[Rd] bug in plot.table(..., log='y')?

[Martin Maechler]

>>>>> Bill Dunlap 
>>>>>     on Mon, 30 May 2022 09:38:45 -0700 writes:

    > Martin wrote

    > If you have a table with  0  counts  and think you'd prefer
    > log="y" --- something I strongly agree is often a good idea,
    > giving much more useful plots ---

    > I'd consider in this case using the good old
    > log( 1+   y )
    > or log( eps+ y )  trick.


    > One could also sqrt(y), which helps stabilize the variances of count data.

Definitely,  thank you, Bill!

What I mean above (and I think you understood, but probably not
many other readers because I was too terse), 
was of course to use   log="y"  with the "+ eps" trick,
i.e., {in a general situation}

      plot(x, y+eps, log="y")

so the labels show numbers on the y+eps scale, and for smallish
eps, this is visually the same as y-scale - unless you are close to y=0.


    > Making nicely spaced and labelled tick marks for these transformations can
    > be a pain.  Perhaps some package already does this.

    > -Bill

Not used yet, but from documentation, Stahel's 'plgraphics'
package (see bottom below),  does allow "arbitrary" transformation.

For the specific case of table() {or xtable()} results with true counts,
I agree it would be nice to have something like  'sqrt="y"' or
just 'sqrt=TRUE' which would "show" sqrt(<count>) but label the
axis non-equidistantly with counts.

A bit like

   y <- sort(rlnorm(333, 3))
   plot(qnorm(ppoints(y)), y, log="y", yaxt="n")
   sfsmisc::eaxis(2, sub=1)

does for log-transformed.

The simple traditional-graphics    plot(*, log="y") is often
good enough, but I like to see from the ticks that there was a
transformation.

Martin

    > On Mon, May 30, 2022 at 3:41 AM Martin Maechler <maechler using stat.math.ethz.ch>
    > wrote:

    >> >>>>> Spencer Graves
    >> >>>>>     on Sat, 28 May 2022 11:41:49 -0500 writes:
    >> 
    >> > On 5/28/22 11:23 AM, Duncan Murdoch wrote:
    >> >> On 28/05/2022 11:33 a.m., Spencer Graves wrote:
    >> >>> Dear R Developers:
    >> >>>
    >> >>>
    >> >>>       Consider the following example:
    >> >>>
    >> >>>
    >> >>> (tstTable <- table(rep(1:3, 3:1))) plot(tstTable)
    >> >>> plot(tstTable, log='y')
    >> >>>
    >> >>>
    >> >>>       "plot(tstTable)" works as expected.
    >> >>> "plot(tstTable, log='y')" gives a warning:
    >> >>>
    >> >>>
    >> >>> Warning message: In plot.window(...) :     nonfinite
    >> >>> axis=2 limits [GScale(-inf,0.477121,..); log=TRUE] --
    >> >>> corrected now
    >> >>>
    >> >>>
    >> >>>       AND the plot has a y axis scale running from
    >> >>> 1e-307 to 1e+13.
    >> >>>
    >> >>>
    >> >>>       This is with R 4.2.0 (R Console and the current
    >> >>> RStudio) under macOS 11.6.6.
    >> >>>
    >> >>>
    >> >>>       "plot(as.numeric(names(tstTable),
    >> >>> as.numeric(tstTable), log='y'))" works as expected ;-)
    >> >>>
    >> >>>
    >> >>>       Comments?        Thanks for your valuable work in
    >> >>> making it easier for people everywhere to do quality
    >> >>> statistics.
    >> >>
    >> >> The help page ?plot.table says that ylim defaults to c(0,
    >> >> max(x)), i.e.  c(0,3) in your example.  If you're asking
    >> >> to plot that on a log scale, there are bound to be
    >> >> problems.
    >> >>
    >> >> If you specify ylim, e.g. as c(min(tstTable),
    >> >> max(tstTable)), things are fine in your example; they
    >> >> won't be in examples where the min is zero.
    >> >>
    >> >> Duncan Murdoch
    >> 
    >> >     Thanks.  I looked at the help file but didn't read it
    >> > carefully enough.
    >> 
    >> >     Spencer
    >> 
    >> If you have a table with  0  counts  and think you'd prefer
    >> log="y" --- something I strongly agree is often a good idea,
    >> giving much more useful plots ---
    >> 
    >> I'd consider in this case using the good old
    >> log( 1+   y )
    >> or log( eps+ y )  trick.
    >> 
    >> My colleague Werner Stahel has spent quite a bit of effort in
    >> order to make such "log-transformed plots in case of {zero etc}"
    >> plot even smarter and convenient...
    >> and has put this (and many more related ideas of doing smart and
    >> robust good data analysis) in his package 'plgraphics'
    >> (on R-forge, but still not on CRAN unfortunately).
    >> With many thanks to Ian Howson, still nicely available also here:
    >> 
    >> https://rdrr.io/rforge/plgraphics/
    >> 
    >> His generalized  log(1 + y)   is  plgraphics::logst(),
    >> documented on the rdrr mirror here
    >> https://rdrr.io/rforge/plgraphics/man/logst.html
    >> 
    >> Martin