From ripley at stats.ox.ac.uk  Sun May 13 11:18:57 2007
From: ripley at stats.ox.ac.uk (Prof Brian Ripley)
Date: Sun, 13 May 2007 10:18:57 +0100 (BST)
Subject: [Rd] Implicit vs explicit printing and the call stack
In-Reply-To: <f8e6ff050705120736q754367d9nef4a488c6fa53a03@mail.gmail.com>
References: <f8e6ff050705120736q754367d9nef4a488c6fa53a03@mail.gmail.com>
Message-ID: <Pine.LNX.4.64.0705130939060.1927@gannet.stats.ox.ac.uk>

First, it was not clear that you are talking about the output of 
traceback(), which is _a representation of_ the call stack and depends on 
the details of deparsing.

Second, the difference is I believe not implicit vs explicit printing, but 
of printing an evaluated object vs printing a call.  What your subject 
line would correspond to is

x <- ggplot(mtcars, aes(x = cyl, y = -mpg)) + scale_y_log10() + geom_point()
x vs print(x)

I can't demonstrate (what is aes?), but I expect that would show minimal 
differences.

The issue seems to be whether arguments have been evaluated, and if so 
whether they were promises.  Promises can be deparsed back to the symbolic 
representation rather than to their value.  When you call print explicitly 
_on the ggplot call_, you have promises to arguments (to support lazy 
evaluation).  As far as I know (this is a detail of your code), the object 
ggplot returns has evaluated 'mtcars' and contains the value and not the 
promise, hence the difference in the deparsing of the call stack.

You chose to call traceback() without 'max.lines', and the answer would 
seem to be

1) don't use a buggy print method,
2) if you have to (to fix it), use 'max.lines' or do this in two steps.

If you want your end users to see a nicer representation, reconsider what 
you actually return in your object.


On Sat, 12 May 2007, hadley wickham wrote:

> Hi everyone,
>
> I've run into a bit of strange problem with implicit vs explicit
> printing and the call stack. I've included an example at the bottom of
> this email.  The basic problem is that I have an S3 object with a
> print method.  When the object is implicitly printed (ie. typed
> directly into the console) the function arguments in the call stack
> are exploded out to their actual values, rather than just the name I
> typed in (see below for an example if my language is confusing).  When
> I explicitly "print" the object, the call stack is fine.
>
> This is not just of academic interest, because with a larger dataset
> and an implicit print, there is a noticeable delay before control
> returns to the prompt  (I can't quantify it exactly because
> system.time requires a explicit print, but it's on the order of a few
> seconds).
>
> I'm not sure if I've provided enough information to be able to solve
> the problem, so please let me know what additional details would be
> useful.
>
> Thanks,
>
> Hadley
>
>
>> ggplot(mtcars, aes(x=cyl, y=-mpg)) + scale_y_log10() + geom_point()
> Error in grid.pretty(.$domain()) : infinite axis extents [GEPretty(-inf,inf,5)]
> In addition: Warning messages:
> 1: NaNs produced in: log(x, base)
> 2: no non-missing arguments to min; returning Inf
> 3: no non-missing arguments to max; returning -Inf
> 4: no non-missing arguments to min; returning Inf
> 5: no non-missing arguments to max; returning -Inf
>> traceback()
> 16: .Call(L_pretty, range)
> 15: grid.pretty(.$domain())
> 14: get("breaks", env = .$y(), inherits = TRUE)(.$y(), ...)
> 13: .$y()$breaks()
> 12: range(at)
> 11: as.numeric(x)
> 10: unit(range(at), "native")
> 9: ggaxis_line(at, position)
> 8: ggaxis(.$y()$breaks(), .$y()$labels(), "left", range$y)
> 7: get("guide_axes", env = coordinates, inherits = TRUE)(coordinates,
>       ...)
> 6: coordinates$guide_axes()
> 5: guides_basic(plot, scales, cs)
> 4: ggplot_plot(x, ...)
> 3: grid.draw(ggplot_plot(x, ...))
> 2: print.ggplot(list(data = list(mpg = c(21, 21, 22.8, 21.4, 18.7,
>   18.1, 14.3, 24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4,
>   14.7, 32.4, 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26,
>   30.4, 15.8, 19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4,
>   4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8,
>   6, 8, 4), disp = c(160, 160, 108, 258, 360, 225, 360, 146.7,
>   140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7,
>   75.7, 71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351,
>   145, 301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62,
>   95, 123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,
>   150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,
>   3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 3.07,
>   3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76, 3.15,
>   3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11), wt = c(2.62,
>   2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19, 3.15, 3.44, 3.44,
>   4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2, 1.615, 1.835, 2.465,
>   3.52, 3.435, 3.84, 3.845, 1.935, 2.14, 1.513, 3.17, 2.77, 3.57,
>   2.78), qsec = c(16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84,
>   20, 22.9, 18.3, 18.9, 17.4, 17.6, 18, 17.98, 17.82, 17.42, 19.47,
>   18.52, 19.9, 20.01, 16.87, 17.3, 15.41, 17.05, 18.9, 16.7, 16.9,
>   14.5, 15.5, 14.6, 18.6), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1,
>   1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
>   1), am = c(1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>   1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4,
>   4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,
>   3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4, 2,
>   2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4,
>   6, 8, 2)), layers = list(<environment>), scales = <environment>,
>       defaults = list(x = cyl, y = -mpg), title = NULL, fixedaspect = FALSE,
>       coordinates = <environment>, formula = ". ~ .", margins = FALSE))
> 1: print(list(data = list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1,
>   14.3, 24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7,
>   32.4, 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4,
>   15.8, 19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6,
>   6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8,
>   4), disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,
>   167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,
>   71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145, 301,
>   121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123,
>   180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 150, 245,
>   175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9, 3.9, 3.85,
>   3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 3.07, 3.07, 3.07,
>   2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76, 3.15, 3.73, 3.08,
>   4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11), wt = c(2.62, 2.875,
>   2.32, 3.215, 3.44, 3.46, 3.57, 3.19, 3.15, 3.44, 3.44, 4.07,
>   3.73, 3.78, 5.25, 5.424, 5.345, 2.2, 1.615, 1.835, 2.465, 3.52,
>   3.435, 3.84, 3.845, 1.935, 2.14, 1.513, 3.17, 2.77, 3.57, 2.78
>   ), qsec = c(16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84,
>   20, 22.9, 18.3, 18.9, 17.4, 17.6, 18, 17.98, 17.82, 17.42, 19.47,
>   18.52, 19.9, 20.01, 16.87, 17.3, 15.41, 17.05, 18.9, 16.7, 16.9,
>   14.5, 15.5, 14.6, 18.6), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1,
>   1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
>   1), am = c(1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>   1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4,
>   4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,
>   3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4, 2,
>   2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4,
>   6, 8, 2)), layers = list(<environment>), scales = <environment>,
>       defaults = list(x = cyl, y = -mpg), title = NULL, fixedaspect = FALSE,
>       coordinates = <environment>, formula = ". ~ .", margins = FALSE))
>> print(ggplot(mtcars, aes(x=cyl, y=-mpg)) + scale_y_log10() + geom_point())
> Error in grid.pretty(.$domain()) : infinite axis extents [GEPretty(-inf,inf,5)]
> In addition: Warning messages:
> 1: NaNs produced in: log(x, base)
> 2: no non-missing arguments to min; returning Inf
> 3: no non-missing arguments to max; returning -Inf
> 4: no non-missing arguments to min; returning Inf
> 5: no non-missing arguments to max; returning -Inf
>> traceback()
> 16: .Call(L_pretty, range)
> 15: grid.pretty(.$domain())
> 14: get("breaks", env = .$y(), inherits = TRUE)(.$y(), ...)
> 13: .$y()$breaks()
> 12: range(at)
> 11: as.numeric(x)
> 10: unit(range(at), "native")
> 9: ggaxis_line(at, position)
> 8: ggaxis(.$y()$breaks(), .$y()$labels(), "left", range$y)
> 7: get("guide_axes", env = coordinates, inherits = TRUE)(coordinates,
>       ...)
> 6: coordinates$guide_axes()
> 5: guides_basic(plot, scales, cs)
> 4: ggplot_plot(x, ...)
> 3: grid.draw(ggplot_plot(x, ...))
> 2: print.ggplot(ggplot(mtcars, aes(x = cyl, y = -mpg)) + scale_y_log10() +
>       geom_point())
> 1: print(ggplot(mtcars, aes(x = cyl, y = -mpg)) + scale_y_log10() +
>       geom_point())
>
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>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



[Rd] Implicit vs explicit printing and the call stack
Prof Brian Ripley