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# Testing code for the RCMIP5 'makeGlobalStat.R' script
# Uses the testthat package
# See http://journal.r-project.org/archive/2011-1/RJournal_2011-1_Wickham.pdf
library(testthat)
# To run this code:
# source("makeGlobalStat.R")
# source("RCMIP5.R") # for cmip5data
# library(testthat)
# test_file("tests/testthat/test_makeGlobalStat.R")
context("makeGlobalStat")
implementations <- c("data.frame", "array")
test_that("makeGlobalStat handles bad input", {
expect_error(makeGlobalStat(1)) # non-list d
expect_error(makeGlobalStat(cmpi5data())) # wrong size list d
expect_error(makeGlobalStat(d,verbose=1)) # non-logical verbose
expect_error(makeGlobalStat(d,verbose=c(T, T))) # multiple verbose values
expect_error(makeGlobalStat(d,FUN=1)) # non-function FUN
expect_error(makeGlobalStat(d,FUN=c(mean, mean))) # multiple FUN values
})
test_that("makeGlobalStat handles monthly data", {
years <- 1850:1851
for(i in implementations) {
d <- cmip5data(years, loadAs=i)
res <- makeGlobalStat(d, verbose=F)
# Is 'res' correct type and size?
expect_is(res,"cmip5data", info=i)
# Did unchanging info get copied correctly?
expect_equal(res$valUnit, d$valUnit, info=i)
expect_equal(res$files, d$files, info=i)
# Lon/lat removed, numCells set, and provenance updated?
expect_null(res$lon, info=i)
expect_null(res$lat, info=i)
expect_is(res$numCells, "integer", info=i)
expect_gt(nrow(res$provenance), nrow(d$provenance)) #, info=i)
# Does time match what we expect?
expect_equal(res$time, d$time, info=i)
# Is the answer value data frame correctly sized?
expect_equal(RCMIP5:::nvals(res), RCMIP5:::nvals(d)/length(d$lon), info=i)
# Are the answer values numerically correct?
expect_equal(mean(RCMIP5:::vals(res)), mean(RCMIP5:::vals(d)), info=i) # no weighting
}
})
test_that("makeGlobalStat weights correctly", {
for(i in implementations) {
d <- cmip5data(1850, randomize=T, monthly=F, loadAs=i)
darea <- cmip5data(0, time=F, randomize=T, loadAs=i) # create an area file
res <- makeGlobalStat(d, area=darea, sortData=F, verbose=F)
# Are the answer values numerically correct?
dummyans <- weighted.mean(RCMIP5:::vals(d), w=RCMIP5:::vals(darea))
expect_equal(dummyans, RCMIP5:::vals(res), info=i)
}
})
test_that("weighted.sum works correctly", {
# d <- cmip5data(1850, randomize=T, monthly=F)
# darea <- cmip5data(0, time=F, randomize=T)
# res <- makeGlobalStat(d, area=darea, verbose=F, sortData=F, FUN=weighted.sum)
# Are the answer values numerically correct?
# dummyans <- weighted.sum(d$val$value, w=darea$val$value)
# expect_equal(dummyans, res$val$value)
# Make sure the function itself is OK
# expect_equal(weighted.sum(1:4), 10)
# expect_equal(weighted.sum(1:4, 1:4), 30) # 4*4 + 3*3 + 2*2 + 1*1
})
test_that("makeGlobalStat handles 4-dimensional data", {
for(i in implementations) {
years <- 1850:1851
d <- cmip5data(years, Z=T, loadAs=i)
res <- makeGlobalStat(d, verbose=F)
# Do years match what we expect?
expect_equal(res$time, d$time, info=i)
# Is the answer value array correctly sized?
expect_equal(RCMIP5:::nvals(res), RCMIP5:::nvals(d)/length(d$lon), info=i)
}
})
test_that("makeGlobalStat handles custom function and dots", {
years <- 1850:1851
llsize <- 2
for(i in implementations) {
d <- cmip5data(years, lonsize=llsize, latsize=llsize, loadAs=i)
darea <- cmip5data(0, time=F, lonsize=llsize, latsize=llsize, loadAs=i)
# All data 1 except for max lon/lat is 2
if(is.data.frame(d$val)) {
d$val$value <- 1
d$val$value[d$val$lon == max(d$lon) & d$val$lat == max(d$lat)] <- 2
darea$val$value <- c(rep(1, llsize*llsize-1), llsize*llsize-1)
} else if(is.array(d$val)) {
d$val <- array(1, dim=dim(d$val))
d$val[ncol(d$lon),nrow(d$lat),,] <- 2
darea$val <- array(c(rep(1, llsize*llsize-1), llsize*llsize-1), dim=dim(darea$val))
}
# Compute correct answer
ref <- cmip5data(years, lonsize=llsize, latsize=llsize, loadAs="data.frame")
ref$val$value <- 1
ref$val$value[ref$val$lon == max(ref$lon) & ref$val$lat == max(ref$lat)] <- 2
refarea <- cmip5data(0, time=F, lonsize=llsize, latsize=llsize, loadAs="data.frame")
refarea$val$value <- c(rep(1, llsize*llsize-1), llsize*llsize-1)
ans <- aggregate(value~time, data=ref$val, FUN=weighted.mean, w=RCMIP5:::vals(refarea))
res1 <- makeGlobalStat(d, darea, verbose=F, sortData=F, FUN=weighted.mean)
expect_is(res1, "cmip5data", info=i)
myfunc <- function(x, w, ...) weighted.mean(x, w, ...)
res2 <- makeGlobalStat(d, darea, verbose=F, sortData=F, FUN=myfunc)
expect_is(res2, "cmip5data", info=i)
# Are the result values correct?
expect_equal(RCMIP5:::vals(res1), ans$value, info=i)
expect_equal(RCMIP5:::vals(res2), ans$value, info=i)
# Insert NA and recalc w/ na.rm=TRUE
if(is.data.frame(d$val)) {
d$val$value[1] <- NA
} else if(is.array(d$val)) {
d$val[1] <- NA
}
ref$val$value[1] <- NA
ans <- aggregate(value~time, data=ref$val, FUN=weighted.mean, w=RCMIP5:::vals(refarea), na.action=na.pass, na.rm=TRUE)
res1 <- makeGlobalStat(d, darea, verbose=F, sortData=F, FUN=weighted.mean, na.rm=TRUE)
expect_is(res1, "cmip5data", info=i)
myfunc <- function(x, w, ...) weighted.mean(x, w, ...)
res2 <- makeGlobalStat(d, darea, verbose=F, sortData=F, FUN=myfunc, na.rm=TRUE)
expect_is(res2, "cmip5data", info=i)
# Are the result values correct?
expect_equal(RCMIP5:::vals(res1), ans$value, info=i)
expect_equal(RCMIP5:::vals(res2), ans$value, info=i)
}
})
test_that("makeGlobalStat sorts before computing", {
years <- 1850:1851
llsize <- 2
# Note this test is only applicable to the data.frame implementation
d <- cmip5data(years, lonsize=llsize, latsize=llsize, monthly=F, loadAs="data.frame")
darea <- cmip5data(0, time=F, lonsize=llsize, latsize=llsize, loadAs="data.frame")
# All data 1 except for max lon/lat is 2
d$val$value <- 1
d$val$value[d$val$lon == max(d$lon) & d$val$lat == max(d$lat)] <- 2
darea$val$value <- c(rep(1, llsize*llsize-1), llsize*llsize-1)
# Compute correct answer
ans <- aggregate(value~time, data=d$val, FUN=weighted.mean, w=darea$val$value)
# Now we put `darea` out of order and call makeGlobalStat
darea$val <- dplyr::arrange(darea$val, desc(lon), desc(lat))
res1 <- makeGlobalStat(d, darea, verbose=F, sortData=TRUE)
expect_is(res1, "cmip5data")
# makeGlobalStat should sort darea correctly before calculating
# Are the result values correct?
expect_equal(res1$val$value, ans$value)
# This should generate a warning, because sortData not specified
expect_warning(makeGlobalStat(d, darea, verbose=F))
# Put data out of order and test again
#d$val <- d$val[order(d$val$lon, d$val$lat, decreasing=TRUE),]
d$val <- dplyr::arrange(d$val, desc(lon), desc(lat))
res2 <- makeGlobalStat(d, darea, verbose=F, sortData=TRUE)
expect_equal(res2$val$value, ans$value)
})
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