similar to: 3d matrix * 1d matrix question

Dear R-users, I am working on a problem that I am currently not able to solve efficiently. It is about multiplying one column of a matrix with only a certain number of rows of another matrix. Let me illustrate my problem with an example: n.obs = 800 n.rowsperobs = 300 n.param = 23 Designmat = matrix(rnorm(n.obs*n.rowsperobs*n.param),ncol=n.param) Betamat =

Dear R helpers Suppose x  <- c(1:3) y  <- matrix(1:12, ncol = 3, nrow = 4) > y      [,1] [,2] [,3] [1,]    1    5    9 [2,]    2    6   10 [3,]    3    7   11 [4,]    4    8   12 I wish to multiply 1st column of y by first element of x i.e. 1, 2nd column of y by 2nd element of x i.e. 2 an so on. Thus the resultant matrix should be like > z      [,1]   [,2]    [,3] [1,]    1   

is there a way to do element-by-element multiplication as in Gauss and MATLAB, as shown below? Thanks. --- a 1.0000000 2.0000000 3.0000000 x 1.0000000 2.0000000 3.0000000 2.0000000 4.0000000 6.0000000 3.0000000 6.0000000 9.0000000 a.*x 1.0000000 2.0000000 3.0000000 4.0000000

I am trying to multiply a 3D array of 4x4x4 by the 4 3D arrays of a 4D array with dimensions 4x4x4x4 (the last dimension being the one that I want to split by). (4x4x4 array) > hiaAry , , a1 i1 i2 i3 i4 h1 9.5936098 6.001040 0.08772 0.3138600 h2 1.2003500 1.454570 2.79248 0.0000000 h3 0.1346500 0.201220 0.39256 0.5464000 h4 0.0109000 0.012270 0.16417 0.2766900 ,

I don't think the global fast math flag should override the NoContraction decoration as that's mostly the point of that decoration to begin with, to have fine granular control while still having a broad sweeping optimization. Did I miss your point? I feel like I did. On Thu, Aug 23, 2018, 3:42 PM Michael Berg <michael_c_berg at apple.com> wrote: > Ryan, > > Given that the

I have a big matrix 'ret'. I want to multiply each row of it with a 2nd vector 'pos', resulting result, I want to save in a vector named 'port'. I wrote following code: > pos [1] 2593419 2130220 6198197 1673888 1980000 1784732 2052120 -7490228 -5275000 > dim(ret) [1] 500 9 > fu # user defined function function(x) { fu = x %*%

I am having a hard time understanding just what 'sweep' does. The documentation states: Return an array obtained from an input array by sweeping out a summary statistic. So what does it mean "weeping out a summary statistic"? Thank you. Kevin

Say I have two matrixes: one is 8x28 and other 8x8 I'd like to multiply, for example, first and second column from the 8x8 and plant them in first column of 8x28. Then take first and third of 8x8 and plant into second column of 8x28.etc. Any ideas? Thanks! [[alternative HTML version deleted]]

I am sure there is a simple solution to this... I have a column in a data frame specifying a grouping (1, -1) for my observations, and need to mutliply each observation in all the other columns of the data frame by the corresponding value in the given column. I played with apply, and saw some suggestions for sweep, but did not manage to get it working. My table contains NAs.... Example of

Hi Ryan, In this case there already is an implementation for this, it's just hard to find being in the internals of the LoopVR pass. I'm planning to pull the multiply and udiv support out of there. Your patch looks good but beyond what Dan mentioned you have a bug calculating NewUpper: the constant ranges are half-open intervals where "[5, 10)" includes the value 9 but not

Nicolai, Can you do without the use of -fp-contract=fast (Options.AllowFPOpFusion == FPOpFusion::Fast ) and without Unsafe? As I SPIR-V’s usage of NoContraction flies in the face of both. If so, you should be able to get what you want, as then you are down to just IR flags. You will need a model to generate the correct behavior though in your SPIR-V implementation wrt IR flag emissions.

Hi Jonas, > my target handles operands of multiplying instructions differently based on > signedness. since the result of a multiply doesn't depend on the signedness, I find it strange that your target differentiates between them. What I'm saying is that if you have (say) two i32 numbers a and b and you do a signed multiply: c = a *s b and an unsigned multiply d = a *u b

Thank You, It means vmovdqa64 zmm22, zmmword ptr [rip + .LCPI0_0] # zmm22 = [8,9,10,11,12,13,14,15] zmm22 will contain 64 bit constant values which are indexes here zmm22=8, 9, 10, 11, 12,13,14,15. not the values loaded from these locations. and zmm2 contains constant 4000. so, vpmuludq zmm14, zmm10, zmm2 ; will multiply the indexes values with 4000, as for array b the stride is 4000. zmm14=

This is very strange: I want compute the following in R: g = B/D * solve(A) where B and D are quadratics so they are just a scalar number, e.g. B=t(a) %*% F %*% a; I want to multiply B/D to A^(-1), but R just does not allow me to do that and it keeps complaining that "nonconformable array, etc." I tried the following two tricks and they worked: as.numeric(B/D) * solve(A)

Suppose x <- array(c(1,1,1,1,2,2,2,2), dim = c(2,2,2)) y <- c(5, 10) Now I would like to multiply x[, , 1] with y[1] and x[, , 2] with y[2]. Possible solution is a for-loop: for (i in 1:2) { x[, , i] * y[i] } Another possible solution is this construction: as.vector(t(replicate(nrow(x) * ncol(x), y))) * x I find that these two solutions have a relatively large computation

I've looked at the code for matrix multiplies in R, and found that it can speeded up quite a bit, for multiplies that are really vector dot products, and for other multiplies in which the result matrix is small. Here's my test program: u <- seq(0,1,length=1000) v <- seq(0,2,length=1000) A2 <- matrix(2.1,2,1000) A5 <- matrix(2.1,5,1000) B3 <- matrix(3.2,1000,3) A4 <-

Hi all, I'm learning R. I'm used to Matlab and am having the following issue: I define a column vector and matrix and then multiply them. The result is not what I expect: v2 <- c(0,1,0) M <- cbind(c(1,4,7),c(2,5,8),c(3,6,9)) M*v2 [,1] [,2] [,3] [1,] 0 0 0 [2,] 4 5 6 [3,] 0 0 0 I expect the result to be a column, specifically the 2nd column of M.

Hi, I have a vector and a list, with data I would like to multiply together. So for instance I have a vector s: [[1]] [1] 44308 [[2]] [1] 4371 Also, I have a list d: [[1]] [1] 1201 6170 2036 2927 1625 1391 2074 1453 3172 3027 4691 3719 1185 320 2071 1027 1046 1186 1403 580 1382 440 8 174 [[2]] [1] 6521 688 2678 3409 3033 1608 3618 1461 1836 2104 879 1095 2630 1591 2986 703 2548

Hi, I've got an array, say with i,jth entry = A_ij, and a vector, say with jth entry= v_j. I would like to multiply each column of the array by the corresponding vector component, i,e. find the array with i,jth entry A_ij * v_j This seems so basic but I can't figure out how to do it without a loop. Any suggestions? Michal.

Hi Tomas, Can you share the full code for your benchmark, compiler options, and performance results so that I can try to reproduce them? There are a lot of variables that can affect the results. Private email is fine if it is too much for the mailing list. I am measuring on Knight's Landing (KNL) that was released in November. KNL is not a co-processor so no offload is necessary. R executes