From ripley at stats.ox.ac.uk  Wed Jul  5 10:49:09 2006
From: ripley at stats.ox.ac.uk (Prof Brian Ripley)
Date: Wed, 5 Jul 2006 09:49:09 +0100 (BST)
Subject: [Rd] problem getting R 2.3.1 svn r38481 to pass make check-all
In-Reply-To: <1152026786.31350.9.camel@graptoleberis.geog.ucl.ac.uk>
References: <1152026786.31350.9.camel@graptoleberis.geog.ucl.ac.uk>
Message-ID: <Pine.LNX.4.64.0607050937450.11987@gannet.stats.ox.ac.uk>

By `R 2.3.1 svn r38481' do you mean R-patched?  (R 2.3.1 is released.)

Looks like r38469 ported the revised test results but not the test: I have 
now done so.


On Tue, 4 Jul 2006, Gavin Simpson wrote:

> Hi,
>
> I noticed this problem on my home desktop running FC4 and again on my
> laptop running FC5. Both have previously compiled and passed make
> check-all on 2.3.1 svn revisions from 10 days ago or so. On both these
> machines, make check-all is consistently failing (4 out of 4 attempts on
> the FC 4 desktop and 3 out of 3 on the FC 5 laptop) in the
> p-r-random-tests tests. This is with both default compiler flags and
> extra flags set in config.site.
>
> R is failing make check-all with the following set of messages:
>
> ...
> make[3]: Entering directory `/home/gavin/R/2.3-patches/build/tests'
> running code in '../../tests/p-r-random-tests.R' ... OK
> comparing 'p-r-random-tests.Rout' to
> '../../tests/p-r-random-tests.Rout.save' ...1a2,16
>> R version 2.4.0 Under development (unstable) (2006-06-30 r38463)
>> Copyright (C) 2006 The R Foundation for Statistical Computing
>> ISBN 3-900051-07-0
>>
>> R is free software and comes with ABSOLUTELY NO WARRANTY.
>> You are welcome to redistribute it under certain conditions.
>> Type 'license()' or 'licence()' for distribution details.
>>
>> R is a collaborative project with many contributors.
>> Type 'contributors()' for more information and
>> 'citation()' on how to cite R or R packages in publications.
>>
>> Type 'demo()' for some demos, 'help()' for on-line help, or
>> 'help.start()' for an HTML browser interface to help.
>> Type 'q()' to quit R.
> 254a270,274
>>> ## regression test for non-central t bug
>>> dkwtest("t", df=20, ncp=3)
>> t(df = 20, ncp = 3) PASSED
>> [1] TRUE
>>>
> make[3]: *** [p-r-random-tests.Rout] Error 1
> make[3]: Leaving directory `/home/gavin/R/2.3-patches/build/tests'
> make[2]: *** [test-Random] Error 2
> make[2]: Leaving directory `/home/gavin/R/2.3-patches/build/tests'
> make[1]: *** [test-all-devel] Error 1
> make[1]: Leaving directory `/home/gavin/R/2.3-patches/build/tests'
> make: *** [check-all] Error 2
>
> I looked in ./tests/p-r-random-tests.Rout.fail and couldn't see anything
> that indicated a failure - everything had PASSED or TRUE as results of
> the tests. I append the contents of this file below.
>
> Anyone see what is wrong?
>
> Thanks in advance,
>
> Gavin
>
> ## Contents of p-r-random-tests.Rout.fail ##
>
> R : Copyright 2006, The R Foundation for Statistical Computing
> Version 2.3.1 Patched (2006-07-03 r38481)
> ISBN 3-900051-07-0
>
> R is free software and comes with ABSOLUTELY NO WARRANTY.
> You are welcome to redistribute it under certain conditions.
> Type 'license()' or 'licence()' for distribution details.
>
> R is a collaborative project with many contributors.
> Type 'contributors()' for more information and
> 'citation()' on how to cite R or R packages in publications.
>
> Type 'demo()' for some demos, 'help()' for on-line help, or
> 'help.start()' for an HTML browser interface to help.
> Type 'q()' to quit R.
>
>> ##
>> ## RNG tests using DKW inequality for rate of convergence
>> ##
>> ## P(sup | F_n - F | > t) < 2 exp(-2nt^2)
>> ##
>> ## The 2 in front of exp() was derived by Massart. It is the best
> possible
>> ## constant valid uniformly in t,n,F. For large n*t^2 this agrees with
> the
>> ## large-sample approximation to the Kolmogorov-Smirnov statistic.
>> ##
>>
>>
>> superror <- function(rfoo,pfoo,sample.size,...) {
> +     x <- rfoo(sample.size,...)
> +     tx <- table(x)
> +     xi <- as.numeric(names(tx))
> +     f <- pfoo(xi,...)
> +     fhat <- cumsum(tx)/sample.size
> +     max(abs(fhat-f))
> + }
>>
>> pdkwbound <- function(n,t) 2*exp(-2*n*t*t)
>>
>> qdkwbound <- function(n,p) sqrt(log(p/2)/(-2*n))
>>
>> dkwtest <- function(stub = "norm", ...,
> +                     sample.size = 10000, pthreshold = 0.001,
> +                     print.result = TRUE, print.detail = FALSE,
> +                     stop.on.failure = TRUE)
> + {
> +     rfoo <- eval(as.name(paste("r", stub, sep="")))
> +     pfoo <- eval(as.name(paste("p", stub, sep="")))
> +     s <- superror(rfoo, pfoo, sample.size, ...)
> +     if (print.result || print.detail) {
> +         printargs <- substitute(list(...))
> +         printargs[[1]] <- as.name(stub)
> +         cat(deparse(printargs))
> +         if (print.detail)
> +             cat("\nsupremum error = ",signif(s,2),
> +                 " with
> p-value=",min(1,round(pdkwbound(sample.size,s),4)),"\n")
> +     }
> +     rval <- (s < qdkwbound(sample.size,pthreshold))
> +     if (print.result)
> +         cat(c(" FAILED\n"," PASSED\n",)[rval+1])
> +     if (stop.on.failure && !rval)
> +         stop("dkwtest failed")
> +     rval
> + }
>>
>> .proctime00 <- proc.time() # start timing
>>
>>
>> dkwtest("binom",size =   1,prob = 0.2)
> binom(size = 1, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("binom",size =   2,prob = 0.2)
> binom(size = 2, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("binom",size = 100,prob = 0.2)
> binom(size = 100, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("binom",size = 1e4,prob = 0.2)
> binom(size = 10000, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("binom",size =   1,prob = 0.8)
> binom(size = 1, prob = 0.8) PASSED
> [1] TRUE
>> dkwtest("binom",size = 100,prob = 0.8)
> binom(size = 100, prob = 0.8) PASSED
> [1] TRUE
>> dkwtest("binom",size = 100,prob = 0.999)
> binom(size = 100, prob = 0.999) PASSED
> [1] TRUE
>>
>> dkwtest("pois",lambda =  0.095)
> pois(lambda = 0.095) PASSED
> [1] TRUE
>> dkwtest("pois",lambda =  0.95)
> pois(lambda = 0.95) PASSED
> [1] TRUE
>> dkwtest("pois",lambda =  9.5)
> pois(lambda = 9.5) PASSED
> [1] TRUE
>> dkwtest("pois",lambda = 95)
> pois(lambda = 95) PASSED
> [1] TRUE
>>
>> dkwtest("nbinom",size =   1,prob = 0.2)
> nbinom(size = 1, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("nbinom",size =   2,prob = 0.2)
> nbinom(size = 2, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("nbinom",size = 100,prob = 0.2)
> nbinom(size = 100, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("nbinom",size = 1e4,prob = 0.2)
> nbinom(size = 10000, prob = 0.2) PASSED
> [1] TRUE
>> dkwtest("nbinom",size =   1,prob = 0.8)
> nbinom(size = 1, prob = 0.8) PASSED
> [1] TRUE
>> dkwtest("nbinom",size = 100,prob = 0.8)
> nbinom(size = 100, prob = 0.8) PASSED
> [1] TRUE
>> dkwtest("nbinom",size = 100,prob = 0.999)
> nbinom(size = 100, prob = 0.999) PASSED
> [1] TRUE
>>
>> dkwtest("norm")
> norm() PASSED
> [1] TRUE
>> dkwtest("norm",mean = 5,sd = 3)
> norm(mean = 5, sd = 3) PASSED
> [1] TRUE
>>
>> dkwtest("gamma",shape =  0.1)
> gamma(shape = 0.1) PASSED
> [1] TRUE
>> dkwtest("gamma",shape =  0.2)
> gamma(shape = 0.2) PASSED
> [1] TRUE
>> dkwtest("gamma",shape = 10)
> gamma(shape = 10) PASSED
> [1] TRUE
>> dkwtest("gamma",shape = 20)
> gamma(shape = 20) PASSED
> [1] TRUE
>>
>> dkwtest("hyper",m = 40,n = 30,k = 20)
> hyper(m = 40, n = 30, k = 20) PASSED
> [1] TRUE
>> dkwtest("hyper",m = 40,n =  3,k = 20)
> hyper(m = 40, n = 3, k = 20) PASSED
> [1] TRUE
>> dkwtest("hyper",m =  6,n =  3,k =  2)
> hyper(m = 6, n = 3, k = 2) PASSED
> [1] TRUE
>> dkwtest("hyper",m =  5,n =  3,k =  2)
> hyper(m = 5, n = 3, k = 2) PASSED
> [1] TRUE
>> dkwtest("hyper",m =  4,n =  3,k =  2)
> hyper(m = 4, n = 3, k = 2) PASSED
> [1] TRUE
>>
>>
>> dkwtest("signrank",n =  1)
> signrank(n = 1) PASSED
> [1] TRUE
>> dkwtest("signrank",n =  2)
> signrank(n = 2) PASSED
> [1] TRUE
>> dkwtest("signrank",n = 10)
> signrank(n = 10) PASSED
> [1] TRUE
>> dkwtest("signrank",n = 30)
> signrank(n = 30) PASSED
> [1] TRUE
>>
>> dkwtest("wilcox",m = 40,n = 30)
> wilcox(m = 40, n = 30) PASSED
> [1] TRUE
>> dkwtest("wilcox",m = 40,n = 10)
> wilcox(m = 40, n = 10) PASSED
> [1] TRUE
>> dkwtest("wilcox",m =  6,n =  3)
> wilcox(m = 6, n = 3) PASSED
> [1] TRUE
>> dkwtest("wilcox",m =  5,n =  3)
> wilcox(m = 5, n = 3) PASSED
> [1] TRUE
>> dkwtest("wilcox",m =  4,n =  3)
> wilcox(m = 4, n = 3) PASSED
> [1] TRUE
>>
>> dkwtest("chisq",df =  1)
> chisq(df = 1) PASSED
> [1] TRUE
>> dkwtest("chisq",df = 10)
> chisq(df = 10) PASSED
> [1] TRUE
>>
>> dkwtest("logis")
> logis() PASSED
> [1] TRUE
>> dkwtest("logis",location = 4,scale = 2)
> logis(location = 4, scale = 2) PASSED
> [1] TRUE
>>
>> dkwtest("t",df =  1)
> t(df = 1) PASSED
> [1] TRUE
>> dkwtest("t",df = 10)
> t(df = 10) PASSED
> [1] TRUE
>> dkwtest("t",df = 40)
> t(df = 40) PASSED
> [1] TRUE
>>
>> dkwtest("beta",shape1 = 1, shape2 = 1)
> beta(shape1 = 1, shape2 = 1) PASSED
> [1] TRUE
>> dkwtest("beta",shape1 = 2, shape2 = 1)
> beta(shape1 = 2, shape2 = 1) PASSED
> [1] TRUE
>> dkwtest("beta",shape1 = 1, shape2 = 2)
> beta(shape1 = 1, shape2 = 2) PASSED
> [1] TRUE
>> dkwtest("beta",shape1 = 2, shape2 = 2)
> beta(shape1 = 2, shape2 = 2) PASSED
> [1] TRUE
>> dkwtest("beta",shape1 = .2,shape2 = .2)
> beta(shape1 = 0.2, shape2 = 0.2) PASSED
> [1] TRUE
>>
>> dkwtest("cauchy")
> cauchy() PASSED
> [1] TRUE
>> dkwtest("cauchy",location = 4,scale = 2)
> cauchy(location = 4, scale = 2) PASSED
> [1] TRUE
>>
>> dkwtest("f",df1 =  1,df2 =  1)
> f(df1 = 1, df2 = 1) PASSED
> [1] TRUE
>> dkwtest("f",df1 =  1,df2 = 10)
> f(df1 = 1, df2 = 10) PASSED
> [1] TRUE
>> dkwtest("f",df1 = 10,df2 = 10)
> f(df1 = 10, df2 = 10) PASSED
> [1] TRUE
>> dkwtest("f",df1 = 30,df2 =  3)
> f(df1 = 30, df2 = 3) PASSED
> [1] TRUE
>>
>> dkwtest("weibull",shape = 1)
> weibull(shape = 1) PASSED
> [1] TRUE
>> dkwtest("weibull",shape = 4,scale = 4)
> weibull(shape = 4, scale = 4) PASSED
> [1] TRUE
>>
>> ## regression test for PR#7314
>> dkwtest("hyper", m=60, n=100, k=50)
> hyper(m = 60, n = 100, k = 50) PASSED
> [1] TRUE
>> dkwtest("hyper", m=6, n=10, k=5)
> hyper(m = 6, n = 10, k = 5) PASSED
> [1] TRUE
>> dkwtest("hyper", m=600, n=1000, k=500)
> hyper(m = 600, n = 1000, k = 500) PASSED
> [1] TRUE
>>
>> cat('Time elapsed: ', proc.time() - .proctime00,'\n')
> Time elapsed:  2.404 0.004 2.408 0 0
>>
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



[Rd] problem getting R 2.3.1 svn r38481 to pass make check-all
Prof Brian Ripley