Inspect the return value of a method
Source:R/workflows-inspect.R
, R/aliases.R
ggtrace_inspect_return.Rd
Inspect the return value of a method
Usage
ggtrace_inspect_return(x, method, cond = 1L, ..., error = FALSE)
inspect_return(x, method, cond = 1L, ..., error = FALSE)
Arguments
- x
A ggplot object
- method
A function or a ggproto method. The ggproto method may be specified using any of the following forms:
ggproto$method
namespace::ggproto$method
namespace:::ggproto$method
- cond
When the return value should be inspected. Defaults to
1L
.- ...
Unused.
- error
If
TRUE
, continues inspecting the method until the ggplot errors. This is useful for debugging but note that it can sometimes return incomplete output.
Tracing context
When quoted expressions are passed to the cond
or value
argument of
workflow functions they are evaluated in a special environment which
we call the "tracing context".
The tracing context is "data-masked" (see rlang::eval_tidy()
), and exposes
an internal variable called ._counter_
which increments every time a
function/method has been called by the ggplot object supplied to the x
argument of workflow functions. For example, cond = quote(._counter_ == 1L)
is evaluated as TRUE
when the method is called for the first time. The
cond
argument also supports numeric shorthands like cond = 1L
which evaluates to
quote(._counter_ == 1L)
, and this is the default value of cond
for
all workflow functions that only return one value (e.g., ggtrace_capture_fn()
).
It is recommended to consult the output of ggtrace_inspect_n()
and
ggtrace_inspect_which()
to construct expressions that condition on ._counter_
.
For highjack functions like ggtrace_highjack_return()
, the value about to
be returned by the function/method can be accessed with returnValue()
in the
value
argument. By default, value
is set to quote(returnValue())
which
simply evaluates to the return value, but directly computing on returnValue()
to
derive a different return value for the function/method is also possible.
Examples
library(ggplot2)
p1 <- ggplot(diamonds, aes(cut)) +
geom_bar(aes(fill = cut)) +
facet_wrap(~ clarity)
p1
# Return value of `Stat$compute_panel` for the first panel
ggtrace_inspect_return(x = p1, method = Stat$compute_panel)
#> count prop x width flipped_aes fill PANEL group
#> 1 210 1 1 0.9 FALSE Fair 1 1
#> 2 96 1 2 0.9 FALSE Good 1 2
#> 3 84 1 3 0.9 FALSE Very Good 1 3
#> 4 205 1 4 0.9 FALSE Premium 1 4
#> 5 146 1 5 0.9 FALSE Ideal 1 5
# Return value for 4th panel
ggtrace_inspect_return(x = p1, method = Stat$compute_panel,
cond = 4L)
#> count prop x width flipped_aes fill PANEL group
#> 1 261 1 1 0.9 FALSE Fair 4 1
#> 2 978 1 2 0.9 FALSE Good 4 2
#> 3 2591 1 3 0.9 FALSE Very Good 4 3
#> 4 3357 1 4 0.9 FALSE Premium 4 4
#> 5 5071 1 5 0.9 FALSE Ideal 4 5
# Return value for 4th panel, 2nd group (bar)
ggtrace_inspect_return(
x = p1, method = StatCount$compute_group,
cond = quote(data$PANEL[1] == 4 && data$group[1] == 2)
)
#> count prop x width flipped_aes
#> 1 978 1 2 0.9 FALSE