similar to: how to sort new data frame based on the original data frame

Hey, I am hoping someone can help me with a sampling question. I have a data frame of 8 variables (the first column is the subjects' id): SubID CSE1 CSE2 CSE3 CSE4 WSE1 WSE2 WSE3 WSE4 1 6 5 6 2 6 2 2 4 2 6 4 7 2 6 6 2 3 3 5 5 5 5 5 5

I have another round of questions about IR select canonicalizations. For the purity of this quiz, please disregard prior knowledge of how this is handled by instcombine or how this is lowered by your favorite target...of course we'll fix it. :) Some answers in the links below if you do want to know. Which, if any, of these is canonical? 1. Is a zext simpler than a select? a. define i32

Earlier, I posted the following question: I want to superimpose histograms from three populations onto the same graph, changing the shading of the bars for each population. After consulting the help files and the archives I cannot find out how to do this (seemly) simple graph. To be clear, I want - a single x axis (from -3 to 18) - three groups of bars forming the histograms of each population

Subsetting from a dataframe with only one variable returns a vector, not a dataframe. This seems somewhat inconsistent. Wouldn't it be better if subsetting would respect the structure completely? v1<-1:4 v2<-4:1 df1<-data.frame(v1) df2<-data.frame(v1,v2) sel1<-c(TRUE,TRUE,TRUE,TRUE) > df1[sel1,] [1] 1 2 3 4 > df2[sel1,] v1 v2 1 1 4 2 2 3 3 3 2 4 4 1 -- Erich

From: Christian Borntraeger <borntraeger at de.ibm.com> drivers/s390/sysinfo.c uses the store system information intruction to query the system about information of the machine, the LPAR and additional hypervisors. KVM has to implement the host part for this instruction. To avoid code duplication, this patch splits the common definitions from sysinfo.c into a separate header file

From: Christian Borntraeger <borntraeger at de.ibm.com> drivers/s390/sysinfo.c uses the store system information intruction to query the system about information of the machine, the LPAR and additional hypervisors. KVM has to implement the host part for this instruction. To avoid code duplication, this patch splits the common definitions from sysinfo.c into a separate header file

From: Carsten Otte <cotte at de.ibm.com> From: Christian Borntraeger <borntraeger at de.ibm.com> This patch introduces in-kernel handling of some intercepts for privileged instructions: handle_set_prefix() sets the prefix register of the local cpu handle_store_prefix() stores the content of the prefix register to memory handle_store_cpu_address() stores the cpu number of

I'm looking to give the SPA-3000 a whirl as I'm having too much difficulty with the irq sharing thing inside the box. I'm reading the book but without having one in-hand to play with it appears a little obtuse at this time. Before I drop down my money can someone with some hands-on with one of these confirm if the SPA-3000 can: a) detect inbound distinctive ring (this looks to me like

Hello, I am having a problem where code that plots lines using a different data frame plots bars with the current data frame (I am intended to plot lines). The code specifies lines (see below), so I can't figure out why the results are bars. I suspect that it may have something to do with the fact that in the data frame where the code worked as intended, the both variables specifying

I could do this in various hacky ways, but what's the right way? I have a nice application of the by function, which does what I want. The output looks like this: > auc_stress lab.samples.stress$subid: 2 cortisol amylase 1 919.05 6834.8 ---------------------------------------------------------------------------------------------------------------------------

Greetings, Is it possible to match several columns in a merge statement? Here is my problem: data1 looks like this... SUBID TARGID ITEM RATING 1 1 1 4 1 1 2 5 1 1 3 3 1 1 4 2 1 1 5 5 ...... SUBID is the ID for the raters, TARGID is the ID for the targets being rated, ITEM ranges from 1 to 64 crossed

I have another question about drawing samples from a data frame. This might sound really tricky. Let me use a data frame I have posted earlier as an example: SubID CSE1 CSE2 CSE3 CSE4 WSE1 WSE2 WSE3 WSE4 1 6 5 6 2 6 2 2 4 2 6 4 7 2 6 6 2 3 3 5 5 5 5

I wrote some code to do this. It only works with 2 groups (that's all I needed), but could probably be generalized. It got my graph made, and I haven't needed a graph like this one again, so I never went back to really clean it up. It works by first plotting both sets of rectangles, then going back over the ones that had the first bar totally covered by the second. Hope this helps,

I was running a sampling syntax based on a data frame (ago) of 160 rows and 25 columns. Below are the column names: > names(ago) [1] "SubID" "AGR1" "AGR2" "AGR3" "AGR4" "AGR5" "AGR6" "AGR7" "AGR8" [10] "AGR9" "AGR10" "WAGR1" "WAGR2"

Hello, I've been looking through ?phantom and ?expression and this forum for examples of how I might be able to manipulate some of the names that appear on the y-axis of the barplot below. For example, the "gw" in "ECgw" would appear as a subscript...or "qr" would be the theta symbol followed by subscript "r". My attempts haven't even come close

Hi all, I have a large dataset that has >10k entries. The dataset is stored in a dataframe with the headers: SubID Condition1 Condition2 Result1 Result2 There are multiple entries for a given SubID(Subject ID). Condition 1 has 3 levels and condition2 has 2 levels (therefore there are 6 possible combinations all together e.g. Cond1 Level1 x Cond2 Level 1 etc.) and i need to compute for 1. The

Dear R-users, I have written the following code to generate some trellis plots. It works perfectly fine except that it is quite slow when it is apply to my typical datasets (over several thousands of lines). I believe the problem comes from the loops I am using to subset my data.frame. I read in the archives that the tapply function is often more efficient than a loop in R. Unfortunately ,

This patch series introduces a backend for kvm to run on IBM System z machines that uses the mainframe's sie virtualization capability. This work runs 64bit guests on z800/z890/z900/z990/z9/z10 class machines with a 64bit linux host. Userspace will follow once we're done brushing it over. The patch queue consists of the following patches, which can be applied in sequence on top of kvm.git

This patch series introduces a backend for kvm to run on IBM System z machines that uses the mainframe's sie virtualization capability. This work runs 64bit guests on z800/z890/z900/z990/z9/z10 class machines with a 64bit linux host. Userspace will follow once we're done brushing it over. The patch queue consists of the following patches, which can be applied in sequence on top of kvm.git

Hi, You may try: dat1 <- structure(list(SubID = 1:8, CSE1 = c(6L, 6L, 5L, 5L, 5L, 5L, 3L, 3L), CSE2 = c(5L, 4L, 5L, 4L, 6L, 4L, 6L, 6L), CSE3 = c(6L, 7L, 5L, 3L, 7L, 3L, 6L, 6L), CSE4 = c(2L, 2L, 5L, 4L, 5L, 6L, 3L, 3L), WSE1 = c(6L, 6L, 5L, 4L, 6L, 4L, 6L, 6L), WSE2 = c(2L, 6L, 5L, 4L, 4L, 3L, 5L, 5L), WSE3 = c(2L, 2L, 4L, 5L, 4L, 7L, 2L, 4L), WSE4 = c(4L, 3L, 5L, 2L, 1L, 3L, 1L, 7L)),