SUMMER (version 2.0.0)

hatchPlot: Plot maps with uncertainty hatching.

Description

This function visualizes the map with different variables. The input data frame can be either the long or wide format.

Usage

hatchPlot(
  data,
  variables,
  values = NULL,
  labels = NULL,
  geo,
  by.data,
  by.geo,
  is.long = FALSE,
  lower,
  upper,
  lim = NULL,
  lim.CI = NULL,
  breaks.CI = NULL,
  ncol = 4,
  hatch = NULL,
  border = NULL,
  size = 1,
  legend.label = NULL,
  per1000 = FALSE,
  direction = 1,
  ...
)

Arguments

data

a data frame with variables to be plotted

variables

vector of variables to be plotted. If long format of data is used, only one variable can be selected

values

the column corresponding to the values to be plotted, only used when long format of data is used

labels

vector of labels to use for each variable, only used when wide format of data is used

geo

SpatialPolygonsDataFrame object for the map

by.data

column name specifying region names in the data

by.geo

variable name specifying region names in the data

is.long

logical indicator of whether the data is in the long format, default to FALSE

lower

column name of the lower bound of the CI

upper

column name of the upper bound of the CI

lim

fixed range of values for the variables to plot

lim.CI

fixed range of the CI widths to plot

breaks.CI

a vector of numerical values that decides the breaks in the CI widths to be shown

ncol

number of columns for the output tabs

hatch

color of the hatching lines.

border

color of the polygon borders.

size

line width of the polygon borders.

legend.label

Label for the color legend.

per1000

logical indicator to plot mortality rates as rates per 1,000 live births. Note that the added comparison data should always be in the probability scale.

direction

Direction of the color scheme. It can be either 1 (smaller values are darker) or -1 (higher values are darker). Default is set to 1.

...

unused.

Author

Zehang Richard Li, Katie Wilson

Examples

if (FALSE) {
years <- levels(DemoData[[1]]$time)

# obtain direct estimates
data <- getDirectList(births = DemoData, 
years = years,  
regionVar = "region", timeVar = "time", 
clusterVar = "~clustid+id", 
ageVar = "age", weightsVar = "weights", 
geo.recode = NULL)
# obtain direct estimates
data_multi <- getDirectList(births = DemoData, years = years,
  regionVar = "region",  timeVar = "time", clusterVar = "~clustid+id",
  ageVar = "age", weightsVar = "weights", geo.recode = NULL)
data <- aggregateSurvey(data_multi)

fit2 <- smoothDirect(data = data, geo = geo, Amat = mat, 
  year.label = years.all, year.range = c(1985, 2019), 
  rw = 2, is.yearly=TRUE, m = 5, type.st = 4)
out2 <- getSmoothed(fit2)

plot(out2, is.yearly=TRUE, is.subnational=TRUE)

hatchPlot(data = subset(out2, is.yearly==FALSE), geo = geo,
variables=c("years"), values = c("median"), 
by.data = "region", by.geo = "REGNAME", 
lower = "lower", upper = "upper", is.long=TRUE)

}