From maechler at stat.math.ethz.ch  Mon Feb 29 19:01:58 2016
From: maechler at stat.math.ethz.ch (Martin Maechler)
Date: Mon, 29 Feb 2016 19:01:58 +0100
Subject: [Rd] [patch] Support many columns in model.matrix
In-Reply-To: <CABz6aZdZvLr=3_8yOqPr+_HYu-Vi=XQD5vKc8zATt0pFMUtypQ@mail.gmail.com>
References: <CABz6aZdZvLr=3_8yOqPr+_HYu-Vi=XQD5vKc8zATt0pFMUtypQ@mail.gmail.com>
Message-ID: <22228.34710.467047.134759@stat.math.ethz.ch>

>>>>> Karl Millar via R-devel <r-devel at r-project.org>
>>>>>     on Fri, 26 Feb 2016 15:58:20 -0800 writes:

    > Generating a model matrix with very large numbers of
    > columns overflows the stack and/or runs very slowly, due
    > to the implementation of TrimRepeats().

    > This patch modifies it to use Rf_duplicated() to find the
    > duplicates.  This makes the running time linear in the
    > number of columns and eliminates the recursive function
    > calls.

Thank you, Karl.
I've committed this (very slightly modified) to R-devel,

(also after looking for a an example that runs on a non-huge
 computer and shows the difference) :

nF <- 11 ; set.seed(1)
lff <- setNames(replicate(nF, as.factor(rpois(128, 1/4)), simplify=FALSE), letters[1:nF])
str(dd <- as.data.frame(lff)); prod(sapply(dd, nlevels))
## 'data.frame':	128 obs. of  11 variables:
##  $ a: Factor w/ 3 levels "0","1","2": 1 1 1 2 1 2 2 1 1 1 ...
##  $ b: Factor w/ 3 levels "0","1","2": 1 1 1 1 1 1 2 1 1 1 ...
##  $ c: Factor w/ 3 levels "0","1","2": 1 1 1 2 1 1 1 2 1 1 ...
##  $ d: Factor w/ 3 levels "0","1","2": 1 1 2 2 1 2 1 1 2 1 ...
##  $ e: Factor w/ 3 levels "0","1","2": 1 1 1 1 1 1 1 1 2 1 ...
##  $ f: Factor w/ 2 levels "0","1": 2 1 2 1 2 1 1 2 1 2 ...
##  $ g: Factor w/ 4 levels "0","1","2","3": 2 1 1 2 1 3 1 1 1 1 ...
##  $ h: Factor w/ 4 levels "0","1","2","4": 1 1 1 1 2 1 1 1 1 1 ...
##  $ i: Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 2 ...
##  $ j: Factor w/ 3 levels "0","1","2": 1 2 3 1 1 1 1 1 1 1 ...
##  $ k: Factor w/ 3 levels "0","1","2": 1 1 1 1 1 1 1 1 1 1 ...
## 
## [1] 139968

system.time(mff <- model.matrix(~ . ^ 11, dd, contrasts = list(a = "contr.helmert")))
##  user  system elapsed 
## 0.255   0.033   0.287  --- *with* the patch on my desktop (16 GB)
## 1.489   0.031   1.522  --- for R-patched (i.e. w/o the patch)

> dim(mff)
[1]    128 139968
> object.size(mff)
154791504 bytes

---

BTW: These example would gain tremendously if I finally got
     around to provide

   model.matrix(........, sparse = TRUE)

which would then produce a Matrix-package sparse matrix.

Even for this somewhat small case, a sparse matrix is a factor
of 13.5 x smaller :

> s1 <- object.size(mff); s2 <- object.size(M <- Matrix::Matrix(mff)); as.vector( s1/s2 )
[1] 13.47043

I'm happy to collaborate with you on adding such a (C level)
interface to sparse matrices for this case.

Martin Maechler



[Rd] [patch] Support many columns in model.matrix
Martin Maechler