is.na(as.logical(0/0))
is.na(as.integer(0/0))
is.nan(max(c(0/0, -1, 1)))
is.nan(max(c(-1, 1, 0/0)))
is.nan(min(c(0/0, -1, 1)))
is.nan(min(c(-1, 1, 0/0)))
{
	# as.logical(1/0) used to produce Error
	# bug 216, sbug 8/7/91 david
	as.logical(1/0)
}
{
	# comparions with NaN's used to fall thru to the hardware; we want
	# to trap them and process according to S rules;
	# comparison operations with NaN's should produce NA's.
	# bug 130 (erroneously 125), sbug 7/19/91 david.
	T
}
is.na((0/0) == (0/0)) && ! is.nan((0/0) == (0/0)) 
is.na((0/0) != (0/0)) && ! is.nan((0/0) != (0/0)) 
is.na((0/0) > (0/0))  && ! is.nan((0/0) > (0/0)) 
is.na((0/0) < (0/0))  && ! is.nan((0/0) < (0/0))
{
	# as.logical and as.integer used to fail with 0/0
	# sbug 7/16/90 david

	is.na(as.logical(0/0)) && is.na(as.integer(0/0))
}
{
	# min, max, range used to be screwy with NaN's
	# sbug 7/13/90 pat, 7/16/90 david

	x <- c(0/0, -1, 0, 1)
	y <- c(-1, 0, 1, 0/0)
	T
}
is.nan(max(x))
is.nan(max(y))
is.nan(min(x))
is.nan(min(y))
all(is.nan(range(x)))
all(is.nan(range(y)))
all(is.nan(range(c(0, 1, -1, 0/0))))
{
	# check that several functions (contour, persp, pretty, image.
	# stem, boxplot) accept NaN's and Inf's, in the sense that they are
	# either removed in Q-code, or the underlying stuff does something
	# sensible with them.
	#
	# Q-code fixes: contour, 7/12/91 bill
	#		persp, 7/12/91 bill
	#		pretty, 7/12/91 bill
	#
	# $P/narang.r now chucks Inf's along with NA's and NaN's, also changes
	# to $I/u/mach.mpp, $P/inftst.C (new), $DEV/gr_extern/test_inf.c: 
	# 	7/12/91 bill, 9/5/91 peter (twice), 9/8/91 peter (twice).
	#
	# Patch to $QPE/interface.c to convert Inf's to NA's before old S code
	# is called (this is for single precision, ATT already did it for
	# double): 7/28/91 bill
	#
	# misc: 9/4/91 peter, 9/5/91 scott, bill, 
	#
	# See also ~stest/graphics/tests/Sbug1 for related tests.

	#cat("\nSHOULD get warning 'NAs generated in: log(x)' vvv.\n")
options(warn=-1)
	m.double <- matrix(log((-1):7), 3, 3)
options(warn=1)
	#cat("SHOULD get warning 'NAs generated in: log(x)' ^^^.\n\n")
	m.single <- m.double
	storage.mode(m.single) <- "single"

	# The following statements used to produce Errors with lots of messages:
	# They should be completely silent now, not even warnings.
	dummy.device.on()
	contour(1:3, 1:3, m.double)
	contour(1:3, 1:3, m.single)
	persp(1:3, 1:3, m.double)
	persp(1:3, 1:3, m.single)
	dummy.device.off()

	# Expect no messages:
	pretty(c(Inf,1))
	pretty(as.single(c(Inf, 1)))
	T
}
{
	# (a+bi)/0 used to have an incorrect real part.
	# sbug 9/15/91 david

	Re(1i/0) == 0
}
{
	# all.equal used to fail with complexes
	# bug 386, sbug 9/16/91 david

	all.equal(c(1i,2,Inf), c(1i,2,Inf))
}
{
	# all.equal again, same mail message

	all.equal(c(1i,2,NA), c(1i,2,3)) == "1 missing value mismatches"
}
{
	# test that the code in comp_util.c underlying Re, Im and Conj works
	# for NaN's. (C code: cx_re, cx_im, cx_conj).
	# sbug 9/12/91 david

	"is.na.pattern.na"<- function(x) is.na(x) & !is.nan(x)

	"f"<- function(z) c(Re(z), Im(z), Conj(z))

# 	Tests upcoming:
	T
}
all(is.na.pattern.na(f(complex(re=0, im=NA))))
all(is.na.pattern.na(f(complex(re=NA, im=0))))
all(is.nan(f(complex(re=0, im=0/0))))
all(is.nan(f(complex(re=0/0, im=0))))
all(is.na.pattern.na(f(complex(re=NA, im=NA))))
all(is.nan(f(complex(re=0/0, im=0/0))))

{ "end cx_re, cx_im, cx_conj tests" ; T }
{
	# fixes to comp_util:Cmult by david
	# sbug 9/11/91 (twice, but ignore patch), 9/12/91 for patch - david

	if (platform() == "SUNOS5_SPARC") TRUE else {1i*Inf == Inf*1i && is.infinite(Inf*1i)}
}
{
	# various tests associated with complex math in comp_util.
	# Written on hardcopy of sbug 9/3/91, checked with david.

	# here come the tests
	T
}
{ A <- (1+1i)*Inf ; Re(A) == Inf && Im(A) == Inf }
if (platform() == "SUNOS5_SPARC") TRUE else { B <- (1+0i)*Inf ; Re(B) == Inf && Im(B) == 0 }
{ C <- complex(mod=Inf, arg=0) ; Re(C) == Inf && Im(C) == 0 }
if (platform() == "SUNOS5_SPARC") TRUE else { D <-  complex(mod=Inf, arg=pi/2) ; Re(D) == 0 && Im(D) == Inf }
{
	# Infi didn't used to data.dump/data.restore properly. On 
	# restoration, it was just Inf, not Infi.
	# bug 387, sbug 9/16/91 david

	cmpx.infi <<- Infi
	temp <- tempfile()
	data.dump("cmpx.infi", temp)
	rm(cmpx.infi)
 	data.restore(temp)
	unlink(temp)
	cmpx.infi == Infi
}
{
	# Make sure we ran $C/fix.fpcr on Sqpe for HP300. This ensures that
	# the floating point control register will get run-time initialized
	# in such a way that the machine will follow IEEE rules, not generate 
	# FPE's for exceptional math.

	if (platform() != "HP300") TRUE else {
		cat("Should NOT get any warnings with this exceptional math. vvv\n")
		ans <- is.infinite(1/0) && is.nan(0/0)
		cat("Should NOT get any warnings with this exceptional math. ^^^\n")
		ans
	}
}
{
	# 1i/0 should be 0 + Infi; it was NaN + 0i [sic] on HP-300.
	# This was due to the floating point control register on betty being
	# initialized to send SIGFPE on divide-by-zeros, instead of behaving
	# in IEEE fashion. Fixed by David's $C/fix.fpcr.
	# bug 580, 11/7/91 peter

	a <- 1i/0
	Re(a) == 0 && Im(a) == Inf
}
if (platform() == "SUNOS5_SPARC") TRUE else {
	# Inf * 1i should be complex Inf; it was NaN (NA?) on HP-300. Same
	# cause as that behind 1i/0 being NaN: floating point control 
	# register initialized to undesirable value.
	# bug 579, sbug 11/6/91 (twice) peter

	a <- Inf * 1i
	Re(a) == 0 && Im(a) == Inf

}
if (platform() == "SUNOS5_SPARC") TRUE else {
	# manifestations of bug 579 (Inf * 1i being NaN):
	# bug 579, sbug 11/6/91 (twice) peter

	a <- complex(re=0, im=Inf)
	ans <- Re(a) == 0 && Im(a) == Inf

	a2 <- complex(mod=Inf, arg=pi/2)
	ans <- ans && (Re(a2) == 0 && Im(a2) == Inf)

	ans
}
{
	# special values with mean, median. Bug 206.
	# -peter
	T
}
is.na(mean(c(1,2,3,NA), na.rm=F))
is.na(median(c(1,2,3,NA), na.rm=F))
is.infinite(m <- mean(c(1, Inf))) && sign(m) == 1
is.infinite(m <- mean(c(1, -Inf))) && sign(m) == -1
is.na(mean(c(-Inf, 0, Inf)))
is.infinite(m <- median(c(1,Inf))) && sign(m) == 1
is.infinite(m <- median(c(-Inf, 1))) && sign(m) == -1
median(c(-Inf, 1, 2)) == 1
median(c(1, 2, Inf)) == 2
median(c(-Inf, 0, Inf)) == 0