On Thu, 18 Jul 2019, Jan Galkowski wrote:
> I have confirmed that a complete workaround to these problems is available
> if, as Bill Dunlap suggested, "version=2" is used in all *save* incantations.
That will mask this particular symptom, but the real problem is that
the C++ code in the package
My apologies
On Thu, Jul 18, 2019 at 4:00 PM Bert Gunter wrote:
> This query should almost certainly be posted on the Bioconductor Help site
> rather than here. Especially so as it is a general question about a
> genomics "workflow" rather than a question about R programming.
>
> Bert Gunter
>
This query should almost certainly be posted on the Bioconductor Help site
rather than here. Especially so as it is a general question about a
genomics "workflow" rather than a question about R programming.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
Good evening,
I am dealing with an already analyzed .RData file consisting of
pre-configured data objects loaded into my environment. I am attempting to
take this data, which shows an overall correlation of survival with
methylation pattern for a form of brain cancer, and go to the individual
Peter, it appears to be the same as this bug:
https://github.com/xianyi/OpenBLAS/issues/2168
I added my info to the discussion.
Thanks for the reminder.
And thank you again to Ivan for the help.
Sarah
On Thu, Jul 18, 2019 at 3:17 PM Peter Langfelder
wrote:
>
> Sarah, if you haven't done so
Sarah, if you haven't done so already, please do us (OpenBLAS users) a
big favor and report the bug, either to Fedora or directly to OpenBLAS
maintainers.
Peter
On Thu, Jul 18, 2019 at 11:46 AM Sarah Goslee wrote:
>
> Wow. You are entirely correct. I would not have been able to pinpoint
> the
I have confirmed that a complete workaround to these problems is available if,
as Bill Dunlap suggested, "version=2" is used in all *save* incantations.
Thanks Bill!
- Jan
On Thu, Jul 18, 2019, at 10:39, William Dunlap wrote:
> Note that you can reproduce this in R-3.5.1 if you specify
Wow. You are entirely correct. I would not have been able to pinpoint
the problem, or how to test it. Thank you.
I am unhappy you are right, since these are the fast workstations I
use for all of my heavy-duty analysis, and it's not even *possible* to
rerun everything.
Oh dear.
Here, with the
Thanks Jim,
I appreciate that you spend so much time helping me on this.
I translated your code to use my plot_ly function this way, I'm not sure if
this is correct, but tried to match your x and y axis and the labels. Here is
the complete code including data below, but it seems like my code
On Thu, 18 Jul 2019 13:30:09 -0400
Sarah Goslee wrote:
> I'm not even remotely a hardware expert: if the difference is due to
> changes in the instruction set, I assume that has potential
> consequences for other things, and I just happened to spot it in this
> particular case because it's
I'll address all of your questions below, but starting with this:
> Could any of the computers
exhibiting the bizarre behaviour be equipped with an AVX-512-capable
CPU?
Yes. Both computers that are giving the bizarre results have Intel
i9-7900X CPUs; the X-series apparently is AVX-512-capable.
But it's also a convenience feature. Note that $E returned null
because there was an ambiguity. By the time you got to $Ex the column
you were referencing was unambiguous and you didn't have to type out
the whole thing. Useful if you have very long column names, for
example imported from a
On Thu, 18 Jul 2019 11:50:17 -0400
Sarah Goslee wrote:
> The problem is in the conversion from RGB to Lab.
Hmm. Assuming defaults and skipping all checks, convertColor(red.rgb,
from = "sRGB", to = "Lab") amounts to the following:
red.rgb <- t(col2rgb(rep('red',8), alpha = 0)/255)
# let's hope
I didn't include enough detail, despite the length of my original
email. The problem is in the conversion from RGB to Lab. I converted
it back to RGB because most of us are more familiar with that. Below
are the intermediate steps.
And to make it even more bizarre, it fails with eight or more
Hello Yannick,
That behavior is documented in the help for subsetting ( ?'$' ):
Both ‘[[’ and ‘$’ select a single element of the list. The main
difference is that ‘$’ does not allow computed indices, whereas
‘[[’ does. ‘x$name’ is equivalent to ‘x[["name", exact =
FALSE]]’.
Hello all
I noticed today that you can access dataframe columns by using incomplete
names. This is a really unexpected behavior which led to some unexpected errors
and I was wondering whether it's a bug or not and whether it should be changed
in the future.
Here's a working example using the
Something about the deferred string conversion object in
a <- names(attributes(apresX)[[4]][[1]][[1]])
is malformed; .Internal(inspect(a)) also infinite loops.
Will try to narrow this down.
Best,
luke
On Thu, 18 Jul 2019, William Dunlap via R-help wrote:
> If you use version=3, ascii=TRUE
Gracias Carlos por responder.
Te comento que si tengo fija la semilla.
Entendería yo que eso variaría en la estimación, pero en la predicción
debería tomar los resultados del modelo y aplicar los coeficientes. Lo
extraño es que si ejecuto varias veces solo las predicciones ... estas
tienen
If you use version=3, ascii=TRUE and look at the file made up to the point
of the error, you can see a quasi-infinite repeat of a block of 165 numbers
(after a deferred string called "base"?). Looks like inappropriate
recursion.
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Thu, Jul 18, 2019
This is, indeed, bizzare!
On Thu, 18 Jul 2019 10:35:57 -0400
Sarah Goslee wrote:
> I've gotten as far as locating the problem in this line from
> grDevices::convertColor()
>
> xyz <- from$toXYZ(color, from.ref.white)
So if you manually feed the arguments:
Lab <-
Note that you can reproduce this in R-3.5.1 if you specify serialization
version 3 (which became the default in 3.6.0).
> save(apresX, file="351-2.RData", version=2)
> save(apresX, file="351-2.RData", version=3)
Error: C stack usage 7969184 is too close to the limit
> version$version.string
[1]
Hola Carlos:
Como siempre, perfecta esta solución! Es lo que necesitaba.
Muchas gracias por esta ayuda y por el tiempo dedicado.
Saludos
On Thu, 18 Jul 2019 14:21:24 +0200
Carlos Ortega wrote:
> Hola,
>
> Sí, lo puedes hacer de esta forma...
>
> #-
> set.seed(20)
> DATOS <-
I am getting unexpected results when converting from RGB to Lab. This
is clearly some kind of configuration problem, but I cannot find it. I
have three linux workstations, both fully updated (except all are
running R 3.6.0 instead of 3.6.1, because that's the latest Fedora 30
binary). I'm running
Por la semilla.
Cada vez que inicias la red, los pesos comienzan con unos valores
aleatorios.
Si fijas la semilla, de ejecución en ejecución no debieras de ver variación.
Saludos,
Carlos Ortega
www.qualityexcellence.es
El jue., 18 jul. 2019 a las 14:58, patricio fuenmayor (<
Hola todos
Cuando realizo las predicciones del modelo multinomial con el paquete nnet,
estas cambian cada vez que lo ejecuto ... saben por qué pasa esto ??
Gracias por la ayuda.
[[alternative HTML version deleted]]
___
R-help-es mailing list
Hola,
Sí, lo puedes hacer de esta forma...
#-
set.seed(20)
DATOS <- data.frame (
ID = c (1:10)
, TIEMPO = sample(1:40, 10, replace=F)
, DEF = as.factor(sample(c(0,1), 10, replace=T))
)
library(ggplot2)
ggplot( data = DATOS ) +
geom_point( aes(x = TIEMPO,
Hola.
Ya se puede utilizar EpiLinux desde DistroTest.
https://distrotest.net/EpiLinux/5.0
Para los que no lo sepáis, EpiLinux es una distribución de linux especializada
en software de bioestadística y epidemiología y viene con R + RCommander +
RStudio instalados.
Es una oportunidad de poder
Hola Pedro:
Gracias por la ayuda. No conocía esta manera más elegante de mostrar las curvas
de Kaplan-Meier. Te la compro.
En realidad quería mostrar un gráfico con la longitud de les tiempos de
seguimiento y al final un símbolo para indicar el estado. Seria un gráfico
similar a:
Hola, te vale esto? Es forma estandar de representar graficos supervivencia
Basado en esto:
https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/
set.seed(20)
DATOS <- data.frame (
ID = c (1:10)
, TIEMPO = sample(1:40, 10, replace=F)
, DEF = sample(0:1, 10, replace=T)
Hi Steven,
I caved in and installed plotly. Not an easy task. When I tried your
example, I got a blank HTML page displayed. I then created a plot with
your data above showing every third monthday label. If this is what
you want, maybe the way I have coded it will work in plotly.
Buenos días a todos:
Alguien me puede ayudar a hacer (si se puede) con unos datos similares a:
set.seed(20)
DATOS <- data.frame (
ID = c (1:10)
, TIEMPO = sample(1:40, 10, replace=F)
, DEF = sample(0:1, 10, replace=T)
);DATOS
un gráfico que muestre
> # Test for saving. Jan Galkowski, 17th July 2019.
> # produceProtectionFault.R
>
> library(apcluster)
> cl1 <- cbind(rnorm(100, 0.2, 0.05), rnorm(100, 0.8, 0.06))
> cl2 <- cbind(rnorm(50, 0.7, 0.08), rnorm(50, 0.3, 0.05))
> x <- rbind(cl1, cl2)
>
> ## compute similarity matrix and run affinity
> "JG" == Jan Galkowski
> on Tue, 16 Jul 2019 21:56:28 -0400 writes:
JG> Did something seriously change in R 3.6.1 at least for Windows in terms
of stack impacts?
JG> I'm encountering many problems with the 00UNLOCK, needing to disable
locking during installations.
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