r - ggplot2::coord_cartesian 在方面

Question

coord_cartesian 不允许设置 per-facet 坐标，并且使用其他范围限制往往会在特定的极端产生一条直线。由于我们有广泛变化的 y 范围，我们不能在所有方面设置相同的限制；在绘图之前限制数据对 geom_line/geom_path ( https://stackoverflow.com/a/27319786/3358272 ) 并不友好，因为插入数据以到达边缘需要更多的努力，然后插入 NA 以拆分线。 (最终，获得所需结果的唯一方法就是这样做，这对于其他数据来说可能有点繁重。)
在 https://gist.github.com/burchill/d780d3e8663ad15bcbda7869394a348a 中建议了一种解决方法，它以

test_data %>%
  ggplot(aes(x=Nsubjects, y = Odds, color=EffectSize)) +
  facet_wrap(DataType ~ ExpType, labeller = label_both, scales="free") +
  geom_line(size=2) +
  geom_ribbon(aes(ymax=Upper, ymin=Lower, fill=EffectSize, color=NULL), alpha=0.2)

在 ggplot2 的早期版本中，该要点定义了 coord_panel_ranges 并且能够控制每个方面的坐标。两个正确的方面应该缩小到 1-6(ish) y 轴，以便爆炸置信区间离开屏幕，并使方面主要关注数据的“正常范围”。 (注意: test_data 和这个 vis 不是我的，它取自 gist。虽然我的需求有些相似，但我认为最好留在 gist 的数据和代码的范围内。)
不幸的是，这现在对我来说失败了 ggplot2-3.3.0 。与最近丢失 ggplot2::scale_range 相关的初始错误，我试图通过对 burchill 代码(使用其他 ggplot2::: 内部函数)的这种改编来缓解:

UniquePanelCoords <- ggplot2::ggproto(
  "UniquePanelCoords", ggplot2::CoordCartesian,
  
  num_of_panels = 1,
  panel_counter = 1,
  panel_ranges = NULL,
  
  setup_layout = function(self, layout, params) {
    self$num_of_panels <- length(unique(layout$PANEL))
    self$panel_counter <- 1
    layout
  },
  
  setup_panel_params =  function(self, scale_x, scale_y, params = list()) {
    if (!is.null(self$panel_ranges) & length(self$panel_ranges) != self$num_of_panels)
      stop("Number of panel ranges does not equal the number supplied")
    
    train_cartesian <- function(scale, limits, name, given_range = NULL) {
      if (is.null(given_range)) {
        expansion <- ggplot2:::default_expansion(scale, expand = self$expand)
        range <- ggplot2:::expand_limits_scale(scale, expansion,
                                               coord_limits = self$limits[[name]])
      } else {
        range <- given_range
      }
      
      out <- scale$break_info(range)
      out$arrange <- scale$axis_order()
      names(out) <- paste(name, names(out), sep = ".")
      out
    }
    
    cur_panel_ranges <- self$panel_ranges[[self$panel_counter]]
    if (self$panel_counter < self$num_of_panels)
      self$panel_counter <- self$panel_counter + 1
    else
      self$panel_counter <- 1
    
    c(train_cartesian(scale_x, self$limits$x, "x", cur_panel_ranges$x),
      train_cartesian(scale_y, self$limits$y, "y", cur_panel_ranges$y))
  }
)

coord_panel_ranges <- function(panel_ranges, expand = TRUE, default = FALSE, clip = "on") {
  ggplot2::ggproto(NULL, UniquePanelCoords, panel_ranges = panel_ranges, 
          expand = expand, default = default, clip = clip)
}

但这仍然失败

test_data %>%
  ggplot(aes(x=Nsubjects, y = Odds, color=EffectSize)) +
  facet_wrap(DataType ~ ExpType, labeller = label_both, scales="free") +
  geom_line(size=2) +
  geom_ribbon(aes(ymax=Upper, ymin=Lower, fill=EffectSize, color=NULL), alpha=0.2) +
  coord_panel_ranges(panel_ranges = list(
    list(x=c(8,64), y=c(1,4)), # Panel 1
    list(x=c(8,64), y=c(1,6)), # Panel 2
    list(NULL),                # Panel 3, an empty list falls back on the default values
    list(x=c(8,64), y=c(1,7))  # Panel 4
  ))
# Error in panel_params$x$break_positions_minor() : 
#   attempt to apply non-function

我对扩展 ggplot2 不是很熟悉，我怀疑 ggproto 中遗漏了一些东西。这是 proto 的返回值的样子:

str(c(train_cartesian(scale_x, self$limits$x, "x", cur_panel_ranges$x),
      train_cartesian(scale_y, self$limits$y, "y", cur_panel_ranges$y)))
# List of 14
#  $ x.range       : num [1:2] 8 64
#  $ x.labels      : chr [1:3] "20" "40" "60"
#  $ x.major       : num [1:3] 0.214 0.571 0.929
#  $ x.minor       : num [1:6] 0.0357 0.2143 0.3929 0.5714 0.75 ...
#  $ x.major_source: num [1:3] 20 40 60
#  $ x.minor_source: num [1:6] 10 20 30 40 50 60
#  $ x.arrange     : chr [1:2] "secondary" "primary"
#  $ y.range       : num [1:2] 1 4
#  $ y.labels      : chr [1:4] "1" "2" "3" "4"
#  $ y.major       : num [1:4] 0 0.333 0.667 1
#  $ y.minor       : num [1:7] 0 0.167 0.333 0.5 0.667 ...
#  $ y.major_source: num [1:4] 1 2 3 4
#  $ y.minor_source: num [1:7] 1 1.5 2 2.5 3 3.5 4
#  $ y.arrange     : chr [1:2] "primary" "secondary"

我是否需要一个 x 元素，该元素是一个至少包含一个 break_positions_minor 函数的列表，或者是否需要继承其他内容以确保 panel_params$x$break_positions_minor 存在或使用合理的默认值？

数据:

test_data <- structure(list(DataType = structure(c(1L, 1L, 1L, 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), .Label = c("A", "B"), class = "factor"), 
    ExpType = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("X", "Y"), class = "factor"), 
    EffectSize = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("15", "35"
    ), class = "factor"), Nsubjects = c(8, 16, 32, 64, 8, 16, 
    32, 64, 8, 16, 32, 64, 8, 16, 32, 64, 8, 16, 32, 64, 8, 16, 
    32, 64, 8, 16, 32, 64, 8, 16, 32, 64), Odds = c(1.06248116259846, 
    1.09482076720863, 1.23086993413208, 1.76749340505612, 1.06641831731573, 
    1.12616954196688, 1.48351814320987, 3.50755080416964, 1.11601399761081, 
    1.18352602009495, 1.45705466646283, 2.53384744810515, 1.13847061762186, 
    1.24983742407086, 1.97075900741022, 6.01497152563726, 1.02798821372378, 
    1.06297006279249, 1.19432835697453, 1.7320754674107, 1.02813271730924, 
    1.09355953747203, 1.44830680332583, 3.4732692664923, 1.06295915758305, 
    1.12008443626365, 1.3887632112682, 2.46321037334, 1.06722652223114, 
    1.1874936754725, 1.89870184372054, 5.943747409114), Upper = c(1.72895843644471, 
    2.09878774769559, 2.59771794965346, 5.08513435549015, 1.72999898901071, 
    1.8702196882561, 3.85385388850167, 5.92564404180303, 1.99113042576373, 
    2.61074135841984, 3.45852331828636, 4.83900142207583, 1.57897154221764, 
    1.8957409107653, 10, 75, 2.3763918424135, 2.50181951057562, 
    3.45037180395673, 3.99515276392065, 2.04584535265976, 2.39317394040066, 
    2.832526733659, 5.38414183471915, 1.40569501856836, 2.6778044191832, 
    2.98023068052396, 4.75934650422069, 1.54116883311054, 2.50647989271592, 
    3.48517589981551, 100), Lower = c(0.396003888752214, 0.0908537867216577, 
    -0.135978081389309, -1.55014754537791, 0.40283764562075, 
    0.382119395677663, -0.88681760208193, 1.08945756653624, 0.240897569457892, 
    -0.243689318229938, -0.544413985360706, 0.228693474134466, 
    0.69796969302609, 0.603933937376415, 0.183548809738402, 3.57236968943798, 
    -0.320415414965949, -0.375879384990643, -1.06171509000767, 
    -0.531001829099242, 0.010420081958713, -0.206054865456611, 
    0.0640868729926525, 1.56239669826544, 0.720223296597732, 
    -0.437635546655903, -0.202704257987574, 0.167074242459314, 
    0.593284211351745, -0.131492541770921, 0.312227787625573, 
    3.76692741957876)), .Names = c("DataType", "ExpType", "EffectSize", 
"Nsubjects", "Odds", "Upper", "Lower"), class = c("tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -32L))

Answer 1

我修改了函数train_cartesian匹配 view_scales_from_scale 的输出格式(定义 here )，这似乎有效:

train_cartesian <- function(scale, limits, name, given_range = NULL) {
    if (is.null(given_range)) {
        expansion <- ggplot2:::default_expansion(scale, expand = self$expand)
        range <- ggplot2:::expand_limits_scale(scale, expansion,
                                               coord_limits = self$limits[[name]])
    } else {
        range <- given_range
    }
    
    out <- list(
        ggplot2:::view_scale_primary(scale, limits, range),
        sec = ggplot2:::view_scale_secondary(scale, limits, range),
        arrange = scale$axis_order(),
        range = range
    )
    names(out) <- c(name, paste0(name, ".", names(out)[-1]))
    out
}

p <- test_data %>%
  ggplot(aes(x=Nsubjects, y = Odds, color=EffectSize)) +
  facet_wrap(DataType ~ ExpType, labeller = label_both, scales="free") +
  geom_line(size=2) +
  geom_ribbon(aes(ymax=Upper, ymin=Lower, fill=EffectSize, color=NULL), alpha=0.2)

p + 
  coord_panel_ranges(panel_ranges = list(
    list(x=c(8,64), y=c(1,4)), # Panel 1
    list(x=c(8,64), y=c(1,6)), # Panel 2
    list(NULL),                # Panel 3, an empty list falls back on the default values
    list(x=c(8,64), y=c(1,7))  # Panel 4
  ))

原答案
我从 similar problem 中被骗了之前。

# alternate version of plot with data truncated to desired range for each facet
p.alt <- p %+% {test_data %>%
    mutate(facet = as.integer(interaction(DataType, ExpType, lex.order = TRUE))) %>%
    left_join(data.frame(facet = 1:4,
                         ymin = c(1, 1, -Inf, 1),  # change values here to enforce
                         ymax = c(4, 6, Inf, 7)),  # different axis limits
              by = "facet") %>%
    mutate_at(vars(Odds, Upper, Lower), list(~ ifelse(. < ymin, ymin, .))) %>%
    mutate_at(vars(Odds, Upper, Lower), list(~ ifelse(. > ymax, ymax, .))) }

# copy alternate version's panel parameters to original plot & plot the result
p1 <- ggplot_build(p)
p1.alt <- ggplot_build(p.alt)
p1$layout$panel_params <- p1.alt$layout$panel_params
p2 <- ggplot_gtable(p1)
grid::grid.draw(p2)