similar to: List to a summary table

Hi, I am using code below to get a plot that will show me on the X axis the number of clusters and on the Y axis the cluster average widths. However I am getting this error: Error in summary(silhouette(cutree(d, x), dist(iris[, -5])))$si.summary : $ operator is invalid for atomic vectors the code I am using is: avgs<-sapply(1:20,function(x) summary(silhouette(cutree(d,x),

On 27 June 2013 17:05, Tobias Grosser <tobias at grosser.es> wrote: > We are looking for a good way/value to show the reliability of individual > results in the UI. Do you have some experience, what a good measure of the > reliability of test results is? > Hi Tobi, I had a look at this a while ago, but never got around to actually work on it. My idea was to never use

Hello everyone, I build llvm-2.9 from source code. After install, i find the executable file is 'gcc', NOT 'llvm-gcc'. It is not convenient because there has been another gcc in system. To avoid conflict i rename gcc to llvm-gcc now. Can i avoid the problem by options when build? Thanks

On Jun 27, 2013, at 9:27 AM, Renato Golin <renato.golin at linaro.org> wrote: > On 27 June 2013 17:05, Tobias Grosser <tobias at grosser.es> wrote: > We are looking for a good way/value to show the reliability of individual results in the UI. Do you have some experience, what a good measure of the reliability of test results is? > > Hi Tobi, > > I had a look at

On 06/23/2013 11:12 PM, Star Tan wrote: > Hi all, > > > When we compare two testings, each of which is run with three samples, how would LNT show whether the comparison is reliable or not? > > > I have seen that the function get_value_status in reporting/analysis.py uses a very simple algorithm to infer data status. For example, if abs(self.delta) <= (self.stddev *

Just forwarding this to the list, my original reply was bounced. On Jun 27, 2013, at 11:14 AM, Chris Matthews <chris.matthews at apple.com> wrote: > There are a few things we have looked at with LNT runs, so I will share the insights we have had so far. A lot of the problems we have are artificially created by our test protocols instead of the compiler changes themselves. I have been

My data looks like this: > data name G_hat_0_0 G_hat_1_0 G_hat_2_0 G_0 G_hat_0_1 G_hat_1_1 G_hat_2_1 G_1 1 rs0 0.488000 0.448625 0.063375 1 0.480875 0.454500 0.064625 1 2 rs1 0.002375 0.955375 0.042250 1 0.000000 0.062875 0.937125 2 3 rs2 0.050375 0.835875 0.113750 1 0.877250 0.115875 0.006875 0 4 rs3 0.000000 0.074750 0.925250 2 0.897750 0.102000

There are a few things we have looked at with LNT runs, so I will share the insights we have had so far. A lot of the problems we have are artificially created by our test protocols instead of the compiler changes themselves. I have been doing a lot of large sample runs of single benchmarks to characterize them better. Some key points: 1) Some benchmarks are bi-modal or multi-modal, single

Hi all, When we compare two testings, each of which is run with three samples, how would LNT show whether the comparison is reliable or not? I have seen that the function get_value_status in reporting/analysis.py uses a very simple algorithm to infer data status. For example, if abs(self.delta) <= (self.stddev * confidence_interval), then the data status is set as UNCHANGED. However, it

Full_Name: Clay B Version: 2.5.0 (2007-04-23) OS: Solaris Nevada Build 55b Submission from: (NULL) (65.101.229.198) I find that running this script causes R to segfault reliably. However, running just for one system at a time (modifying the for loop updating iter to run just for a system at a time works). The system is a Sun W2100z with 12 GB of ram, and R segfaults using only around 360 MB of

OK. (Note: I am ccing this to the list so that others can correct any mistakes, misunderstandings, or misstatements that I may make; and also give you more and better advice about how to proceed. For example, there may be environmental packages ( see the environmetrics task view, https://CRAN.R-project.org/view=Environmetrics) that already do everything you want from your data source that someone