similar to: [RFC] bitfield access shrinking

On Thu, Mar 9, 2017 at 10:54 AM, Hal Finkel <hfinkel at anl.gov> wrote: > On 03/09/2017 12:14 PM, Wei Mi via llvm-dev wrote: >> >> In >> http://lists.llvm.org/pipermail/cfe-commits/Week-of-Mon-20120827/063200.html, >> consecutive bitfields are wrapped as a group and represented as a >> large integer and emits loads stores and bit operations appropriate

On 03/09/2017 12:28 PM, Krzysztof Parzyszek via llvm-dev wrote: > We could add intrinsics to extract/insert a bitfield, which would > simplify a lot of that bitwise logic. But then you need to teach a bunch of places about how to simply them, fold using bitwise logic and other things that reduce demanded bits into them, etc. This seems like a difficult tradeoff. -Hal > >

Good evening I often have as output from simulations a list of various values, vectors and matrices. Supposing that I then run said simulation several times, I often want to extract a particular result from each simulation for plotting and, ideally, put it in a matrix. A simple example v1 <- 1:5 v2 <- 6:10 other1 <- "stuff" other2 <- "stuff" set1 <-

Dear R users, I am working on allocating the rows within a dataframe into some factor levels.Consider the following dataframe: Start.action Start.time 1 Start.setting 2010-12-30 17:58:00 2 Start.setting 2010-12-30 18:40:00 3 Start.setting 2010-12-31 22:39:00 4 Start.setting 2010-12-31 23:24:00 5

Colleagues, (R: 2.13.0; OS X) I often receive sequential datasets in which there are new rows interposed between existing rows. For example: SET1 <- data.frame(list(LETTERS=LETTERS[c(1:4, 6:10)], NUMBERS=c(1:4, 6:10))) SET2 <- data.frame(list(LETTERS=LETTERS[1:10], NUMBERS=1:10)) > SET1 LETTERS NUMBERS 1 A 1 2 B 2 3 C 3 4 D 4 5

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Hello! I need to compare 2 datasets whether they come from the same distribution. I use function ks.boot{Matching}. And what is the confidence level of the p-value, returned by ks.boot function? The code is: set=read.table("http://stella.sai.msu.ru:8080/~gala/data/testsets.csv", header=T,sep=',') set1=set[!is.na(set$set1),'set1']

Dear friends, I have a data set with 23 columns and 38000 rows. It is a panel running from the years 1991 through 2005. I want to aggregate the data and get the medians of each of the 23 columns for each of the years. In other words my output should be like this Year Median 1991 123 1992 145 1993 132 etc. The sample lines of code to do this operation is set1 <-

I have encountered this problem on several occasions and am not sure how to handle it. I use for-loops to cycle through datasets. When each dataset is of equal length, it works fine as I can combine the datasets and have each loop pick up a different column, but when the datasets are differing lengths, I am struggling. Here is an example: A<-1:10 B<-1:15 C<-1:18

Hello, I've been clustering my data using hclust and cutting the resulting tree with cutree. Separately, I visualize the clusterings with heatmap. Is it possible to have the dendrogram on the heatmap reflect the cutree results? That is, instead of having one large dendrogram, it would have 4 or 25 in the example below. Any guidance on if that's possible or not, and what kinds of

Hi all, Suppose that I've two data frames, a and b say, both containing a column 'id'. While data frame 'a' contains multiple rows sharing the same id, data frame 'b' contains just one entry per id (i.e. a 1 to n relationship). For the ease of modeling I now want to generate a new data frame c, which is basically a copy of data frame 'a' augmented by the values

Dear list, I have two martix like these, each rows with name in the matrix. I try to select rows with identical name from two matrix and calculate their correlation. Matrix1: 2-Sep 9 5.5 1 7.18 10.0 8 139.45 2-Sep 7 4.9 15 8.22 61.68 9 123.62 4-Sep 5-Sep AAMP A2M A2M . . . Matrix2: 2-Sep 4 7 1 6.8 12 8 19.4

Hi, This question should be simple to answer. I am a new R user. I have a data.frame called appended. I would like to break it into 7 smaller datasets based on the value of a categorical variable dp (which has values 1:7). I would like to name the smaller datasets set1, set2, set3,....,set7. I don't know how to refer to the variable in the for loop, when naming the output datasets. In STATA

Hello, I am a new R -user and request your help for the following problem. I need to merge two dataset of longitudinal study which has two column (id and respose) common. when I used merge option to join the datas side be side, because of the repeated subject id, I got larger data set which is not accurate. I would like to connect twi data sets by id and response in such a way that data are

I would like to create 15 box plots from two sets of data. Set1 - containts PayGrade, Min_Salary, Max_Salary data for 15 pay grades Set2 - contains PayGrade, Actual_Min, Actual_Max, and Actual_Mean for the 15 pay grades I would like 15 box plots (one for each paygrade) whose whiskers were the Min_Salary and Max_Salary data and whose ''box'' was Actual_Min, Actual_Mean,

Hi Mats, It's private backend. I will try describing what I am dealing with. struct S { unsigned int a : 8; unsigned int b : 8; unsigned int c : 8; unsigned int d : 8; unsigned int e; } We want to read S->b for example. The size of struct S is 64 bits, and seems LLVM treats it as i64. Below is the IR corresponding to S->b, IIRC. %0 = load

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

All, I'm sure that this is covered somewhere, but I can't seem to find a good explanation. I have an existing table that contains information grouped by date. This is as so: Day NumberOfCustomers NumberOfComplaints 20060512 10040 40 20060513 32420 11 ... I also have a table at the detail level as so: Day Meal PricePaid UsedCupon 20060512 Fish 14 Y 20060512 Chicken 20 N

Dear all, I have a (probably very basic) question. I am imputing data with the mice package, using 10 chains. I can then write out the 10 final values of the chains simply by name1 <- complete(imp, 1) : : name10 <- complete(imp,10) Not a big deal, I just wanted to do that in a little loop as follows: for (i in 1:10){ set[i] <-

In a code segment of my pass plugin, I try to gather AliasSets for all StoreInst, LoadInst and CallInst instructions in a function. Some behaviors of the pass puzzled me. Below is the *.ll of the test program which I run the pass on, it was get with "llvm-gcc -Wl,--disable-opt" from a rather simple *.c program. ---------------------------------- ; ModuleID = 'ptralias.bc'