().

Description

Plot method for profilePerspective().

Usage

## S3 method for class 'profile_perspective'
plot(x, ...)

Arguments

Plot method for neighborhoodSnow().

Description

Plot method for neighborhoodSnow().

Usage

## S3 method for class 'snow'
plot(x, type = "area.polygons", non.snow.cases = TRUE,
  alpha.level = 1/3, polygon.type = "solid", polygon.col = NULL,
  polygon.lwd = NULL, add = FALSE, ...)

Arguments

Plot method for sohoGraph().

Description

Visualize underlying road network (with or without cases and pumps).

Usage

## S3 method for class 'soho_graph'
plot(x, ...)

Arguments

Value

A base R plot.

Plot aggregate time series data from Vestry report.

Description

Plot aggregate fatality data and indicates the date of the removal of the handle of the Broad Street pump.

Usage

## S3 method for class 'time_series'
plot(x, statistic = "fatal.attacks",
  pump.handle = TRUE, main = "Removal of the Broad Street Pump Handle",
  type = "o", xlab = "Date", ylab = "Fatalities", ...)

Arguments

See Also

timeSeries

Examples

plot(timeSeries())
plot(timeSeries(), statistic = "deaths")
plot(timeSeries(), bty = "n", type = "h", lwd = 4)

Plot method for voronoiLatlong()

Description

Plot method for voronoiLatlong()

Usage

## S3 method for class 'voronoi_latlong'
plot(x, add.pumps = TRUE,
  delaunay.voronoi = "voronoi", euclidean.paths = FALSE, ...)

Arguments

Plot Voronoi neighborhoods.

Description

Plot Voronoi neighborhoods.

Usage

## S3 method for class 'voronoi_nominal'
plot(x, delaunay.voronoi = "voronoi",
  euclidean.paths = FALSE, ...)

Arguments

Value

A base R graph.

See Also

voronoiNominal()

addVoronoi()

Plot method for neighborhoodWalking().

Description

Plot method for neighborhoodWalking().

Usage

## S3 method for class 'walking'
plot(x, type = "area.points", add = FALSE,
  tsp.method = "repetitive_nn", path.width = 2, alpha.level = 0.75,
  polygon.type = "solid", polygon.col = NULL, polygon.lwd = 2, ...)

Arguments

Value

A base R plot.

Note

When plotting area graphs with simulated data (i.e., case.set = "expected"), there may be discrepancies between observed cases and expected neighborhoods, particularly between neighborhoods. type = "roads" inspired by Shiode et. al. (2015).

Plot the walking path between selected cases and/or pumps.

Description

Plot the walking path between selected cases and/or pumps.

Usage

## S3 method for class 'walking_path'
plot(x, zoom = TRUE, add = FALSE,
  long.title = TRUE, mileposts = TRUE, milepost.unit = "distance",
  milepost.interval = NULL, alpha.level = 1, ...)

Arguments

Value

A base R plot.

Print method for neighborhoodEuclidean().

Description

Parameter values for neighborhoodEuclidean().

Usage

## S3 method for class 'euclidean'
print(x, ...)

Arguments

Value

A list of argument values.

Examples

## Not run: 
neighborhoodEuclidean()
print(neighborhoodEuclidean())

## End(Not run)

Print method for neighborhoodEuclidean(latlong = TRUE).

Description

Print method for neighborhoodEuclidean(latlong = TRUE).

Usage

## S3 method for class 'euclideanLatlong'
print(x, ...)

Arguments

Value

A list of argument values.

Examples

## Not run: 
neighborhoodEuclidean(latlong = TRUE)
print(neighborhoodEuclidean(latlong = TRUE))

## End(Not run)

Print method for euclideanPath().

Description

Summary output.

Usage

## S3 method for class 'euclidean_path'
print(x, ...)

Arguments

Value

An R data frame.

Print method for isoVertices().

Description

Print method for isoVertices().

Usage

## S3 method for class 'iso_vertices'
print(x, ...)

Arguments

Value

A vector with observed counts.

Print summary data for timeSeries().

Description

Return summary results.

Usage

## S3 method for class 'time_series'
print(x, ...)

Arguments

Value

An R data frame.

Examples

timeSeries()
print(timeSeries())

Print method for voronoiLatlong().

Description

Parameter values for voronoiLatlong().

Usage

## S3 method for class 'voronoi_latlong'
print(x, ...)

Arguments

Value

A list of argument values.

Print method for voronoiNominal().

Description

Parameter values for voronoiNominal().

Usage

## S3 method for class 'voronoi_nominal'
print(x, ...)

Arguments

Value

A list of argument values.

Print method for neighborhoodWalking().

Description

Parameter values for neighborhoodWalking().

Usage

## S3 method for class 'walking'
print(x, ...)

Arguments

Value

A list of argument values.

Examples

## Not run: 
neighborhoodWalking()
print(neighborhoodWalking())

## End(Not run)

Print method for walkingPath().

Description

Summary output.

Usage

## S3 method for class 'walking_path'
print(x, ...)

Arguments

Value

An R data frame.

2D Profile .

Description

2D Profile .

Usage

profile2D(angle = 0, pump = 7, vestry = FALSE, graphics = "base",
  multi.core = FALSE)

Arguments

Examples

## Not run: 
profile2D(angle = 30)
profile2D(angle = 30, graphics = "ggplot2")

## End(Not run)

3D Profile.

Description

3D Profile.

Usage

profile3D(pump.select = NULL, pump.subset = NULL, vestry = FALSE,
  drop.neg.subset = FALSE, multi.core = FALSE)

Arguments

Examples

## Not run: 
profile3D(pump.select = 6:7)
profile3D(pump.subset = -7)
profile3D(pump.subset = -7, drop.neg.subset = TRUE)

## End(Not run)

Extract numeric case IDs by pump neighborhood.

Description

Extract numeric case IDs by pump neighborhood.

Usage

pumpCase(x, case)

Arguments

Value

An R list of numeric ID of cases by pump neighborhoods.

Examples

## Not run: 
pumpCase(neighborhoodEuclidean())
pumpCase(neighborhoodVoronoi())
pumpCase(neighborhoodWalking())

## End(Not run)

Compute pump coordinates.

Description

Returns either the set of x-y coordinates for the pumps themselves or for their orthogonally projected "addresses" on the network of roads.

Usage

pumpData(vestry = FALSE, orthogonal = FALSE, multi.core = FALSE)

Arguments

Value

An R data frame.

Note

Note: The location of the fourteenth pump, at Hanover Square, and the "correct" location of the Broad Street pump are approximate. This function documents the code that generates pumps, pumps.vestry, ortho.proj.pump and ortho.proj.pump.vestry.

See Also

pumpLocator

Compute fatalities by pump.

Description

Compute fatalities by pump.

Usage

pumpFatalities(pump.select = NULL, metric = "walking", vestry = FALSE,
  latlong = FALSE, multi.core = FALSE)

Arguments

Examples

## Not run: 
pumpFatalities(pump.select = -7)
pumpFatalities(latlong = TRUE)
pumpFatalities(metric = "euclidean", vestry = TRUE)

## End(Not run)

Locate water pump by numerical ID.

Description

Highlight selected water pump.

Usage

pumpLocator(id = 7, zoom = FALSE, vestry = FALSE, add.title = TRUE,
  highlight.segment = TRUE, latlong = FALSE)

Arguments

Value

A base R graphics plot.

See Also

pumpData

Examples

pumpLocator()
pumpLocator(zoom = TRUE)
pumpLocator(14, vestry = TRUE, zoom = TRUE)

Dodson and Tobler's pump data with street name.

Description

Adds and amends road locations for water pumps from John Snow's map to Dodson and Tobler's street data. The latter are available at Michael Friendly's HistData::Snow.streets.

Usage

pumps

Format

A data frame with 13 observations and 4 variables that describe the pumps on Snow's map.

id

pump number between 1 and 13

street

nearest street

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Note

pumpData documents the code for these data.

See Also

pumpLocator

Vestry report pump data.

Description

These data include the fourteenth pump, at Hanover Square, and the "corrected" location of the Broad Street pump that Snow includes in the second version of his map in the Vestry report.

Usage

pumps.vestry

Format

A data frame with 14 observations and 4 variables.

id

pump number between 1 and 14

street

nearest street

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Note

pumpData documents the code for these data.

See Also

pumpLocator

Sample of road intersections (segment endpoints).

Description

Sample of road intersections (segment endpoints).

Usage

rd.sample

Format

A list with 2 variables that list randomly re-arranges unique road intersections (segment endpoints).

one

endpoints with 1 intersection

three

endpoints with 3 intersections

Rectangular filter data.

Description

Coordinates to filter out frame shadow using sp::point.in.polygon().

Usage

rectangle.filter

Format

A data frame with 2 variables and 4 observations.

x

longitude

y

latitude

"Expected" cases.

Description

The result of using sp::spsample() and sp::Polygon() to generate 19,993 regularly spaced simulated cases within the map's borders.

Usage

regular.cases

Format

A data frame with 2 variable that records the position of 19,993 "expected" cases fitted by sp::spsample().

x

x-coordinate

y

y-coordinate

Note

simulateFatalities documents the code for these data.

Dodson and Tobler's street data transformed into road segments.

Description

This data set transforms Dodson and Tobler's street data to give each straight line segment of a "road" a unique ID.

Usage

road.segments

Format

A data frame with 658 observations and 11 variables. The data describe the straight line segments used to recreate the roads on Snow's map.

street

numeric street ID

id

character segment ID

name

road name

x1

x-coordinate of first endpoint

y1

y-coordinate of first endpoint

x2

x-coordinate of second endpoint

y2

y-coordinate of second endpoint

lon1

longitude of first endpoint

lat1

latitude of first endpoint

lon2

longitude of second endpoint

lat2

latitude of second endpoint

Note

roadSegments documents the code for these data.

See Also

roads

vignette("road.names")

streetNameLocator

streetNumberLocator

segmentLocator

Reshape 'roads' data frame into 'road.segments' data frame.

Description

Used to integrate pumps and cases into road network when computing walking neighborhoods.

Usage

roadSegments(latlong = FALSE)

Arguments

Value

An R data frame.

Note

This function documents the code that generates road.segments.

Dodson and Tobler's street data with appended road names.

Description

This data set adds road names from John Snow's map to Dodson and Tobler's street data. The latter are also available from HistData::Snow.streets.

Usage

roads

Format

A data frame with 1243 observations and 6 variables. The data describe the roads on Snow's map.

street

street segment number, which range between 1 and 528

n

number of points in this street line segment

x

x-coordinate

y

y-coordinate

id

unique numeric ID

name

road name

lon

longitude

lat

latitude

See Also

road.segments

vignette("road.names")

streetNameLocator

streetNumberLocator

segmentLocator

Highlight segment by ID.

Description

Highlight segment by ID.

Usage

segmentHighlight(id, highlight = TRUE, col = "red", rotate.label = FALSE,
  latlong = FALSE)

Arguments

Value

A base R graphics segment(s).

Examples

streetNameLocator("Soho Square", zoom = TRUE, highlight = FALSE)
ids <- road.segments[road.segments$name == "Soho Square", "id"]
invisible(lapply(ids, function(x) segmentHighlight(x, highlight = FALSE)))

Plot/Locate road segment by ID.

Description

Highlight selected road segment(s) and cases.

Usage

segmentLocator(segment.id = "216-1", zoom = TRUE, latlong = FALSE,
  cases = "address", token = "id", vestry = FALSE, add.pump = TRUE,
  add.title = TRUE, add.subtitle = TRUE, highlight = TRUE,
  distance.unit = "meter", time.unit = "second", walking.speed = 5,
  cex.text = 0.67)

Arguments

Value

A base R graphics plot.

Note

With Dodson and Tobler's data, a street (e.g., Broad Street) is often comprised of multiple straight line segments. To identify each segment individually, an additional number is appended to form a text string ID (e.g., "116-2"). See cholera::road.segments.

Examples

## Not run: 
segmentLocator("216-1")
segmentLocator("216-1", zoom = -10)
segmentLocator("216-1", latlong = TRUE, zoom = -10)
segmentLocator("216-1", distance.unit = "yard")
segmentLocator("216-1", zoom = FALSE)

## End(Not run)

Road "address" of simulated (i.e., "expected") cases.

Description

Road "address" of simulated (i.e., "expected") cases.

Usage

sim.ortho.proj

Format

A data frame with 6 variables that records the "address" of 19,993 simulate cases along the network of roads.

case

numeric case ID

road.segment

"address" road segment

x.proj

x-coordinate

y.proj

y-coordinate

dist

Euclidean or orthogonal distance to home road segment

type

type of projection: Euclidean ("eucl") or orthogonal ("ortho")

Note

simulateFatalities documents the code for these data.

List of "simulated" fatalities grouped by walking-distance pump neighborhood.

Description

List of "simulated" fatalities grouped by walking-distance pump neighborhood.

Usage

sim.pump.case

Format

A list 4972 IDs spread over 13 vectors.

sim.pump.case

numerical ID

Note

neighborhoodWalking documents the code for these data. For details, see vignette("pump.neighborhoods").

Examples

## Not run: 
pumpCase(neighborhoodWalking(case.set = "expected"))

## End(Not run)

Walking distance to Broad Street Pump (#7).

Description

Walking distance to Broad Street Pump (#7).

Usage

sim.walking.distance

Format

A data frames with 5 variables.

case

case ID

pump

pump ID

pump.name

pump name

distance

walking distance in meters

time

walking time in seconds based on 5 km/hr walking speed

Project simulated fatalities onto road network

Description

Places regularly spaced "simulated" or "expected" cases across the face of the map and then finds the "addresses" of those cases via orthogonal projection or simple proximity to road graph network. These data are used to generate "expected" pump neighborhoods.

Usage

simulateFatalities(recompute.regular.cases = FALSE, simulated.obs = 20000L,
  multi.core = FALSE)

Arguments

Value

An R data frame: sim.ortho.proj.

Note

This function is computationally intensive. With "simulated.obs" set to 20,000 (generating 19,993 cases). This function documents the code that generates sim.ortho.proj and regular.cases. In real world terms, the distance between simulated cases is approximately 6 meters.

Snow neighborhood fatalities.

Description

Numeric IDs of fatalities from Dodson and Tobler that fall within Snow's Broad Street pump neighborhood.

Usage

snow.neighborhood

Format

A vector with 384 observations.

snow.neighborhood

numeric case ID

Create a set of colors for pump neighborhoods.

Description

Uses RColorBrewer::brewer.pal().

Usage

snowColors(vestry = FALSE)

Arguments

Value

A character vector of colors.

Note

Built with 'RColorBrewer' package.

Plot John Snow's cholera map.

Description

Plot John Snow's cholera map.

Usage

snowMap(vestry = FALSE, stacked = TRUE, add.axes_box = TRUE,
  add.cases = TRUE, add.landmarks = FALSE, add.pumps = TRUE,
  add.roads = TRUE, add.frame = TRUE, main = NA, case.col = "gray",
  case.pch = 15, latlong = FALSE, ...)

Arguments

Value

A base R graphics plot.

Note

Uses amended version of Dodson and Tobler's data included in this package.

Examples

snowMap()
snowMap(vestry = TRUE, stacked = FALSE)

Compute network graph of roads and embed cases, landmarks and pumps (prototype).

Description

Compute network graph of roads and embed cases, landmarks and pumps (prototype).

Usage

sohoGraph(vestry = FALSE, case.set = "observed", embed.addr = TRUE,
  embed.landmarks = TRUE, embed.pumps = TRUE, latlong = FALSE,
  drop.isolates = FALSE)

Arguments

Value

An R list of nodes, edges and an 'igraph' network graph.

Highlight road by name.

Description

Highlight road by name.

Usage

streetHighlight(road.name, col = "red", lwd = 3, latlong = FALSE)

Arguments

Value

A base R graphics segment(s).

Examples

snowMap()
streetHighlight("Broad Street")

Compute length of selected street.

Description

Compute length of selected street.

Usage

streetLength(road = "Oxford Street", distance.unit = "meter",
  latlong = FALSE)

Arguments

Value

An R vector of length one.

Examples

streetLength("Oxford Street")
streetLength("oxford street")
streetLength("oxford street", distance.unit = "yard")

Locate street(s) by name(s).

Description

Highlight selected road(s) and cases.

Usage

streetNameLocator(street.name = "Broad Street", zoom = TRUE,
  latlong = FALSE, cases = "address", token = "id", vestry = FALSE,
  add.pump = TRUE, add.title = TRUE, add.subtitle = TRUE,
  highlight = TRUE, distance.unit = "meter", time.unit = "second",
  walking.speed = 5, cex.text = 0.67)

Arguments

Value

A base R graphics plot.

Note

See streetNames().

Examples

## Not run: 
#' streetNameLocator("broad street")
streetNameLocator("Broad Street", zoom = -10)
streetNameLocator("Broad Street", latlong = TRUE, zoom = -10)
streetNameLocator("Broad Street", distance.unit = "yard")
streetNameLocator("Broad Street", zoom = FALSE)

## End(Not run)

Street names (alphabetized).

Description

Unique road names from Snow's cholera map.

Usage

streetNames()

Value

An R character vector.

Note

See vignette("roads"), and roads and road.segment data frames.

Locate street by its numerical ID.

Description

Highlight selected road segment(s) and cases.

Usage

streetNumberLocator(street.number = 216, zoom = TRUE, latlong = FALSE,
  cases = "address", token = "id", vestry = FALSE, add.pump = TRUE,
  add.title = TRUE, add.subtitle = TRUE, highlight = TRUE,
  distance.unit = "meter", time.unit = "second", walking.speed = 5,
  cex.text = 0.67)

Arguments

Value

A base R graphics plot.

Note

See cholera::roads.

Examples

## Not run: 
streetNumberLocator(216)
streetNumberLocator(216, zoom = -10)
streetNumberLocator(216, latlong = TRUE, zoom = -10)
streetNumberLocator(216, distance.unit = "yard")
streetNumberLocator(216, zoom = FALSE)

## End(Not run)

Summary method for neighborhoodEuclidean().

Description

Return computed counts for Euclidean neighborhoods.

Usage

## S3 method for class 'euclidean'
summary(object, ...)

Arguments

Value

A vector of counts by neighborhood.

Examples

## Not run: 
summary(neighborhoodEuclidean())

## End(Not run)

Summary method for voronoiNominal().

Description

Return computed counts for Voronoi neighborhoods.

Usage

## S3 method for class 'voronoi_nominal'
summary(object, ...)

Arguments

Value

A vector of counts by neighborhood.

See Also

addVoronoi() plot.voronoi()

Tanaka contour plot.

Description

Soho elevation data.

Usage

tanakaContourPlot(add = FALSE)

Arguments

Aggregate time series fatality data from the Vestry report.

Description

Aggregate time series fatality data from the Vestry report.

Usage

timeSeries(vestry = FALSE)

Arguments

Value

A R list with two objects: "data" and "source" ("snow" or "vestry").

• date: Calendar date.

• day: Day of the week.

• deaths: Measure of fatality.

• fatal.attacks: Measure of fatality.

Note

The "snow" data appears on p. 117 of the report; the "vestry" data appear in Appendix B on p.175.

See Also

plot.time_series, print.time_series, vignette("time.series")

Examples

timeSeries(vestry = TRUE)
plot(timeSeries())

Unstack "stacks" in Snow's cholera map.

Description

Unstacks fatalities data by 1) assigning the coordinates of the base case to all cases in a stack and 2) setting the base case as an "address" and making the number of fatalities an attribute.

Usage

unstackFatalities(multi.core = FALSE, dev.mode = FALSE)

Arguments

Value

An R list.

Note

This function documents the code that generates anchor.case, fatalities.address, fatalities.unstacked and ortho.proj.

See Also

vignette("unstacking.fatalities")

Coordinates of Voronoi polygon vertices for original map.

Description

Coordinates of Voronoi polygon vertices for original map.

Usage

voronoi.polygons

Format

A list of 13 data frames frames with 5 variables.

vertex

vertex ID

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Coordinates of Voronoi polygon vertices for Vestry Report map.

Description

Coordinates of Voronoi polygon vertices for Vestry Report map.

Usage

voronoi.polygons.vestry

Format

A list of 14 data frames frames with 5 variables.

vertex

vertex ID

x

x-coordinate

y

y-coordinate

lon

longitude

lat

latitude

Extract vertices of Delaunay triangles and Dirichelet (Voronoi) tiles.

Description

For construction and plotting of Delaunay and Voronoi polygons.

Usage

voronoiPolygons(sites, rw.data = NULL, rw = NULL, type = "tiles",
  output = "vertices", latlong = FALSE)

Arguments

Value

An R list of data frames or base R graphics polygon()'s'.

Note

This function relies on the 'deldir' package.

Examples

snowMap()
voronoiPolygons(pumps, output = "polygons")

snowMap()
voronoiPolygons(pumps, roads, output = "polygons")

snowMap()
voronoiPolygons(pumps, roads, type = "triangles", output = "polygons")

vertices <- voronoiPolygons(pumps, roads)
snow.colors <- grDevices::adjustcolor(snowColors(), alpha.f = 1/3)
snowMap(add.cases = FALSE)
invisible(lapply(seq_along(vertices), function(i) {
  polygon(vertices[[i]], col = snow.colors[[i]])
}))

Compute walking path from case/landmark to nearest or selected pump.

Description

Compute walking path from case/landmark to nearest or selected pump.

Usage

walkingPath(origin = 1, destination = NULL, type = "case-pump",
  vestry = FALSE, latlong = FALSE, case.set = "observed",
  location = "nominal", weighted = TRUE, distance.unit = "meter",
  time.unit = "second", walking.speed = 5, include.landmarks = TRUE)

Arguments