bayesPop (version 3.2-3)

pop.map: World Map of Population Measures

Description

Generates a world map of various population measures for a given quantile and a projection or observed period.

Usage

pop.map(pred, sex = c("both", "male", "female"), age = "all", expression = NULL, ...)
get.pop.map.parameters(pred, expression = NULL, sex = c('both', 'male', 'female'), 
    age = 'all', range = NULL, nr.cats = 50, same.scale = TRUE, quantile = 0.5, ...)
    
pop.map.gvis(pred, ...)

Arguments

pred

Object of class bayesPop.prediction.

sex

One of both (default), male or female. By default the male and female counts are summed up. This argument is only used if expression is NULL.

age

Either a character string all (default) or an integer vector of age indices. Value 1 corresponds to age 0-4, value 2 corresponds to age 5-9 etc. Last age goup $130+$ corresponds to index 27. This argument is only used if expression<

expression

Expression defining the population measure to be plotted. For syntax see pop.expressions. The country components of the expression should be given as XXX.

range

Range of the population measure to be displayed. It is of the form c(min, max).

nr.cats

Number of color categories.

same.scale

Logical controlling if maps for all years of this prediction object should be on the same color scale.

quantile

Quantile for which the map should be generated. It must be equal to one of the values in dimnames(pred$quantiles[[2]]), i.e. 0, 0.025, 0.05, 0.1, 0.2, 0.25, 0.3, 0.4, 0.5, 0.6, 0.7, 0.75, 0.8, 0.9, 0.95, 0.975, 1. Value 0.5 corresponds to the

...

Additional arguments passed to the underlying functions. In pop.map, these are quantile, year, projection.index, device, main, and device.args (see

Value

• get.pop.map.parameters returns a list with elements:
• pred
  The object of class bayesPop.prediction used in the function.
• quantile
  Value of the argument quantile.
• catMethod
  If the argument same.scale is TRUE, this element contains breakpoints for categorization. Otherwise, it is NULL.
• numCats
  Number of categories.
• coulourPalette
  Subset of the rainbow palette, starting from dark blue and ending at red.
• ...
  Additional arguments passed to the function.

Performance and Caching

If the expression argument or a non-standard combination of sex and age is used, quantiles are computed on the fly. In such a case, trajectory files for all countries have to be loaded from disk, which can be quite time expensive. Therefore a simple caching mechanism was added to the prediction object which allows re-using data from previously used expressions. The prediction object points to an environment called cache which is a collection of data arrays that are results of evaluating expressions. The space-trimmed expressions are the names of the cache entries. Every time a map function is called, it is checked if the corresponding expression is contained in the cache. If it is not the case, the quantiles are computed on the fly, otherwise the existing values are taken. The cache data are also stored on disk, namely in the simulation directory of the prediction object. By default, every update of the cache in memory is also updated on the disk. Thus, data expression results can be re-used in multiple R sessions. Function pop.cleanup.cache deletes the content of the cache. This behaviour can be turned off by setting the argument write.to.cache=FALSE in the get.pop.prediction function. We use this settings in the examples throughout this manual whenever the example data from the installation directory is used, in order to prevent writing into the installation directory.

Details

pop.map creates a single map for the given time period and quantile. If the package fields is installed, a color bar legend at the botom of the map is created.

Function get.pop.map.parameters can be used in combination with pop.map. It sets breakpoints for the color scheme.

Function pop.map.gvis creates an interactive map using the googleVis package and opens it in an internet browser. It also generates a table of the mapped values that can be sorted by columns interactively in the browser.

See Also

tfr.map

Examples

##########################
# This example only makes sense if there is a simulation 
# for all countries. Below, only five countries are included,
# so the map is useless.
##########################
sim.dir <- file.path(find.package("bayesPop"), "ex-data", "Pop")
pred <- get.pop.prediction(sim.dir=sim.dir, write.to.cache=FALSE)
# Uses heat colors with seven categories by default
pop.map(pred, sex='female', age=4:10)
# Female population in child-bearing age as a proportion of totals
pop.map(pred, expression='PXXX_F[4:10] / PXXX')
# The same with more colors
params <- get.pop.map.parameters(pred, expression='PXXX_F[4:10] / PXXX')
do.call('pop.map', params)
# Another projection year on the same scale
do.call('pop.map', c(list(year=2043), params))