Displaying 20 results from an estimated 2000 matches similar to: "Another incorrect behaviour of [.data.frame (PR#13629)"
2009 Mar 28
0
Incorrect behaviour of [.data.frame (PR#13628)
Full_Name: Wacek Kusnierczyk
Version: 2.8.0 and 2.10.0 r48231
OS: Ubuntu 8.04 Linux 32 bit
Submission from: (NULL) (80.202.30.36)
According to the R Language definition (sec. 3.4.3), [.data.frame has the
following properties:
"if two indices are supplied (even if one is empty) it creates matrix-like
indexing for a structure that is basically a list of vectors of the same length.
If a
2008 Jul 01
1
[.data.frame speedup
Below is a version of [.data.frame that is faster
for subscripting rows of large data frames; it avoids calling
duplicated(rows)
if there is no need to check for duplicate row names, when:
i is logical
attr(x, "dup.row.names") is not NULL (S+ compatibility)
i is numeric and negative
i is strictly increasing
"[.data.frame" <-
function (x, i, j,
2008 Oct 26
4
odd behaviour of identical
given what ?identical says, i find the following odd:
x = 1:10
y = 1:10
all.equal(x,y)
[1] TRUE
identical(x,y)
[1] TRUE
y[11] = 11
y = y[1:10]
all.equal(x,y)
[1] TRUE
identical(x,y)
[1] FALSE
y
[1] 1 2 3 4 5 6 7 8 9 10
length(y)
[1] 10
looks like a bug.
platform i686-pc-linux-gnu
arch i686
os linux-gnu
system
2009 Mar 29
2
if does not covert raw to logical (PR#13630)
Full_Name: Wacek Kusnierczyk
Version: 2.8.0 and 2.10.0 r48242
OS: Ubuntu 8.04 Linux 32 bit
Submission from: (NULL) (80.202.30.36)
The following raises an error:
if (as.raw(1)) 1
# error: unimplemented type 'raw' in 'asLogical'
However, ?'if' says:
"
Arguments:
cond: A length-one logical vector that is not 'NA'. Conditions of
length
2009 Jan 21
0
patch for src/main/character.c
Attached is a suggested patch for src/main/character.c. It does not fix
a bug, but rather provides an improvement on the recent extension of
do_grep.
In essence, instead of four occurences of 'invert ^ LOGICAL(ind)[i]'
that accommodate for the option 'invert' added to grep, there is one
occurence of 'LOGICAL(ind)[i] ^= invert' that modifies in-place the
logical vector of
2009 Mar 30
1
duplicated fails to rise correct errors (PR#13632)
Full_Name: Wacek Kusnierczyk
Version: 2.8.0 and 2.10.0 r48242
OS: Ubuntu 8.04 Linux 32 bit
Submission from: (NULL) (129.241.110.161)
In the following code:
duplicated(data.frame(), incomparables=NA)
# Error in if (!is.logical(incomparables) || incomparables)
.NotYetUsed("incomparables != FALSE") :
# missing value where TRUE/FALSE needed
the raised error is clearly not the
2008 Jun 18
1
strsplit and the empty string
Hello,
I am wondering about the behaviour of strsplit. When the pattern
matches the beginning of the search string, the mepty string is added to
the result, but that's not the case when the pattern matches the end of
the search string:
strsplit(" hello dolly ")
[1] "" "hello" "dolly"
The man for strsplit explains the algorithm:
"
The algorithm
2009 Apr 25
0
incorrect output and segfaults from sprintf with %*d (PR#13675)
On Fri, Apr 24, 2009 at 14:40, Wacek Kusnierczyk
<Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> wrote:
> maechler at stat.math.ethz.ch wrote:
>>
>> =A0 =A0 vQ> sprintf has a documented limit on strings included in the ou=
tput using the
>> =A0 =A0 vQ> format '%s'. =A0It appears that there is a limit on the leng=
th of strings included
>> =A0 =A0 vQ>
2009 Apr 02
2
actual argument matching does not conform to the definition (PR#13634)
Full_Name: Wacek Kusnierczyk
Version: 2.10.0 r48269
OS: Ubuntu 8.04 Linux 32 bit
Submission from: (NULL) (129.241.199.164)
In the following example (and many other cases):
quote(a=1)
# 1
the argument matching is apparently incorrect wrt. the documentation (The R
Language Definition, v 2.8.1, sec. 4.3.2, p. 23), which specifies the following
algorithm for argument matching:
1. Attempt to
2009 Jan 02
1
[Fwd: Re: [R] Randomly remove condition-selected rows from a matrix]
Following Duncan's suggestion, I forward the below to R-devel.
vQ
-------- Original Message --------
Subject: Re: [R] Randomly remove condition-selected rows from a matrix
Date: Fri, 02 Jan 2009 10:34:52 -0500
From: Duncan Murdoch <murdoch at stats.uwo.ca>
To: Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no>
CC: R help <R-help at stat.math.ethz.ch>
2009 Apr 02
0
actual argument matching does not conform to the definition (PR#13635)
The explanation is that quote() is a primitive function and that the argument matching rules do not apply to primitives. That section of the R Language definition should say that primitives are excluded; it is documented in ?.Primitive.
-thomas
On Thu, 2 Apr 2009 waku at idi.ntnu.no wrote:
> Full_Name: Wacek Kusnierczyk
> Version: 2.10.0 r48269
> OS: Ubuntu 8.04 Linux 32 bit
2009 Feb 12
0
Patch for src/main/character.c, systematizing recent fix to do_grep
The attached patch provides a modification to the recent fix/improvement
to do_grep already included in the most recent development version.
The original fix added new functionality to the grep function by adding
a new parameter, 'invert'. In the source code for the underlying
do_grep, the value of the parameter is used to invert the logical
match-no match flag vector ind. The
2009 Mar 14
1
multiple hypothesis testing
Dear all,
Myself Vijaykumar Muley working as senior research fellow. By training I am
a computational biologist with not a strong knowledge of statistics. I have
done some analysis which is explained as follows,
I have 10340 (X) profiles of binary vectors with same length(N=845), I will
call then "gene profiles"
for example...
v1 v2 v3 v4.....vN
a 1 0 1 0 1
b 0
2009 May 26
1
Bug in "$<-.data.frame" yields corrupt data frame (PR#13724)
Full_Name: Steven McKinney
Version: 2.9.0
OS: Mac OS X 10.5.6
Submission from: (NULL) (142.103.207.10)
A corrupt data frame can be constructed as follows:
foo <- matrix(1:12, nrow = 3)
bar <- data.frame(foo)
bar$NewCol <- foo[foo[, 1] == 4, 4]
bar
lapply(bar, length)
> foo <- matrix(1:12, nrow = 3)
> bar <- data.frame(foo)
> bar$NewCol <- foo[foo[, 1] == 4, 4]
2024 Jul 14
2
xftrm is more than 100x slower for AsIs than for character vectors
? Fri, 12 Jul 2024 17:35:19 +0200
Hilmar Berger via R-devel <r-devel at r-project.org> ?????:
> This can be finally traced to base::rank() (called from
> xtfrm.default), where I found that
>
> "NB: rank is not itself generic but xtfrm is, and rank(xtfrm(x), ....)
> will have the desired result if there is a xtfrm method. Otherwise,
> rank will make use of ==, >,
2017 Nov 20
2
Small performance bug in [.Date
Hi all,
I think there's an unnecessary line in [.Date which has a considerable
impact on performance when subsetting large dates:
x <- Sys.Date() + 1:1e6
microbenchmark::microbenchmark(x[1])
#> Unit: microseconds
#> expr min lq mean median uq max neval
#> x[1] 920.651 1039.346 3624.833 2294.404 3786.881 41176.38 100
`[.Date` <- function(x, ...,
2009 May 14
1
Simulation)
I wrote
As a beginner, I agree .... the for loop is much clearer to me.
Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> replied
>
>well, that's quite likely. especially given that typical courses in
>programming, afaik, include for looping but not necessarily functional
>stuff -- are you an r beginner, or a programming beginner?
>
Both. My PhD is in
2009 Oct 19
2
how to get rid of 2 for-loops and optimize runtime
Short: get rid of the loops I use and optimize runtime
Dear all,
I want to calculate for each row the amount of the month ago. I use a matrix with 2100 rows and 22 colums (which is still a very small matrix. nrows of other matrixes can easily be more then 100000)
Table before
Year month quarter yearmonth Service ... Amount
2009 9 Q3 092009 A ...
2002 Oct 25
0
[., multiple inheritance, and R 1.6
Matt Nelson <MNelson at sequenom.com> reported a problem using the Hmisc library that did not occur with versions of R before 1.6. I am running
platform i686-pc-linux-gnu
arch i686
os linux-gnu
system i686, linux-gnu
status
major 1
minor 6.0
year 2002
month 10
day 01
language R
> library(Hmisc)
> g <-
2009 Nov 02
1
two small wishes (with code sugegstions) for R-core
Dear R developers,
It would be great if you could implement the two minor code changes suggested below, which would help processing large objects in R.
Jens Oehlschl?gel
# Wish no. 1: let [.AsIs return the class AFTER subsetting, not the class of the original object
# Wish no. 2: adjust write.csv and write.csv2 for multiple calls in chunked writing
# Rationale no. 1: a couple of packages