Agree that sweep is the tool here. (If you think it is clunky, check how more
general array-sweep operations can be done in Matlab.)
However, it isn't really true that sweep isn't moving things around. Notice
the call to aperm() at the end of the code for sweep():
perm <- c(MARGIN, seq_along(dims)[-MARGIN])
FUN(x, aperm(array(STATS, dims[perm]), order(perm)), ...)
What this essentially does for "our" case is
> rbind(1:3,4:6)/t(matrix(c(2,3,4), 3,2))
[,1] [,2] [,3]
[1,] 0.5 0.6666667 0.75
[2,] 2.0 1.6666667 1.50
I.e. take the matrix, create the divisor by replicating STATS to form a matrix
of same size. This is easier if the MARGIN indices come first, because the
recycling works. So you get the 2x3 matrix by filling a 3x2 and then
transposing it (aperm() does this more generally). Finally, just call FUN on
the two arrays.
-pd
> On 27 Feb 2024, at 22:51 , Jeff Newmiller via R-help <r-help@r-project.org>
> wrote:
>
> Why anything but sweep?
>
> The fundamental data type in Matlab is a matrix... they don't have vectors,
> they have Nx1 matrices and 1xM matrices.
>
> Vectors don't have any concept of "row" vs. "column". Straight division is
> always elementwise with recycling as needed, and matrices are really vectors
> in row-major order:
>
> 1 2 3
> 4 5 6
>
> is really
>
> 1 4 2 5 3 6
>
> and when you do straight division NN / lambda then lambda is repeated:
>
> 1 4 2 5 3 6
> 2 3 4 2 3 4
>
> to get
>
> 0.5 1.3 0.5 2.5 1.0 1.5
>
> but if you transpose first
>
> 1 4
> 2 5
> 3 6
>
> then that corresponds to an underlying vector:
>
> 1 2 3 4 5 6
>
> which lines up with lambda in t(NN)/lambda as:
>
> 1 2 3 4 5 6
> 2 3 4 2 3 4
>
> to obtain:
>
> 0.50 0.67 0.75 2.0 1.67 1.50
>
> and inherits the dimensions of t(NN):
>
> 0.50 2.00
> 0.67 1.67
> 0.75 1.50
>
> which can be transposed back as in t( t( NN ) / lambda ):
>
> 0.50 0.67 0.75
> 2.00 1.67 1.50
>
> but that requires a lot of moving elements around while sweep does not.
>
> Operators are not necessarily "better" than named functions... they just look
> different.
>
>
> On February 27, 2024 11:54:26 AM PST, Evan Cooch <evan.co...@gmail.com> wrote:
>> So, trying to convert a very long, somewhat technical bit of lin alg
>> MATLAB code to R. Most of it working, but raninto a stumbling block that
>> is probaably simple enough for someone to explain.
>>
>> Basically, trying to 'line up' MATLAB results from an element-wise
>> division of a matrix by a vector with R output.
>>
>> Here is a simplified version of the MATLAB code I'm translating:
>>
>> NN = [1, 2, 3; 4, 5, 6]; % Example matrix
>> lambda = [2, 3, 4]; % Example vector
>> result_matlab = NN ./ lambda;
>>
>> which yields
>>
>> 0.50000 0.66667 0.75000
>> 2.00000 1.66667 1.50000
>>
>>
>> So, the only way I have stumbled onto in R to generate the same results
>> is to use 'sweep'. The following 'works', but I'm hoping someone can
>> explain why I need something as convoluted as this seems (to me, at least).
>>
>> NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix
>> lambda <- c(2, 3, 4) # Example vector
>> sweep(NN, 2, lambda, "/")
>>
>>
>> [,1] [,2] [,3]
>> [1,] 0.5 0.6666667 0.75
>> [2,] 2.0 1.6666667 1.50
>>
>> First tried the more 'obvious' NN/lambda, but that yields 'the wrong
>> answer' (based solely on what I'm trying to accomplish):
>>
>>
>> [,1] [,2] [,3]
>> [1,] 0.500000 0.5 1.0
>> [2,] 1.333333 2.5 1.5
>>
>> So, why 'sweep'?
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> --
> Sent from my phone. Please excuse my brevity.
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd....@cbs.dk Priv: pda...@gmail.com
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
