finished changed related to new subdir argument

PPgp · Nov 1, 2024 · bc4827f · bc4827f
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -2,3 +2,6 @@
 ^README\.md$
 ^.github$
 ^data-raw
+^tests/last.dump.rda
+^tests/.clustersize
+^tests/.proc
diff --git a/ChangeLog b/ChangeLog
@@ -1,4 +1,4 @@
-5.2-0.9xxx (09/26/2024)
+5.2-0.9xxx (10/31/2024)
 -----
 Added dataset include_2024.
 
@@ -10,11 +10,14 @@ Fixed bug in setting time index when imputation is present in e0.predict.subnat(
 
 Added argument use.wpp.data to run.e0.mcmc(). 
 
-Added the mean variant into sumary output.
+Added the mean variant into summary output.
 
 e0.trajectories.plot() got arguments to plot the means (show.mean), the medians (show.median),
 as well as selected trajectories (traj.index).
 
+Added option of keeping multiple predictions directories in one simulation directory
+(argument "subdir" added to various functions).
+
 5.2-0 (09/15/2023)
 -----
 Annual subnational projections are now possible, via the argument "annual"

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,10 +1,22 @@
 Package: bayesLife
 Type: Package
 Title: Bayesian Projection of Life Expectancy
-Version: 5.2-0.9011
-Date: 2024-09-26
+Version: 5.2-0.9012
+Date: 2024-10-31
 Author: Hana Sevcikova, Adrian Raftery, Jennifer Chunn 
 Maintainer: Hana Sevcikova <[email protected]>
+Authors@R: c(person(given = "Hana",
+                    family = "Sevcikova",
+                    role = c("cre", "aut"),
+                    email = "[email protected]"),
+             person(given = "Adrian",
+                      family = "Raftery",
+                      role = "aut",
+                      email = "[email protected]"),
+             person(given = "Jennifer",
+                      family = "Chunn",
+                      role = "aut")
+            )
 Description: Making probabilistic projections of life expectancy for all countries of the world, using a Bayesian hierarchical model <doi:10.1007/s13524-012-0193-x>. Subnational projections are also supported.
 Depends: 
     bayesTFR (>= 7.3-0),

diff --git a/NAMESPACE b/NAMESPACE
@@ -36,6 +36,7 @@ export(
 	create.thinned.e0.mcmc,
 	get.e0.prediction,
 	has.e0.prediction,
+	available.e0.predictions,
 	get.e0.jmale.prediction,
 	has.e0.jmale.prediction,
 	get.rege0.prediction,

diff --git a/R/project_subnat.R b/R/project_subnat.R
@@ -1,6 +1,6 @@
 e0.predict.subnat <- function(countries, my.e0.file, sim.dir=file.path(getwd(), 'bayesLife.output'),
                               method = c("ar1", "shift", "scale"), predict.jmale = FALSE, my.e0M.file = NULL,
-                               end.year=2100, start.year=NULL, output.dir = NULL, annual = NULL,
+                               end.year=2100, start.year=NULL, subdir = "predictions", output.dir = NULL, annual = NULL,
                               nr.traj=NULL, seed = NULL, ar.pars = NULL, 
                                save.as.ascii = 0, verbose = TRUE, jmale.estimates = NULL, ...) {
     # Run subnational projections, using the Scale AR(1) model applied to a national bayesLife simulation 
@@ -30,7 +30,7 @@ e0.predict.subnat <- function(countries, my.e0.file, sim.dir=file.path(getwd(),
         return(compute.alpha.ar1(...))
 
     method <- match.arg(method)
-    wpred <- get.e0.prediction(sim.dir) # contains national projections
+    wpred <- get.e0.prediction(sim.dir, subdir = subdir) # contains national projections
     wdata <- wpred$e0.matrix.reconstructed
     wmeta <- wpred$mcmc.set$meta
     if(!is.null(seed)) set.seed(seed)
@@ -153,7 +153,7 @@ e0.predict.subnat <- function(countries, my.e0.file, sim.dir=file.path(getwd(),
         PIs_cqp <- array(NA, c(nr.reg, length(quantiles.to.keep), nrow(wtrajs)),
                      dimnames=list(meta$regions$country_code, dimnames(wpred$quantiles)[[2]], dimnames(wtrajs)[[1]]))
         mean_sd <- array(NA, c(nr.reg, 2, nrow(wtrajs)))
-        meta$Tc.index <- .get.Tcindex(meta$e0.matrix, cnames = meta$regions$country_name)
+        meta$Tc.index <- .get.Tcindex(meta$e0.matrix, cnames = meta$regions$country_name, stop.if.less.than2 = FALSE) # allow just one data point
         country.char <- as.character(country.obj$code)
         e0reconstructed <- meta$e0.matrix
 

diff --git a/R/projection_fcns.R b/R/projection_fcns.R
@@ -21,7 +21,8 @@ e0.predict <- function(mcmc.set = NULL, end.year = 2100,
                        replace.output = FALSE, predict.jmale = TRUE, 
                        nr.traj = NULL, thin = NULL, burnin = 10000, 
                        use.diagnostics = FALSE, save.as.ascii = 0, start.year = NULL,
-                       output.dir = NULL, low.memory = TRUE, ignore.last.observed = FALSE,
+                       output.dir = NULL, subdir = "predictions", low.memory = TRUE, 
+                       ignore.last.observed = FALSE,
                        seed = NULL, verbose = TRUE, ...){
 	if(!is.null(mcmc.set)) {
 		if (!inherits(mcmc.set, 'bayesLife.mcmc.set')) {
@@ -41,15 +42,15 @@ e0.predict <- function(mcmc.set = NULL, end.year = 2100,
 					replace.output = replace.output,  
 					nr.traj = nr.traj, thin = thin, burnin = burnin, 
 					save.as.ascii = save.as.ascii, start.year = start.year,
-					output.dir = output.dir, ignore.last.observed = ignore.last.observed,
+					output.dir = output.dir, subdir = subdir, ignore.last.observed = ignore.last.observed,
 					verbose = verbose)
 	if(predict.jmale && mcmc.set$meta$sex == 'F')
 		pred <- e0.jmale.predict(pred, ..., save.as.ascii = save.as.ascii, verbose = verbose)
 	invisible(pred)
 }
 
 e0.predict.extra <- function(sim.dir = file.path(getwd(), 'bayesLife.output'), 
-					prediction.dir = sim.dir, 
+					prediction.dir = sim.dir, subdir = "predictions", 
 					countries = NULL, save.as.ascii = 1000, verbose = TRUE, ...) {
 	# Run prediction for given countries/regions (as codes). If they are not given it will be set to countries 
 	# for which there are MCMC results but no prediction.
@@ -58,9 +59,9 @@ e0.predict.extra <- function(sim.dir = file.path(getwd(), 'bayesLife.output'),
 	mcmc.set <- get.e0.mcmc(sim.dir)
 	if(is.null(mcmc.set))
 		stop('Error in "sim.dir" argument.')
-	pred <- get.e0.prediction(sim.dir=prediction.dir)
+	pred <- get.e0.prediction(sim.dir=prediction.dir, subdir = subdir)
 	if(is.null(pred))
-		stop('Error in "prediction.dir" argument.')
+		stop('Error in "sim.dir", "prediction.dir" or/and "subdir" argument. Use available.e0.predictions() to check on valid predictions directories.')
 	if(length(setdiff(pred$mcmc.set$meta$regions$country_code, mcmc.set$meta$regions$country_code)) > 0)
 		stop('Prediction is inconsistent with the mcmc results. Use e0.predict.')
 	if(is.null(countries)) {
@@ -77,7 +78,7 @@ e0.predict.extra <- function(sim.dir = file.path(getwd(), 'bayesLife.output'),
 	new.pred <- make.e0.prediction(mcmc.set, start.year=pred$start.year, end.year=pred$end.year, replace.output=FALSE,
 									nr.traj=pred$nr.traj, burnin=pred$burnin,
 									countries=countries.idx, save.as.ascii=0, output.dir=prediction.dir,
-									force.creating.thinned.mcmc=TRUE,
+									subdir = subdir, force.creating.thinned.mcmc=TRUE,
 									write.summary.files=FALSE, ignore.last.observed = pred$ignore.last.observed,
 									verbose=verbose)
 
@@ -121,7 +122,7 @@ e0.predict.extra <- function(sim.dir = file.path(getwd(), 'bayesLife.output'),
 
 e0.prediction.setup <- function(...) {
     setup <- list(...)
-    mcmc.set <- start.year <- end.year <- burnin <- replace.output <- verbose <- countries <- NULL # to avoid R check note "no visible binding ..."
+    mcmc.set <- start.year <- end.year <- burnin <- replace.output <- verbose <- countries <- subdir <- NULL # to avoid R check note "no visible binding ..."
     if(is.null(setup$thin)) setup$thin <- NA # this is because thin is a method in coda and the naming clashes within the setup expression
     setup <- within(setup, {
         meta <- mcmc.set$meta
@@ -151,10 +152,10 @@ e0.prediction.setup <- function(...) {
 
         #setup output directory
         if (!exists("output.dir") || is.null(output.dir)) output.dir <- meta$output.dir
-        outdir <- file.path(output.dir, 'predictions')
+        outdir <- file.path(output.dir, basename(subdir))
 
         if(is.null(get0("countries"))) {
-            if(!replace.output && has.e0.prediction(sim.dir = output.dir))
+            if(!replace.output && has.e0.prediction(sim.dir = output.dir, subdir = subdir))
                 stop('Prediction in ', outdir,
                     ' already exists.\nSet replace.output=TRUE if you want to overwrite existing projections.')
             unlink(outdir, recursive=TRUE)
@@ -359,11 +360,11 @@ get.friendly.variant.names.bayesLife.prediction <- function(pred, ...)
 	return(c('median', 'lower 80', 'upper 80', 'lower 95', 'upper 95', 'mean', 'constant'))	
 
 convert.e0.trajectories <- function(dir=file.path(getwd(), 'bayesLife.output'), 
-								 n=1000, output.dir=NULL, 
+								 n=1000, subdir = "predictions", output.dir=NULL, 
 								 verbose=FALSE) {
 	# Converts all trajectory rda files into UN ascii, selecting n trajectories by equal spacing.
 	if(n <= 0) return()
-	pred <- get.e0.prediction(sim.dir=dir)
+	pred <- get.e0.prediction(sim.dir=dir, subdir = subdir)
 	predsex <- pred$mcmc.set$meta$sex
 	preds <- list()
 	preds[[predsex]] <- pred
@@ -376,15 +377,15 @@ convert.e0.trajectories <- function(dir=file.path(getwd(), 'bayesLife.output'),
 			else outdir <- output.dir
 		}
 		if(!file.exists(outdir)) dir.create(outdir, recursive=TRUE)
-		cat('Converting ', list(M='Male', F='Female')[[sex]], ' trajectories from', dir, '\n')
+		cat('Converting ', list(M='Male', F='Female')[[sex]], ' trajectories from', file.path(dir, subdir), '\n')
 		bayesTFR:::do.convert.trajectories(pred=preds[[sex]], n=n, output.dir=outdir, verbose=verbose)
 	}
 }
 
 write.e0.projection.summary <- function(dir=file.path(getwd(), 'bayesLife.output'), 
-									 output.dir=NULL, revision=NULL, adjusted=FALSE) {
+                                        subdir = "predictions", output.dir=NULL, revision=NULL, adjusted=FALSE) {
 # Writes four prediction summary files, one in a user-friendly format, one in a UN-format, one for each sex.
-	pred <- get.e0.prediction(sim.dir=dir)
+	pred <- get.e0.prediction(sim.dir=dir, subdir = subdir)
 	predsex <- pred$mcmc.set$meta$sex
 	preds <- list()
 	preds[[predsex]] <- pred
@@ -429,40 +430,41 @@ get.e0.reconstructed <- function(data, meta) {
     } else store.bayesLife.prediction(new.pred)
 }
 
-e0.median.reset <- function(sim.dir, countries = NULL, joint.male=FALSE) {
+e0.median.reset <- function(sim.dir, countries = NULL, joint.male=FALSE, ...) {
     if(is.null(countries)) {
-        pred <- get.e0.prediction(sim.dir, joint.male = joint.male)
+        pred <- get.e0.prediction(sim.dir, joint.male = joint.male, ...)
         pred$median.shift <- NULL
         .e0.store.adjustment(pred, sim.dir, joint.male)
         cat('\nMedians for all countries reset.\n')
     } else
-	    for(country in countries) pred <- e0.median.shift(sim.dir, country, reset=TRUE, joint.male=joint.male)
+	    for(country in countries) pred <- e0.median.shift(sim.dir, country, reset=TRUE, joint.male=joint.male, ...)
 	invisible(pred)
 }
 
 get.e0.shift <- function(country.code, pred) return(bayesTFR::get.tfr.shift(country.code, pred))
 
-e0.median.shift <- function(sim.dir, country, reset=FALSE, shift=0, from=NULL, to=NULL, joint.male=FALSE) {
-	pred <- get.e0.prediction(sim.dir, joint.male=joint.male)
+e0.median.shift <- function(sim.dir, country, reset=FALSE, shift=0, from=NULL, to=NULL, joint.male=FALSE, ...) {
+	pred <- get.e0.prediction(sim.dir, joint.male=joint.male, ...)
 	new.pred <- bayesTFR:::.bdem.median.shift(pred, type='e0', country=country, reset=reset, 
 				shift=shift, from=from, to=to)
 	.e0.store.adjustment(new.pred, sim.dir, joint.male)
 	invisible(new.pred)
 }
 
-e0.median.set <- function(sim.dir, country, values, years=NULL, joint.male=FALSE) {
-	pred <- get.e0.prediction(sim.dir, joint.male=joint.male)
+e0.median.set <- function(sim.dir, country, values, years=NULL, joint.male=FALSE, ...) {
+	pred <- get.e0.prediction(sim.dir, joint.male=joint.male, ...)
 	new.pred <- bayesTFR:::.bdem.median.set(pred, type='e0', country=country, 
 								values=values, years=years)
 	.e0.store.adjustment(new.pred, sim.dir, joint.male)
 	invisible(new.pred)
 }
 
-e0.median.adjust.jmale <- function(sim.dir, countries, factors = c(1.2, 1.1)) {
-    pred <- get.e0.prediction(sim.dir)
-    if (is.null(pred)) stop('No valid prediction in ', sim.dir)
+e0.median.adjust.jmale <- function(sim.dir, countries, factors = c(1.2, 1.1), subdir = "predictions") {
+    pred <- get.e0.prediction(sim.dir, subdir = subdir)
+    if (is.null(pred)) stop('Prediction not found in ', file.path(sim.dir, subdir), 
+                            '. Check available.e0.predictions() and use the subdir argument to set non-standard prediction subdirectory.')
     joint.male <- get.e0.jmale.prediction(pred)
-    if (is.null(joint.male)) stop('No valid male prediction in ', sim.dir)
+    if (is.null(joint.male)) stop('No valid male prediction in ', file.path(sim.dir, subdir))
     mcmc.set <- pred$mcmc.set
     if(is.null(countries)) {
         cat('\nNo countries given. Nothing to be done.\n')
@@ -485,11 +487,11 @@ e0.median.adjust.jmale <- function(sim.dir, countries, factors = c(1.2, 1.1)) {
                       new.meds[get.country.object(countries[icountry], mcmc.set$meta)$index,], joint.male = TRUE)
     }
     # reload adjusted prediction
-    invisible(get.e0.prediction(sim.dir, joint.male = TRUE))
+    invisible(get.e0.prediction(sim.dir, joint.male = TRUE, subdir = subdir))
 }
 
-e0.shift.prediction.to.wpp <- function(sim.dir, joint.male = FALSE, ...){
-    pred <- get.e0.prediction(sim.dir, joint.male = joint.male)
+e0.shift.prediction.to.wpp <- function(sim.dir, joint.male = FALSE, subdir = "predictions", ...){
+    pred <- get.e0.prediction(sim.dir, joint.male = joint.male, subdir = subdir)
     new.pred <- bayesTFR:::.do.shift.prediction.to.wpp(pred, 
                                                        wpp.dataset = if(joint.male) "e0Mproj" else "e0Fproj", ...)
     .e0.store.adjustment(new.pred, sim.dir, joint.male)

diff --git a/man/convert.trajectories.Rd b/man/convert.trajectories.Rd
@@ -8,11 +8,12 @@ Converts trajectories of the life expectancy stored in a binary format into two
 }
 \usage{
 convert.e0.trajectories(dir = file.path(getwd(), "bayesLife.output"), 
-    n = 1000, output.dir = NULL, verbose = FALSE)
+    n = 1000, subdir = "predictions", output.dir = NULL, verbose = FALSE)
 }
 \arguments{
   \item{dir}{Directory containing the prediction object. It should correspond to the \code{output.dir} argument of the \code{\link{e0.predict}} function.}
   \item{n}{Number of trajectories to be stored. It can be either a single number or the word \dQuote{all} in which case all available trajectories are converted.}
+  \item{subdir}{Name of subdirectory of \code{dir} containing the prediction.}
   \item{output.dir}{Directory in which the resulting files will be stored. If \code{NULL} the same directory is used as for the prediction. Otherwise, if the directory contains joint predictions for both sexes, the ouptuts are stored into subdirectories \file{F} and \file{M}.}
   \item{verbose}{Logical switching log messages on and off.}
 }

diff --git a/man/e0.median.set.Rd b/man/e0.median.set.Rd
@@ -12,16 +12,18 @@ Editing the Projection Medians
 These functions are to be used by expert analysts. They allow to change the projection medians either to specific values, including the WPP values, or shift the medians by a given constant or a factor.
 }
 \usage{
-e0.median.set(sim.dir, country, values, years = NULL, joint.male = FALSE)
+e0.median.set(sim.dir, country, values, years = NULL, joint.male = FALSE, \dots)
 
 e0.median.shift(sim.dir, country, reset = FALSE, shift = 0, 
-    from = NULL, to = NULL, joint.male = FALSE)
+    from = NULL, to = NULL, joint.male = FALSE, \dots)
 
-e0.median.adjust.jmale(sim.dir, countries, factors = c(1.2, 1.1))
+e0.median.adjust.jmale(sim.dir, countries, factors = c(1.2, 1.1),
+    subdir = "predictions")
 
-e0.median.reset(sim.dir, countries = NULL, joint.male = FALSE)
+e0.median.reset(sim.dir, countries = NULL, joint.male = FALSE, \dots)
 
-e0.shift.prediction.to.wpp(sim.dir, joint.male = FALSE, ...)
+e0.shift.prediction.to.wpp(sim.dir, joint.male = FALSE,
+    subdir = "predictions", \dots)
 }
 \arguments{
   \item{sim.dir}{Directory containing the prediction object.}
@@ -36,12 +38,13 @@ e0.shift.prediction.to.wpp(sim.dir, joint.male = FALSE, ...)
   \item{from}{Year from which the offset/reset should start. By default, it starts at the first prediction period.}
   \item{to}{Year until which the offset/reset should be done. By default, it is set to the last prediction period.}
   \item{factors}{It should be a vector where each element corresponds to one time period. The adjustment of male medians is done as \code{e0m(t) = e0f(t) - gap(t)*factor(t)}.}
-  \item{\dots}{Additional arguments passed to the underlying adjustment function. It can be \code{verbose} to show/hide the progress of the adjustment and \code{wpp.year} to adjust it to if it differs from the wpp year of the simulation.}
+  \item{subdir}{Subdirectory of \code{sim.dir} containing the predictions.}
+  \item{\dots}{Additional arguments passed to the underlying adjustment function. For \code{e0.shift.prediction.to.wpp} it can be \code{stat} with values \dQuote{median} (default) or \dQuote{mean} to specify which statistics should be adjusted; \code{verbose} to show/hide the progress of the adjustment and \code{wpp.year} to adjust it to if it differs from the wpp year of the simulation. For the other functions it can be \code{subdir} to specify the location of the prediction.}
 }
 \details{
 The function \code{e0.median.set} can be used to set the medians of the given country to specific values. Function \code{e0.median.shift} can be used to offset the medians by a specific constant, or to reset the medians to their original BHM values. Function \code{e0.median.adjust.jmale} adjusts male medians using factors that can expand or shrink the female-male gap. 
 
-Function\code{e0.shift.prediction.to.wpp} shifts the projected medians so that they correspond to the values found in the \code{e0Fproj} (\code{joint.male = FALSE}) or \code{e0Mproj} (\code{joint.male = TRUE}) datasets of the \pkg{wpp} package that either corresponds to the package used for the simulation itself or is given by the \code{wpp.year} argument. If using \pkg{wpp2022}, the dataset name is automatically adjusted depending if it is an annual or a 5-year simulation.
+Function\code{e0.shift.prediction.to.wpp} shifts the projected medians or means (if \code{stat} is \dQuote{mean}) so that they correspond to the values found in the \code{e0Fproj} (\code{joint.male = FALSE}) or \code{e0Mproj} (\code{joint.male = TRUE}) datasets of the \pkg{wpp} package that either corresponds to the package used for the simulation itself or is given by the \code{wpp.year} argument. If using \pkg{wpp2022} or higher, the dataset name is automatically adjusted depending if it is an annual or a 5-year simulation. Note that regardless if it is an adjustment of the median or mean, the corresponding offset is always converted to a shift of the median. 
 
 Function \code{e0.median.reset} resets medians of the given countries to the original values. By default it deletes adjustments for all countries.