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Compatability with ggplot2 3.6.0 #166

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d0519a0
remove test
teunbrand Jan 30, 2025
5e30828
target adding labs
teunbrand Jan 30, 2025
ef4b3d5
Prioritise `+.gg_tsensemble` method over `+.gg` to resolve Ops conflict
mitchelloharawild Jan 31, 2025
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,7 @@ License: GPL-3
URL: http://feasts.tidyverts.org/, https://github.com/tidyverts/feasts/
BugReports: https://github.com/tidyverts/feasts/issues
Encoding: UTF-8
RoxygenNote: 7.3.2
RoxygenNote: 7.3.2.9000
Roxygen: list(markdown = TRUE, roclets=c('rd', 'collate', 'namespace'))
Language: en-GB
RdMacros: lifecycle
1 change: 1 addition & 0 deletions NAMESPACE
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Expand Up @@ -2,6 +2,7 @@

S3method("+",gg_tsensemble)
S3method(autoplot,tbl_cf)
S3method(chooseOpsMethod,gg_tsensemble)
S3method(components,classical_decomposition)
S3method(components,feasts_x13arimaseats)
S3method(components,stl_decomposition)
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8 changes: 6 additions & 2 deletions R/graphics.R
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Expand Up @@ -728,11 +728,15 @@ gg_tsresiduals <- function(data, type = "innovation", ...){
}

#' @export
`+.gg_tsensemble` <- function(e1, e2){
e1[[1]] <- e1[[1]] + e2
`+.gg_tsensemble` <- function(e1, e2) {
e1[[1L]] <- e1[[1L]] + e2
e1
}

#' @export
chooseOpsMethod.gg_tsensemble <- function(x, y, mx, my, cl, reverse) TRUE


#' @export
print.gg_tsensemble <- function(x, ...){
x <- lapply(x, ggplot2::ggplotGrob)
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9 changes: 1 addition & 8 deletions tests/testthat/test-graphics.R
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Expand Up @@ -189,7 +189,7 @@ test_that("gg_tsdisplay() plots", {
list(x = "index", y = "value")
)

p <- p + ggplot2::labs(x = "x", y = "y", title = "title")
p[[1]] <- p[[1]] + ggplot2::labs(x = "x", y = "y", title = "title")

p_built <- ggplot2::ggplot_build(p[[1]])

Expand Down Expand Up @@ -267,11 +267,4 @@ test_that("gg_arma() plots", {
ggplot2::layer_data(p, 4)$PANEL,
factor(c(rep_along(ar_roots, 1), rep_along(ma_roots, 2)))
)

p_built <- ggplot2::ggplot_build(p)

expect_equivalent(
p_built$plot$labels[c("x", "y")],
list(x = "Re(1/root)", y = "Im(1/root)")
)
Comment on lines -270 to -276
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The expected label is derived from the global mapping of the plot, while ggplot2 now prioritises layers for default mappings (so the path geoms is the one to provide x/y).

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No problem, in this case the code is better updated to return + ggplot2::labs(x = "Re(1/root)", y = "Im(1/root)").

Am I correct in understanding that ggplot(aes(x = mpg, y = hp)) will now return default axis labels of x = "x" and y = "y" rather than x = "mpg" and y = "hp"? Since geom_*() in this case is inheriting from the default ggplot aes(), it feels like a regression that the path geom wouldn't produce the same x/y labels.

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@teunbrand teunbrand Jan 31, 2025 •
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will now return default axis labels

It will be mpg/hp in that case. Essentially it goes over the layers one-by-one and picks up the labels, so the order in which aesthetics are evaluated matters. It ignores the global aesthetics because they only matter when they are inherited by a layer. The relevant issue is tidyverse/ggplot2#5894 if you want to read more.

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@mitchelloharawild mitchelloharawild Jan 31, 2025 •
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Thanks for the reference! I'm not against the change, and I think the relevant issue is well motivated.

It seems there could be an issue with using annotate() and the new automatic layer-based labels (or I misunderstand their intended interaction -- I haven't read the relevant issue closely yet).

Here's an adapted version of gg_arma() that removes the model and the package NSE handling junk. The default aes(x = Re(1/root), y = Im(1/root), colour = UnitCircle) results in labels labs(x = "x", y = "y", colour = "UnitCircle") for these layers:

... +
  ggplot2::annotate(
    "path", x = cos(seq(0, 2 * pi, length.out = 100)),
    y = sin(seq(0, 2 * pi, length.out = 100))
  ) +
  ggplot2::geom_vline(xintercept = 0) +
  ggplot2::geom_hline(yintercept = 0) +
  geom_point()

Removing annotate() produces the expected labels labs(x = "Re(1/root)", y = "Im(1/root)", colour = "UnitCircle").

Full (not so minimal) MRE ({reprex} isn't working for me at the moment, so apologies for the botched output):

plot_data <- structure(list(
  type = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
                     1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
                     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("AR roots", "MA roots"), class = "factor"), 
  root = c(0.743346174645867+0.743346174645867i, 
           -0.743346174645867+0.743346174645867i, -0.743346174645867-0.743346174645867i, 
           1.01542975837224-0.272083583726372i, 0.272083583726371+1.01542975837224i, 
           -1.01542975837224+0.272083583726371i, -0.272083583726371-1.01542975837224i, 
           1.01542975837224+0.272083583726372i, -0.272083583726372+1.01542975837224i, 
           -1.01542975837224-0.272083583726372i, 0.272083583726372-1.01542975837224i, 
           0.743346174645867-0.743346174645868i, 3.89255799705759+6.88853197873318e-16i, 
           0.7382028071715+0.7382028071715i, -0.877092143351749+0.506389385068237i, 
           -0.506389385068237-0.877092143351749i, 0.877092143351748-0.506389385068237i, 
           0.506389385068238+0.877092143351749i, -1.00840378774125+0.270200980569754i, 
           -0.27020098056976-1.00840378774126i, 1.01277877013646+2.37053503325252e-14i, 
           -6.48524393002789e-15+1.01277877013648i, -1.01277877013648+1.03769254626384e-15i, 
           0.270200980569773-1.00840378774126i, 1.00840378774127-0.270200980569749i, 
           0.270200980569755+1.00840378774126i, -1.00840378774126-0.270200980569754i, 
           3.1285544130455e-15-1.01277877013649i, 0.877092143351752+0.506389385068235i, 
           -0.50638938506824+0.877092143351747i, -0.877092143351755-0.506389385068242i, 
           0.506389385068258-0.877092143351732i, 1.00840378774125+0.270200980569741i, 
           -0.7382028071715+0.738202807171498i, -0.738202807171499-0.738202807171506i, 
           0.738202807171505-0.738202807171487i, -0.270200980569757+1.00840378774125i, 
           1.71020671745964+2.77960735720925e-15i), 
  UnitCircle = structure(c(2L, 
                           2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
                           2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
                           2L, 2L, 2L, 2L, 2L), levels = c("Outside", "Within"), class = "factor")),
  row.names = c(NA, -38L), class = c("tbl_df", "tbl", "data.frame"))


plot_data

library(ggplot2)
ggplot(plot_data, aes(x = Re(1/root), y = Im(1/root),
                      colour = UnitCircle)) +
  ggplot2::annotate(
    "path", x = cos(seq(0, 2 * pi, length.out = 100)),
    y = sin(seq(0, 2 * pi, length.out = 100))
  ) +
  ggplot2::geom_vline(xintercept = 0) +
  ggplot2::geom_hline(yintercept = 0) +
  geom_point() +
  ggplot2::coord_fixed(ratio = 1) +
  facet_grid(cols = vars(type))

image

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@mitchelloharawild mitchelloharawild Jan 31, 2025 •
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Looking into annotate() a bit more, since it is essentially setting up a geom_path() I can understand why it is producing x/y labels. However the resulting labels were a bit surprising to me before I looked into the code since annotate() doesn't have a traditional data+mapping syntax like other layer functions. It is probably difficult to implement, but perhaps annotate() layers should be ignored for layer-based labels.

Perhaps it is best if I just add the desired labels into the plot explicitly.

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I like the suggestion and I've added it to tidyverse/ggplot2#6290

})