similar to: Error in Rolling window of function - rollapply

Hello, I am trying to emulate the "stack" as like on x86 when using push/pop so afterwards I can use LLVM's optimizer passes to simplify (reduce junk) the code. The LLVM IR code: define { i32, i32, i32 } @test(i32 %foo, i32 %bar, i32 %sp) { ; push foo (On "stack") %sp_1 = sub i32 %sp, 4 %sp_1_ptr = inttoptr i32 %sp_1 to i32* store i32 %foo, i32* %sp_1_ptr, align

Thank you for the hint. I adjusted the code and it works: The code after replacing inttoptr with getelementptr: define { i32, i32, i8* } @test(i32 %foo, i32 %bar, i8* %sp) { entry: ; push foo (On "stack") %sp_1 = getelementptr i8, i8* %sp, i32 -4 %sp_1_ptr = bitcast i8* %sp_1 to i32* store i32 %foo, i32* %sp_1_ptr, align 4 ; push bar %sp_2 = getelementptr i8, i8* %sp_1,

Thanks for the answers. Although I am not sure if I've understood the docs about how inttoptr/ptrtointr are different when compared to gep. It says: "It’s invalid to take a GEP from one object, address into a different separately allocated object, and dereference it.". To go back to my intention why I am doing this, I would like to "emulate" some x86 instructions with

Hi again, So I finally gave up on trying to get through the converting (x86' push pop mov add) because it deals a lot with crazy pointer arithmetics and sonce inttoptr and ptrtoint doesn't provide any alias analysis information. Daniel, you said it doesn't make much sense to provide it but in my cases it is actually very much needed, you didn't say it wasn't possible to

Hello, I am currently trying to translate some custom IR to LLVM-IR and came across and issue. The custom IR has several registers and I am basically try to SSAfy it so it can be easily translated/converted to LLVM-IR. The problem: Since in my custom IR I can reassign every register I have to reassign every new expression with a new llvm Value. But my IR has something like this: REG A = VAR C

I want to keep the translation short and simple (My IR doesn't have control flow so it's basically on basic block) that's why I don't want to rely on alloca/load/store. 2016-02-08 6:08 GMT+01:00 George Burgess IV <george.burgess.iv at gmail.com>: > Hi! > > I don't know what "the right way" to do this is, but is there any reason > you're against

Hi, I faced with problem when start using function - rollapply(returns, 3 , mean) Error in UseMethod("rollapply") : No suitable Method for "rollaply" How can I fix the problem? Thank you for help. -- Best regards, Andy Fetsun [[alternative HTML version deleted]]

Hi everyone, I have a rollapply statement that applies a function, in steps, over a data matrix as follows: #Code start testm<-rollapply(mat, 100, by=100, min, na.rm=F) #Code end This moves down matrix 'mat' and calculates the minimum value over a 100 row range, every 100 rows (i.e. no overlaps). NAs are not removed. I want to modify this statement somehow so that the rollapply()

Hi all- Thank you for reading my post. Please bear in mind that I'm very much a newbie with R! My question is this: I'm trying to use rollapply() on an irregular time series so I can't simply use the width parameter (I don't think). Rather than last 5 entries, I'd like to rollapply on last 6 months (for example). What would be the proper course of action for this? Thanks!

Hi, Sorry ahead of time for not including data with this question. Using rollapply to calculate mean values for 5 day blocks, I'd use this: Roll5mean <- rollapply(data, 5, mean, by=5, align = c("left")) My question is, can someone tell me how to fill in the days between each of these means with the previously calculated mean? If this doesn't make sense, I will clarify and

Hi. I'm comparing output from rollapply.zoo, as produced by two versions of R and package zoo. I'm illustrating with an example from a R-help posting 'Zoo - bug ???' dated 2010-07-13. My question is not about the first version, or the questions raised in that posting, because the behaviour is as documented. I'm puzzled as to why na.rm no longer is passed to mean, i.e. why

zoo's rollapply() function appears to be extremely useful for plugging in a function on-the-fly to run over a window. With inline, there is a lot more coding and room for error, and the code is less portable because the user has to have R compiling set up or it won't work. However, rollapply() seems to be really slow. Several orders of magnitude slower than inline, in fact. I don't

Hi I would like to understand how to extend the function (FUN) I am using in rollapply below. ###################################### With the following simplified data, test1 yields parameters for a rolling regression data = data.frame(Xvar=c(70.67,70.54,69.87,69.51,70.69,72.66,72.65,73.36), Yvar =c(78.01,77.07,77.35,76.72,77.49,78.70,77.78,79.58)) data.z = zoo(d) test1 =

Hello I have a vector a =(-2,0,0,0,1,0,0,3,0,0,-4) I want to replace all zeros into previous non-zero state. So for instance the above vector should be converted into: a= (-2,-2,-2,-2,1,1,1,3,3,3,-4) I tried many things and finally concluded that probably(?) rollapply may be the best way? I tried f= function(x){ ifelse(x==0,Lag(x),x) } And then, rollappy(a,1,f) and that

Dear R users. I have zoo object "size_june" containing market-capital values: > dim(size_june) # market-cap data of 625 firms for 20 years [1] 20 625 > class(size_june) [1] "zoo" > size_june # colnames = "size.firmcode" size.34020 size.4710 size.11050 size.10660 size.9540 size.8060 size.16160 size.8080 size.9280 1988-06-30 NA

Here is a relatively simple script (with comments as to the logic interspersed): # Some of these libraries are probably not needed here, but leaving them in place harms nothing: library(tseries) library(xts) library(quantmod) library(fGarch) library(fTrading) library(ggplot2) # Set the working directory, where the data file is located, and read the raw data

Dear List members I want to do the sliding window analysis of some specific values. Here is my code: require(zoo) dat <- read.table("chr1.txt", header = TRUE, sep="\t") dat2 <- cbind(dat[1,3]) #The first column is also important. It represents the position of the site on the chromosome. TS <- zoo(c(dat2)) a <- rollapply(TS, width=1000000, by=200000, FUN=mean,

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I

Hi, I'm trying to figure out common approach on calculating MA on a dataset that contains column "time". After digging around, I believe functions rollmean and rollaply should be used. However I don't quite understand the requirements for the underlying data. Should it be zoo object type? Formatted in a special way? As an example, I'm looking to get calculated

#using "rollapply" to calculate a moving sum or running sum? #I am tryign to use rollapply to calcualte a moving sum? #I tried rollapply and get the error message #"Error in seq.default(start.at, NROW(data), by = by) : # wrong sign in 'by' argument" #example: mymatrix <- ( matrix(data=1:100, nrow=5, ncol=20) ) mymatrix_cumsum <- ( matrix(data=NA, nrow=5,