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other.Rraw
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other.Rraw
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pkgs = c("ggplot2", "hexbin", "plyr", "dplyr", "caret", "zoo", "xts", "gdata", "nlme", "bit64", "knitr", "parallel", "sf", "nanotime", "R.utils", "yaml")
# First expression of this file must be as above: .gitlab-ci.yml uses parse(,n=1L) to read one expression from this file and installs pkgs.
# So that these dependencies of other.Rraw are maintained in a single place.
# TEST_DATA_TABLE_WITH_OTHER_PACKAGES is off by default so this other.Rraw doesn't run on CRAN. It is run by GLCI, locally in dev, and by
# users running test.data.table("other.Rraw").
# zoo needs to be before xts for #5101 otherwise xts's dependency zoo gets attached at position 2 if xts is loaded first
# Optional Suggest-ed package tests moved from tests.Rraw to here in #5516. Retaining their comments:
# "xts", # we have xts methods in R/xts.R
# "nanotime", # fwrite looks for the 'nanotime' class name at C level (but we have our own writer in C, though)
# "yaml" # for fread's yaml argument (csvy capability)
# # zoo # In DESCRIPTION:Suggests otherwise R CMD check warning: '::' or ':::' import not declared from: 'zoo'; it is tested in other.Rraw though
if (exists("test.data.table",.GlobalEnv,inherits=FALSE) ||
!"package:data.table" %in% search()) {
stop("Usage: R CMD INSTALL; require(data.table); test.data.table('other.Rraw')")
# running other.Raw in dev mode (i.e. when data.table is not installed) is not intended to work
}
test = data.table:::test
INT = data.table:::INT
if (any(duplicated(pkgs))) stop("Packages defined to be loaded for integration tests in 'inst/tests/other.Rraw' contains duplicates.")
f = function(pkg) suppressWarnings(suppressMessages(isTRUE(
library(pkg, character.only=TRUE, logical.return=TRUE, quietly=TRUE, warn.conflicts=FALSE, pos="package:base") # attach at the end for #5101
)))
loaded = sapply(pkgs, f)
if (any(!loaded)) {
stop("test.data.table('other.Rraw') is missing required package(s): ", toString(names(loaded)[!loaded]), ". If you can't install them and this is R CMD check, please set environment variable TEST_DATA_TABLE_WITH_OTHER_PACKAGES back to the default, false.")
# Would like to install them now for convenience but gitlab-ci.yml seems to install to bus/mirror-other-packages/cran.
# If that's a cache, that's nice, but we don't know at this point whether this script is being run by GLCI or by a user or in dev.
# We don't allow skipping (e.g. if _R_CHECK_FORCE_SUGGESTS_ is FALSE) to keep things simple and to keep things strict; i.e.
# if this script runs then we want to be sure it has fully passed.
}
cat("\n")
print(data.table(pkg=pkgs, loaded)[loaded==TRUE, .(pkg, version=sapply(pkg, function(p) format(packageVersion(p))))])
cat("\n")
print(sessionInfo())
cat("\n")
if (all(c("package:reshape","package:reshape2") %in% search())) {
warning("Packages 'reshape' and 'reshape2' are both loaded. There have been problems before when you don't use the :: namespace prefix to disambiguate. Probably best to either remove.packages('reshape') and use reshape2 instead, or always use :: when packages mask non-generic names.")
}
if (loaded[["ggplot2"]]) {
DT = data.table( a=1:5, b=11:50, d=c("A","B","C","D"), f=1:5, grp=1:5 )
test(1.1, names(print(ggplot(DT,aes(b,f))+geom_point()))[c(1,3)], c("data","scales")) # update as described in #3047
test(1.2, DT[,print(ggplot(.SD,aes(b,f))+geom_point()),by=list(grp%%2L)],data.table(grp=integer())) # %%2 to reduce time needed for ggplot2 to plot
if (loaded[["hexbin"]]) {
# Test reported by C Neff on 11 Oct 2011
# TODO(r-lib/gtable#94): don't suppressWarnings() here.
x <- suppressWarnings(print(ggplot(DT) + geom_hex(aes(b, f)) + facet_wrap(~grp)))
test(1.3, names(x)[c(1L, 3L)], c("data", "scales"))
}
# Test plotting ITime with ggplot2 which seems to require an as.data.frame method for ITime, #1713
datetimes = c("2011 NOV18 09:29:16", "2011 NOV18 10:42:40", "2011 NOV18 23:47:12",
"2011 NOV19 01:06:01", "2011 NOV19 11:35:34", "2011 NOV19 11:51:09")
DT = IDateTime(strptime(datetimes,"%Y %b%d %H:%M:%S"))
# without as.POSIXct() there is a message but if it gets solved and goes away in future then i) don't fail and ii) restore
# test without as.POSIXct needed and without message
# test(1.4, print(DT[,qplot(idate,itime)])$ranges,
# message="Don't know how to automatically pick scale for object of type ITime. Defaulting to continuous")
test(1.5, print(DT[,qplot(idate,as.POSIXct(itime,tzone=""))])$ranges, print(qplot(idate,as.POSIXct(itime,tzone=""),data=DT))$ranges)
try(graphics.off(),silent=TRUE)
}
if (loaded[["plyr"]]) {
# Test key and indices are dropped when non-dt-aware packages reorders rows using `[`
DT = data.table(a=1:10,b=1:2,key="a")
setindex(DT, b)
test(2.1, plyr::arrange(DT,b), data.table(a=INT(1,3,5,7,9,2,4,6,8,10),b=INT(1,1,1,1,1,2,2,2,2,2)))
}
if (loaded[["dplyr"]]) {
# dplyr::arrange uses vctrs::vec_slice which is implemented in C and bypasses `[` dispatch; #5042
DT = data.table(A=c("b","c","a"), B=10:12)
setindex(DT, A)
DT2 = dplyr::arrange(DT, A)
test(2.2, DT2[A=="c"], data.table(A="c", B=11L))
}
if (FALSE) { # loaded[["reshape"]]
# Fix for #825
# The bug was that names(DT) changed, hence testing DT here not ans. Same fix tested next with caret, so we now just rely on the caret test.
# When running this test on 13 Mar 2018, I noticed that reshape::cast doesn't retain the Date class and returns just numbers. So I copied
# this test to the reshape2 section in main tests.Rraw, changed it to use dcast instead and tested the result explicitly.
DT = data.table(ID = c(611557L, 611557L, 611557L, 894125L, 894125L, 894125L, 894125L, 894125L, 898856L, 898856L, 898856L, 898856L, 898856L, 898856L, 898899L, 898899L, 898899L), DATUM = structure(c(16101, 16071, 16261, 16104, 16133, 16167, 16201, 16236, 16089, 16118, 16147, 16176, 16236, 16208, 16163, 16125, 16209), class = "Date"), N = c(25L, 9L, 23L, 29L, 26L, 26L, 27L, 28L, 39L, 39L, 38L, 36L, 40L, 39L, 19L, 20L, 19L), rank = c(2, 1, 3, 1, 2, 3, 4, 5, 1, 2, 3, 4, 6, 5, 2, 1, 3))
ans = cast(DT, ID ~ rank, value = "DATUM")
test(3, names(DT), c("ID", "DATUM", "N", "rank"))
}
if (loaded[["caret"]]) {
# Fix for #476
# caret seems heavy (plyr, reshape2 and withr). win-builder halts at this point consistently, but we pass on Travis and locally.
# So I put the win-builder fail down to resource issues and moved this test into test.data.table("other.Rraw").
DT = data.table(x = rnorm(10), y = rnorm(10))
cv.ctrl = trainControl(method = 'repeatedcv', number = 5, repeats = 1)
# TODO(topepo/caret#1361): remove suppressWarnings() for partially matched args internal to caret
fit = suppressWarnings(train(y ~ x, data = DT, 'lm', trControl = cv.ctrl))
test(4, names(DT), c("x", "y"))
}
if (loaded[["xts"]]) {
# xts's last returns a one row data.table ok (setDT is needed to pass strict selfrefok(), but if not, no matter, the first subsequent := heals it (if any).
# Not true when DT is a one column data.table/data.frame, see below.
# Potentially, we could unload and reload xts in different orders.
# But users should be using :: to disambiguate (like Python forces you to always).
# This does not apply to code within packages because the NAMESPACE file in a package requires you to disambiguate functions like first() and
# last() which are non-S3 function names in several packages.
x = xts(1:100, Sys.Date()+1:100)
test(5, last(x,10), x[91:100,])
# The important thing this tests is that data.table's last() dispatches to xts's method when data.table is loaded above xts.
# But this might not be the case, depending on whether xts was already loaded before loading data.table.
# So to make this test relevant, in a fresh R session type: "require(xts);require(data.table);test.data.table('other.Rraw')"
# rather than: "require(data.table);require(xts);test.data.table('other.Rraw')"
# Which was the main thrust of bug#2312 fixed in v1.8.3
}
if (loaded[["gdata"]]) {
if (!loaded[["xts"]]) warning("The gdata test expects xts loaded as well since all 3 have a last() function.")
x = list("a",1:2,89)
test(6.1, xts::last(x), list(89)) # would prefer 89 here like data.table does, since "last" means the last one (never more than one) so why retain the one-item list() level?
test(6.2, gdata::last(x), list(89))
test(6.3, data.table::last(x), 89)
DT = data.table(a=7:9)
test(6.4, setDT(xts::last(DT)), data.table(a=9L)) # xts 0.11-0 changes from 9L to data.table(a=9L), setDT added due to "Test 6.4 ran without errors but selfrefok(x) is FALSE", see #3047
test(6.5, data.table::last(DT), DT[3L])
}
if (loaded[["zoo"]]) {
# as.Date.IDate won't change the class if xts package loaded #1500
x = as.IDate("2016-01-15")
test(7.1, class(as.Date(x)), "Date")
# keep.rownames retains zoo::index correctly, #1993
zoo_obj = zoo(matrix(1:12, 4, 3), as.Date("2003-01-01") + 0:3)
test(7.2, as.data.table(zoo_obj, keep.rownames=TRUE),
data.table(rn = c("2003-01-01", "2003-01-02", "2003-01-03", "2003-01-04"),
x.1 = 1:4, x.2 = 5:8, x.3 = 9:12))
}
if (loaded[["nlme"]]) {
# commented out to be consistent with base R, as #1078 and #1128 are more common cases..
# until we can find a workaround for this, Arun disabled this one.
# Search for "Fix for #1078" for the tests..
# These were tests 527 and 528 in tests.Rraw
# test(8.1, {x=Orthodont;tt=lme(distance ~ age, data=x); tt[["data"]]=NULL; tt},
# {x=as.data.table(Orthodont);tt=lme(distance ~ age, data=x);tt[["data"]]=NULL;tt})
test(8.2, {x=iris;tt=groupedData( Sepal.Length ~ Sepal.Width | Species, data=x);attr(tt,"class")=NULL;attr(tt,"FUN")=NULL;tt},
{x=as.data.table(iris);tt=groupedData( Sepal.Length ~ Sepal.Width | Species, data=x);attr(tt,"class")=NULL;attr(tt,"FUN")=NULL;attr(tt,".internal.selfref")=NULL;tt})
}
if (loaded[["bit64"]]) {
# these don't pass UBSAN/USAN because of the overflow, so just here in other.Rraw
test(9.1, as.character((as.integer64(2^62)-1)*2+1), "9223372036854775807")
test(9.2, as.character((as.integer64(2^62)-1)*2+2), NA_character_, warning="integer64 overflow")
test(9.3, as.character(-(as.integer64(2^62)-1)*2-1), "-9223372036854775807")
test(9.4, as.character(-(as.integer64(2^62)-1)*2-2), NA_character_, warning="integer64.*flow")
}
if (loaded[["gdata"]]) {
# fix for bug #81
DT <- data.table(a = c('asdfasdf','asdf','asdgasdgasdgasdg','sdg'), b = runif(4,0,1))
test(10, write.fwf(DT, f<-tempfile()), NULL)
unlink(f)
}
if (loaded[["knitr"]]) {
# That data.table-unaware code in packages like knitr still work
# kable in knitr v1.6 uses DF[...] syntax inside it but the user might have passed a data.table.
# Which is fine and works thanks to cedta().
DT = data.table(x=1, y=2)
test(11, kable(DT), output="x.*y.*1.*2")
}
if (loaded[["parallel"]]) {
#1745 and #1727
if (.Platform$OS.type=="windows") {
warning("This test of auto fallback to single threaded mode when data.table is used from package parallel, does not run on Windows because 'mc.cores'>1 is not supported on Windows; i.e., parallel package isn't parallel on Windows, IIUC. Whereas data.table is parallel built-in on Windows for some functions (fwrite/fread/fsort and expanding) using OpenMP.")
} else {
setDTthreads(2)
if (getDTthreads()!=2) {
# Under UBSAN and ASAN, threads are limited to 1, so only run this test when we have 2 threads.
cat("\n**** Can't get 2 OpenMP threads so unable to test auto fall back to single threaded mode when called from package parallel. Tests using it will be skipped.\n\n> getDTthreads(verbose = TRUE)\n")
getDTthreads(verbose = TRUE)
cat("\n")
} else {
lx <- replicate(4, runif(1e5), simplify=FALSE)
f <- function(mc.cores = 2, threads = 2) {
setDTthreads(threads)
invisible(mclapply(lx, function(x) fsort(x), mc.cores = mc.cores))
}
threadsBefore = getDTthreads()
f(1, 1) # was always ok
f(2, 1) # was always ok
f(1, 2) # was always ok
f(2, 2) # Used to hang. Now should not because data.table auto switches to single threaded
# Commenting out avoid_openmp_hang_within_fork() confirms this test catches catches the hang
test(13.1, getDTthreads()==threadsBefore) # User returned to multithreaded after fork, form v1.12.0 (see news item)
setDTthreads(2)
test(13.2, getDTthreads()==2)
}
}
}
# example(":=", local=TRUE) triggered cedta==FALSE and then error, #2972
test(14.1, {example(':=', package='data.table', local=TRUE, echo=FALSE); TRUE})
test(14.2, {example('CJ', package='data.table', local=TRUE, echo=FALSE); TRUE})
if (loaded[["sf"]]) { #2273
DT = as.data.table(st_read(system.file("shape/nc.shp", package = "sf"), quiet=TRUE))
test(15, DT[1:3, .(NAME, FIPS, geometry)], output="Ashe.*-81.4.*Surry.*-80.4")
dsf = sf::st_as_sf(data.table(x=1:10, y=1:10, s=sample(1:2, 10, TRUE)), coords=1:2)
test(16, split(dsf, dsf$s), list(`1` = dsf[dsf$s == 1, ], `2` = dsf[dsf$s == 2, ]))
}
if (loaded[["yaml"]]) { # csvy; #1701. Was 2032-2033 in tests.Rraw, #5516
f = testDir("csvy/test.csvy")
DT = data.table(var1 = c("A", "B"),
var2 = c(1L, 3L),
var3 = c(2.5, 4.3))
DT_yaml = copy(DT)
setattr(DT_yaml, 'yaml_metadata',
list(name = "my-dataset",
source = "https://github.com/leeper/csvy/tree/master/inst/examples",
schema = list(fields = list(
list(name = "var1", title = "variable 1", type = "string",
description = "explaining var1",
constraints = list(list(required = TRUE))),
list(name = "var2", title = "variable 2", type = "integer"),
list(name = "var3", title = "variable 3", type = "number")
))))
## with skip = '__auto__', fread can figure out
## how to start after the metadata (just ignoring it)
test(16.01, fread(f), DT)
## should be the same, but with yaml_metadata attribute
test(16.02, fread(f, yaml = TRUE), DT_yaml)
## testing verbose messaging
test(16.03, fread(f, yaml = TRUE, verbose = TRUE),
DT_yaml, output = 'Processed.*YAML metadata.*')
## this file is identical, except the body of the
## YAML header is commented out with # (should read identically)
test(16.04,
fread(testDir('csvy/test_comment.csvy'), yaml = TRUE),
DT_yaml)
## user input is taken as most intentional & overrides YAML
DT_yaml[ , var2 := as.numeric(var2)]
test(16.05, fread(f, yaml = TRUE, colClasses = list(numeric = 'var2')),
DT_yaml, message = 'colClasses.*YAML header are in conflict.*var2')
## extraneous/unused fields shouldn't throw off reading
DT = fread(testDir('csvy/test_extraneous.csvy'), yaml = TRUE)
test(16.06, names(DT), c('Date', 'WTI'))
test(16.07, attr(DT, 'yaml_metadata'),
list(names = c("Date", "WTI"), class = "data.frame",
title = "Cushing, OK WTI Spot Price FOB", filename = "data.csv",
fileurl = "https://raw.githubusercontent.com/jrovegno/csvy/master/data.csv",
sourceurl = "http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RWTC&f=D",
source_csvy = "https://github.com/leeper/csvy/tree/master/inst/examples",
item = "PET", sourcekey = "RWTC", freq = "Daily",
rate = "MID", type = "price", units = "Dollars per Barrel",
latestdate = "2015-08-31", releasedate = "2015-09-02",
nextreleasedate = "2015-09-10", source = "Thomson Reuters",
contactemail = "infoctr@eia.doe.gov", contactphone = "(202) 586-8800"))
## yaml can also handle sep, dec, quote, and na.strings
DT_out = data.table(var1 = c("A", "B"),
var2 = c(1L, NA),
var3 = c(2.5, 4.3))
meta =
list(name = NULL,
schema = list(fields = list(
list(name = "var1", title = "variable 1", type = "string",
description = "a single-quoted character variable"),
list(name = "var2", title = "variable 2", type = "integer"),
list(name = "var3", title = "variable 3", type = "number",
description = "European-style numeric")
)),
header = TRUE, sep = "|", dec = ",",
quote = "'", na.strings = "@")
attr(DT_out, 'yaml_metadata') = meta
test(16.08, fread(testDir( 'csvy/test_attributes.csvy'), yaml = TRUE), DT_out)
## user-specified attributes can override data from YAML
meta$sep = "-"
setattr(DT_out, 'yaml_metadata', meta)
test(16.09, fread(testDir('csvy/test_override_sep.csvy'), yaml = TRUE, sep = '|'), DT_out,
message = 'User-supplied.*sep.*override')
meta$sep = "|"
setattr(DT_out, 'yaml_metadata', meta)
test(16.10, fread(testDir('csvy/test_override_header.csvy'), yaml = TRUE, header = FALSE),
DT_out, message = 'User-supplied.*header.*override')
col.names = c('x', 'y', 'z')
setnames(DT_out, col.names)
test(16.11, fread(testDir('csvy/test_override_header.csvy'), yaml = TRUE, header = FALSE, col.names = col.names), DT_out,
message = c('User-supplied.*header.*override', 'User-supplied.*col.names.*override'))
test(16.12, fread(testDir('csvy/test_attributes.csvy'), yaml = TRUE, col.names = col.names),
DT_out, message = 'User-supplied.*col.names')
setnames(DT_out, c('var1', 'var2', 'var3'))
meta$quote = "^"
setattr(DT_out, 'yaml_metadata', meta)
test(16.13, fread(testDir('csvy/test_override_quote.csvy'), yaml = TRUE, quote = "'"),
DT_out, message = 'User-supplied.*quote')
meta$quote = "'"
meta$dec = "."
setattr(DT_out, 'yaml_metadata', meta)
test(16.14, fread(testDir('csvy/test_override_dec.csvy'), yaml = TRUE, dec = ','),
DT_out, message = 'User-supplied.*dec')
meta$dec = ','
meta$na.strings = 'NA'
setattr(DT_out, 'yaml_metadata', meta)
test(16.15, fread(testDir('csvy/test_override_na.csvy'), yaml = TRUE, na.strings = '@'),
DT_out, message = 'User-supplied.*na.strings')
## error if YAML malformed
test(16.16, fread(testDir('csvy/test_incomplete_header.csvy'), yaml = TRUE),
error = 'Reached the end.*YAML.*valid csvy')
## use any other CSV in test directory which doesn't have YAML
if (loaded[["R.utils"]]) test(16.17, fread(testDir('issue_2051.csv.gz'), yaml = TRUE),
error = 'Encountered.*unskipped.*constitute.*valid YAML')
## no problem if some fields are missing a type (just
## resort to standard auto-inferral, i.e., identical to
## the case of partially-specified colClasses)
DT = data.table(var1 = c("A", "B"), var2 = c(1L, 3L),
var3 = c(2.5, 4.3))
setattr(DT, 'yaml_metadata',
list(name = "my-dataset", source = "https://github.com/leeper/csvy/tree/master/inst/examples",
schema = list(fields = list(
list(name = "var1"), list(name = "var2", type = "integer"),
list(name = "var3", type = "number")
))))
test(16.18, fread(testDir('csvy/test_missing_type.csvy'), yaml = TRUE), DT)
## skip applies starting after the YAML header
setattr(DT, 'yaml_metadata',
list(schema = list(fields = list(
list(name = "var1", type = "string"),
list(name = "var2", type = "integer"),
list(name = "var3", type = "number")
))))
test(16.19, fread(testDir('csvy/test_skip.csvy'), yaml = TRUE, skip = 2L), DT)
## user-supplied col.names override metadata (as for colClasses)
cn = paste0('V', 1:3)
setnames(DT, cn)
test(16.20, fread(testDir('csvy/test_skip.csvy'),
yaml = TRUE, skip = 2L, col.names = cn),
DT, message = 'User-supplied column names.*override.*YAML')
## invalid value fails
test(16.21, fread(f, yaml = 'gobble'),
error = 'isTRUEorFALSE\\(yaml\\) is not TRUE')
## warning that skip-as-search doesn't work with yaml
DT_yaml[ , var2 := as.integer(var2)]
test(16.22, fread(f, skip = 'var1,', yaml = TRUE),
DT_yaml, warning = 'Combining a search.*YAML.*')
# fwrite csvy: #3534
tmp = tempfile()
DT = data.table(a = 1:5, b = c(pi, 1:4), c = letters[1:5])
# force eol for platform independence
fwrite(DT, tmp, yaml = TRUE, eol = '\n')
as_read = readLines(tmp)
test(17.01, as_read[c(1L, 24L)], c('---', '---'))
test(17.02, grepl('source: R.*data.table.*fwrite', as_read[2L]))
test(17.03, grepl('creation_time_utc', as_read[3L]))
test(17.04, as_read[4:23],
c("schema:", " fields:", " - name: a", " type: integer",
" - name: b", " type: numeric", " - name: c", " type: character",
"header: yes", "sep: ','", "sep2:", "- ''", "- '|'", "- ''",
# NB: apparently \n is encoded like this in YAML
"eol: |2+", "", "na.strings: ''", "dec: '.'", "qmethod: double",
"logical01: no"))
tbl_body = c("a,b,c", "1,3.14159265358979,a", "2,1,b", "3,2,c", "4,3,d", "5,4,e")
test(17.05, as_read[25:30], tbl_body)
# windows eol
fwrite(DT, tmp, yaml = TRUE, eol = '\r\n')
test(17.06, readLines(tmp)[18L], 'eol: "\\r\\n"')
# multi-class columns
DT[ , t := .POSIXct(1:5, tz = 'UTC')]
fwrite(DT, tmp, yaml = TRUE)
as_read = readLines(tmp)
test(17.07, as_read[13L], " type: POSIXct")
# ~invertibility~
# fread side needs to be improved for Hugh's colClasses update
DT[ , t := NULL]
fwrite(DT, tmp, yaml = TRUE)
DT2 = fread(tmp, yaml = TRUE)
# remove metadata to compare
attr(DT2, 'yaml_metadata') = NULL
test(17.08, all.equal(DT, DT2))
test(17.09, fwrite(DT, append=TRUE, yaml=TRUE, verbose=TRUE),
output = paste0(c('Appending to existing file so setting bom=FALSE and yaml=FALSE', tbl_body[-1L]), collapse=".*"))
# TODO: test gzip'd yaml which is now supported
# yaml + bom arguments
DT = data.table(l=letters, n=1:26)
fwrite(DT, f<-tempfile(), bom=TRUE, yaml=TRUE)
fcon = file(f, encoding="UTF-8") # Windows readLines needs to be told; see also test 1658.50 in tests.Rraw
lines = readLines(fcon)
lines = lines[lines!=""] # an extra "" after "eol: |2+" (line 16) on Linux but not Windows
# remove the blank here so we don't need to change this test if/when that changes in yaml package
test(17.11, length(lines), 48L)
close(fcon)
test(17.12, readBin(f, raw(), 6L), as.raw(c(0xef, 0xbb, 0xbf, 0x2d, 0x2d, 0x2d)))
# re-write should have same output (not appended)
fwrite(DT, f<-tempfile(), bom=TRUE, yaml=TRUE)
fcon = file(f, encoding="UTF-8")
lines = readLines(fcon)
lines = lines[lines!=""]
test(17.13, length(lines), 48L)
close(fcon)
test(17.14, fread(f), DT)
unlink(f)
}
if (loaded[["xts"]]) { # was 1465 in tests.Rraw, #5516
# data.table-xts conversion #882
# Date index
dt = data.table(index = as.Date((as.Date("2014-12-12")-49):as.Date("2014-12-12"),origin="1970-01-01"),quantity = as.numeric(rep(c(1:5),10)),value = rep(c(1:10)*100,5))
xt = as.xts(matrix(data = c(dt$quantity, dt$value),ncol = 2,dimnames = list(NULL,c("quantity","value"))),order.by = dt$index)
dt_xt = as.data.table(xt)
xt_dt = as.xts.data.table(dt)
test(18.01, all.equal(dt, dt_xt, check.attributes = FALSE))
test(18.02, xt, xt_dt)
# POSIXct index
dt <- data.table(index = as.POSIXct(as.Date((as.Date("2014-12-12")-49):as.Date("2014-12-12"),origin="1970-01-01"),origin="1970-01-01"),quantity = as.numeric(rep(c(1:5),10)),value = rep(c(1:10)*100,5))
xt = as.xts(matrix(data = c(dt$quantity, dt$value),ncol = 2,dimnames = list(NULL,c("quantity","value"))),order.by = dt$index)
dt_xt = as.data.table(xt)
xt_dt = as.xts.data.table(dt)
test(18.03, all.equal(dt, dt_xt, check.attributes = FALSE))
test(18.04, xt, xt_dt)
# index types returned from to.period
dt = data.table(index = as.Date((as.Date("2014-12-12") - 729):as.Date("2014-12-12"), origin = "1970-01-01"), quantity = as.numeric(rep(c(1:5), 73)), value = rep(c(1:73) * 100, 5))
xt = as.xts(matrix(data = c(dt$quantity, dt$value), ncol = 2, dimnames = list(NULL, c("quantity", "value"))), order.by = dt$index)
xt_w = xts::to.weekly(xt)
xt_dt_xt_w = as.xts.data.table(as.data.table(xt_w))
xt_m = xts::to.monthly(xt)
xt_dt_xt_m = as.xts.data.table(as.data.table(xt_m))
xt_q = xts::to.quarterly(xt)
xt_dt_xt_q = as.xts.data.table(as.data.table(xt_q))
xt_y = xts::to.yearly(xt)
xt_dt_xt_y = as.xts.data.table(as.data.table(xt_y))
test(18.05, all.equal(xt_w, xt_dt_xt_w, check.attributes = FALSE))
test(18.06, all.equal(xt_m, xt_dt_xt_m, check.attributes = FALSE))
test(18.07, all.equal(xt_q, xt_dt_xt_q, check.attributes = FALSE))
test(18.08, all.equal(xt_y, xt_dt_xt_y, check.attributes = FALSE))
test(18.09, xts::last(1:5), 5L) # was test 1531
# xts issue from Joshua, #1347
x = as.Date(1:5, origin="2015-01-01")
test(18.10, last(x), tail(x, 1L)) # was test 1559
x = xts(1:100, Sys.Date()+1:100)
test(18.11, last(x,10), x[91:100,]) # was test 841
# The important thing this tests is that data.table's last() dispatches to xts's method when data.table is loaded above xts.
# But that isn't tested by R CMD check because xts is loaded above data.table, there.
# So to make this test is relevant, run it in fresh R session directly, after: "require(xts);require(data.table)"
# rather than: "require(data.table);require(xts)"
# Which was the main thrust of bug#2312 fixed in v1.8.3
# fix for #1484; was test 1589
x = xts::as.xts(8, order.by = as.Date("2016-01-03"))
test(18.12, all.equal(as.data.table(x), data.table(index = as.Date("2016-01-03"), V1 = 8), check.attributes=FALSE))
# IDate support in as.xts.data.table #1499; was test 1663
dt <- data.table(date = c(as.IDate("2014-12-31"),
as.IDate("2015-12-31"),
as.IDate("2016-12-31")),
nav = c(100,101,99),
key = "date")
dt.xts <- as.xts.data.table(dt)
test(18.13, dt.xts[1L], xts::xts(data.table(nav=100), order.by=as.Date("2014-12-31")))
# additional coverage missing uncovered in #3117
dt = data.table(index = as.Date((as.Date("2014-12-12")-49):as.Date("2014-12-12"),origin="1970-01-01"),quantity = as.numeric(rep(c(1:5),10)),value = rep(c(1:10)*100,5))
xt = as.xts(matrix(data = c(dt$quantity, dt$value),ncol = 2,dimnames = list(NULL,c("quantity","value"))),order.by = dt$index)
test(18.14, as.data.table(xt, keep.rownames = FALSE), dt[ , !'index'])
names(xt)[1L] = 'index'
test(18.15, as.data.table(xt), error = 'Input xts object should not')
names(xt)[1L] = 'quantity'
setcolorder(dt, c(3, 1, 2))
if (base::getRversion() < "3.6.0") as.xts = as.xts.data.table # fix for when we cannot register s3method for suggested dependency #3286
test(18.16, as.xts(dt), error = 'data.table must have a time based')
setcolorder(dt, c(2, 3, 1))
dt[ , char_col := 'a']
test(18.17, as.xts(dt), xt, warning = 'columns are not numeric')
if (base::getRversion() < "3.6.0") rm(as.xts)
# 890 -- key argument for as.data.table.xts
x = xts(1:10, as.Date(1:10, origin = "1970-01-01"))
old = options(datatable.verbose=FALSE)
test(18.18, capture.output(as.data.table(x, key="index")),
c(" index V1", " 1: 1970-01-02 1", " 2: 1970-01-03 2",
" 3: 1970-01-04 3", " 4: 1970-01-05 4", " 5: 1970-01-06 5",
" 6: 1970-01-07 6", " 7: 1970-01-08 7", " 8: 1970-01-09 8",
" 9: 1970-01-10 9", "10: 1970-01-11 10"))
options(old)
# as.data.table.xts(foo) had incorrect integer index with a column name called 'x', #4897
M = xts::as.xts(matrix(1, dimnames=list("2021-05-23", "x"))) # xts:: just to be extra robust; shouldn't be needed with rm(as.xts) above
test(18.19, inherits(as.data.table(M)$index,"POSIXct"))
# non-numeric xts coredata, #5268
x = xts::xts(x=c(TRUE,FALSE), order.by=Sys.Date()+(1:2))
colnames(x) = "value" # perhaps relates to #4897
test(18.20, identical(x, as.xts(as.data.table(x), numeric.only=FALSE)))
}
# was 2108 in tests.Rraw, #5516
# first and last should no longer load xts namespace, #3857, below commented test for interactive validation when xts present but not loaded or attached
# stopifnot("xts"%in%installed.packages(), !isNamespaceLoaded("xts")); library(data.table); x=as.POSIXct("2019-01-01"); last(x); stopifnot(!isNamespaceLoaded("xts"))
x = as.POSIXct("2019-09-09")+0:1
old = options(datatable.verbose=TRUE)
test(19.01, last(x), x[length(x)], output="!is.xts(x)")
test(19.02, first(x), x[1L], output="!is.xts(x)")
if (loaded[["xts"]]) {
xt = xts(1:2, x)
test(19.03, last(xt, 2L), xt, output="using xts::last: is.xts(x)")
test(19.04, first(xt, 2L), xt, output="using xts::first: is.xts(x)")
xt = xts(matrix(1:4, 2L, 2L), x)
test(19.05, last(xt, 2L), xt, output="using xts::last: is.xts(x)")
test(19.06, first(xt, 2L), xt, output="using xts::first: is.xts(x)")
}
# first on empty df now match head(df, n=1L), #3858
df = data.frame(a=integer(), b=integer())
test(19.11, first(df), df, output="!is.xts(x)")
test(19.12, last(df), df, output="!is.xts(x)")
options(datatable.verbose=FALSE) # so the as.data.table() doesn't pollute output
# xts last-first dispatch fix #4053
x = 1:3
y = as.POSIXct(x, origin="1970-01-01")
df = data.frame(a=1:2, b=3:2)
dt = as.data.table(df)
mx = matrix(1:9, 3, 3)
ar = array(1:27, c(3,3,3))
xt = structure(
c(142.25, 141.229996, 141.330002, 142.860001, 142.050003, 141.399994,
140.570007, 140.610001, 140.380005, 141.369995, 141.669998, 140.539993,
94807600, 69620600, 76645300, 108.999954, 109.231255, 108.360008),
class = c("xts", "zoo"), .indexCLASS = "Date", tclass = "Date", .indexTZ = "UTC", tzone = "UTC",
index = structure(c(1167782400, 1167868800, 1167955200), tzone = "UTC", tclass = "Date"),
.Dim = c(3L, 6L), .Dimnames = list(NULL, c("SPY.Open", "SPY.High", "SPY.Low", "SPY.Close", "SPY.Volume", "SPY.Adjusted"))
)
options(datatable.verbose=TRUE)
if (loaded[["xts"]]) {
test(19.21, last(x, n=2L), 2:3, output="using xts::last: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
test(19.22, last(y, n=2L), y[2:3], output="using xts::last: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
test(19.23, last(x, n=1L), 3L, output="using xts::last: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
test(19.24, last(y, n=1L), y[3L], output="using xts::last: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
xt_last = structure(
c(141.330002, 141.399994, 140.380005, 140.539993, 76645300, 108.360008),
class = c("xts", "zoo"), .indexCLASS = "Date", tclass = "Date", .indexTZ = "UTC", tzone = "UTC",
index = structure(1167955200, tzone = "UTC", tclass = "Date"),
.Dim = c(1L, 6L), .Dimnames = list(NULL, c("SPY.Open", "SPY.High", "SPY.Low", "SPY.Close", "SPY.Volume", "SPY.Adjusted"))
)
xt_last2 = structure(
c(141.229996, 141.330002, 142.050003, 141.399994, 140.610001, 140.380005,
141.669998, 140.539993, 69620600, 76645300, 109.231255, 108.360008),
class = c("xts", "zoo"), .indexCLASS = "Date", tclass = "Date", .indexTZ = "UTC", tzone = "UTC",
index = structure(c(1167868800, 1167955200), tzone = "UTC", tclass = "Date"),
.Dim = c(2L, 6L), .Dimnames = list(NULL, c("SPY.Open", "SPY.High", "SPY.Low", "SPY.Close", "SPY.Volume", "SPY.Adjusted"))
)
test(19.25, last(xt), xt_last, output="using xts::last: is.xts(x)")
test(19.26, last(xt, n=2L), xt_last2, output="using xts::last: is.xts(x)")
test(19.31, first(x, n=2L), 1:2, output="using xts::first: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
test(19.32, first(y, n=2L), y[1:2], output="using xts::first: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
test(19.33, first(x, n=1L), 1L, output="using xts::first: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
test(19.34, first(y, n=1L), y[1L], output="using xts::first: !is.xts(x) & nargs>1 & 'package:xts'%in%search()")
xt_first = structure(
c(142.25, 142.860001, 140.570007, 141.369995, 94807600, 108.999954),
class = c("xts", "zoo"), .indexCLASS = "Date", tclass = "Date", .indexTZ = "UTC", tzone = "UTC",
index = structure(1167782400, tzone = "UTC", tclass = "Date"),
.Dim = c(1L, 6L), .Dimnames = list(NULL, c("SPY.Open", "SPY.High", "SPY.Low", "SPY.Close", "SPY.Volume", "SPY.Adjusted"))
)
xt_first2 = structure(
c(142.25, 141.229996, 142.860001, 142.050003, 140.570007, 140.610001, 141.369995, 141.669998, 94807600, 69620600, 108.999954, 109.231255),
class = c("xts", "zoo"), .indexCLASS = "Date", tclass = "Date", .indexTZ = "UTC", tzone = "UTC",
index = structure(c(1167782400, 1167868800), tzone = "UTC", tclass = "Date"),
.Dim = c(2L, 6L), .Dimnames = list(NULL, c("SPY.Open", "SPY.High", "SPY.Low", "SPY.Close", "SPY.Volume", "SPY.Adjusted"))
)
test(19.35, first(xt), xt_first, output="using xts::first: is.xts(x)")
test(19.36, first(xt, n=2L), xt_first2, output="using xts::first: is.xts(x)")
} else {
test(19.21, last(x, n=2L), 2:3, output="using utils::tail: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.22, last(y, n=2L), y[2:3], output="using utils::tail: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.23, last(x, n=1L), 3L, output="using utils::tail: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.24, last(y, n=1L), y[3L], output="using utils::tail: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.25, last(xt), error="you should have 'xts' installed already")
test(19.26, last(xt, n=2L), error="you should have 'xts' installed already")
test(19.31, first(x, n=2L), 1:2, output="using utils::head: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.32, first(y, n=2L), y[1:2], output="using utils::head: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.33, first(x, n=1L), 1L, output="using utils::head: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.34, first(y, n=1L), y[1L], output="using utils::head: !is.xts(x) & nargs>1 & !'package:xts'%in%search()")
test(19.35, first(xt), error="you should have 'xts' installed already")
test(19.36, first(xt, n=2L), error="you should have 'xts' installed already")
}
test(19.41, last(x), 3L, output="using 'x[[length(x)]]': !is.xts(x) & !nargs>1 & is.null(dim(x))")
test(19.42, last(y), y[3L], output="using 'x[[length(x)]]': !is.xts(x) & !nargs>1 & is.null(dim(x))")
test(19.51, first(x), 1L, output="using 'x[[1L]]': !is.xts(x) & !nargs>1 & is.null(dim(x))")
test(19.52, first(y), y[1L], output="using 'x[[1L]]': !is.xts(x) & !nargs>1 & is.null(dim(x))")
test(19.61, last(df), structure(list(a=2L, b=2L), row.names=2L, class="data.frame"), output="using 'x[nrow(x),]': !is.xts(x) & !nargs>1 & is.data.frame(x)")
test(19.62, last(dt), data.table(a=2L, b=2L), output="using 'x[nrow(x),]': !is.xts(x) & !nargs>1 & is.data.frame(x)")
test(19.71, first(df), structure(list(a=1L, b=3L), row.names=1L, class="data.frame"), output="using 'x[1L,]': !is.xts(x) & !nargs>1 & is.data.frame(x)")
test(19.72, first(dt), data.table(a=1L, b=3L), output="using 'x[1L,]': !is.xts(x) & !nargs>1 & is.data.frame(x)")
# matrix/array utils::tail behavior is likely to change in future R, Michael is more in the topic
test(19.81, last(mx), structure(c(3L, 6L, 9L), .Dim = c(1L, 3L), .Dimnames = list("[3,]", NULL)), output="using utils::tail: !is.xts(x) & !nargs>1 & !is.null(dim(x)) & !is.data.frame(x)")
expected = if (base::getRversion() < "3.7.0") 27L else structure(c(3L, 6L, 9L, 12L, 15L, 18L, 21L, 24L, 27L), .Dim = c(1L, 3L, 3L), .Dimnames = list("[3,]", NULL, NULL)) #4127
test(19.82, last(ar), expected, output="using utils::tail: !is.xts(x) & !nargs>1 & !is.null(dim(x)) & !is.data.frame(x)")
test(19.91, first(mx), structure(c(1L, 4L, 7L), .Dim = c(1L, 3L)), output="using utils::head: !is.xts(x) & !nargs>1 & !is.null(dim(x)) & !is.data.frame(x)")
expected = if (base::getRversion() < "3.7.0") 1L else structure(c(1L, 4L, 7L, 10L, 13L, 16L, 19L, 22L, 25L), .Dim = c(1L, 3L, 3L)) #4127
test(19.92, first(ar), expected, output="using utils::head: !is.xts(x) & !nargs>1 & !is.null(dim(x)) & !is.data.frame(x)")
options(old)
if (loaded[["xts"]]) { # was 2133 in tests.Rraw, #5516
# keep.rownames in as.data.table.xts() supports a string, #4232
xts = xts::xts(1:10, structure(1:10, class = "Date"))
colnames(xts) = "VALUE"
DT = as.data.table(xts, keep.rownames = "DATE", key = "DATE")
test(20.1, colnames(DT), c("DATE", "VALUE"))
test(20.2, key(DT), "DATE")
test(20.3, as.data.table(xts, keep.rownames = "VALUE"),
error = "Input xts object should not have 'VALUE' column because it would result in duplicate column names. Rename 'VALUE' column in xts or use `keep.rownames` to change the index column name.")
test(20.4, as.data.table(xts, keep.rownames = character()),
error = "keep.rownames must be length 1")
test(20.5, as.data.table(xts, keep.rownames = NA_character_),
error = "keep.rownames must not be NA")
}
if (loaded[["nanotime"]]) {
# was 1463.62-65 in tests.Rraw, #5516
x=nanotime(1:4)
test(21.1, shift(x ), c(nanotime::nanotime(NA), x[1:3]))
test(21.2, shift(x, fill=0L), c(nanotime::nanotime(0L), x[1:3]))
test(21.3, shift(x, 1, type="cyclic"), c(x[4L], x[-4L]))
test(21.4, shift(x, -1, type="cyclic"), c(x[-1L], x[1L]))
# was 1752 in tests.Rraw, #5516
DT = data.table(A=nanotime(tt<-c("2016-09-28T15:30:00.000000070Z",
"2016-09-29T23:59:00.000000001Z",
"2016-09-29T23:59:00.000000999Z",
"1970-01-01T00:01:01.000001000Z",
"1970-01-01T00:00:00.000000000Z",
"1969-12-31T23:59:59.999999999Z",
"1969-12-31T23:59:59.000000089Z",
"1969-12-31T12:13:14.000000000Z",
"1969-12-31T12:13:14.999999999Z",
"1969-12-31T12:13:14.000000001Z",
"1967-03-15T00:00:00.300000002Z",
"1967-03-15T23:59:59.300000002Z")))
test(22, capture.output(fwrite(DT, verbose=FALSE))[-1], tt)
# was 2060.401-405 in tests.Rraw, #5516
nt = nanotime(c(1L, 2L, NA_integer_, 4L))
nt_val = nanotime(1:4)
test(23.1, as.character(fcoalesce(nt, nanotime(3L))), as.character(nt_val)) # as.character due to eddelbuettel/nanotime#46
test(23.2, as.character(fcoalesce(nt, nanotime(NA), nanotime(3L))), as.character(nt_val))
test(23.3, as.character(fcoalesce(nt, nanotime(rep(3, 4L)))), as.character(nt_val))
test(23.4, fcoalesce(nt, 1), error='Item 2 has a different class than item 1')
test(23.5, fcoalesce(nt, 1L), error = 'Item 2 is type integer but the first item is type double')
# was 2080.01-05 in tests.Rraw, #5516
n = nanotime(1:4)
n[2L] = NA
opt = options(datatable.verbose=TRUE)
test(24.1, between(n, nanotime(2), nanotime(10)), c(FALSE, NA, TRUE, TRUE), output="between parallel processing of integer64")
test(24.2, between(n, nanotime(3), nanotime(10), incbounds=FALSE), c(FALSE, NA, FALSE, TRUE), output="between parallel processing of integer64")
test(24.3, between(n, nanotime(3), nanotime(NA), incbounds=FALSE, NAbounds=NA), c(FALSE, NA, FALSE, NA), output="between parallel processing of integer64")
options(opt)
test(24.4, between(1:10, nanotime(3), nanotime(6)), error="x is not integer64 but.*Please align classes")
test(24.5, between(1:10, 3, nanotime(6)), error="x is not integer64 but.*Please align classes")
# was 2085.11 in tests.Rraw, #5516
n = nanotime(1:4)
test(25, fifelse(c(TRUE,FALSE,NA,TRUE), n, n+100), c(n[1L], n[2L]+100, nanotime(NA), n[4]))
# was 2127.27 in tests.Rraw, #5516
n = nanotime(1:12)
test(26, fcase(c(-5L:5L<0L,NA), n, c(-5L:5L>0L,NA), n+100), c(n[1L:5L], nanotime(NA), n[7L:11L]+100, as.integer64(NA)))
# na.omit works for nanotime, #4744. Was 2205 in tests.Rraw, #5516
DT = data.table(time=nanotime(c(1,NA,3)))
test(27, na.omit(DT), DT[c(1,3)])
}
# that plot works; moved from tests.Rraw 167 to here to save ram of loading graphics package and possible screen device issues on overloaded servers, #5517
DT = data.table( a=1:5, b=11:50, d=c("A","B","C","D"), f=1:5, grp=1:5 )
test(28.1, DT[,plot(b,f)], NULL)
test(28.2, as.integer(DT[,hist(b)]$breaks), seq.int(10L,50L,by=5L)) # as.integer needed for R 3.1.0
test(28.3, DT[,plot(b,f),by=.(grp)], data.table(grp=integer()))
try(graphics.off(),silent=TRUE)
# test DT$.<- in a data.table-unaware package
# moved from tests.Rraw 1890 to here to save ram of loading stats package and plot, #5517
DT = data.table(A=1:5)
test(29.1, stats::ts.plot(gpars=DT), error="object must have one or more observations")
# Inside ts.plot is a gpars$ylab<- which happens before its error. That dispatches to our $<- which does the alloc.col()
test(29.2, DT, data.table(A=1:5))
if (FALSE) { # moved from tests.Rraw in #5517 and not yet back on; wasn't sure we need to still test reshape2
# test dispatch for non-data.table objects, #4864.
if (inherits(try(getNamespace("reshape2"), silent=TRUE),"try-error")) {
test(1038.001, melt(as.data.frame(DT), id.vars=1:2, measure.vars=5:6),
error="The melt generic in data.table has been passed a data.frame")
} else {
# 1) GLCI rel-cran has reshape2 installed because caret in other.Rraw depends on reshape2
# 2) a user running test.data.table() with reshape2 installed (doesn't have to be loaded)
# 3) in dev locally I have reshape2 installed to run caret in other.Rraw
test(1038.002, melt(as.data.frame(DT), id.vars=1:2, measure.vars=5:6),
as.data.frame(melt(DT, id.vars=1:2, measure.vars=5:6)),
warning="The melt generic in data.table has been passed a data.frame")
}
}
if (loaded[["dplyr"]]) {
# regression test for converting character->list column in a magrittr (dplyr) pipe, #2651
DT = data.table(a = 1, b = 2, c = '1,2,3,4', d = 4)
test(30, DT[, c := strsplit(c, ',', fixed = TRUE) %>% lapply(as.integer) %>% as.list]$c, list(1:4))
}