r - ggplot2::coord_cartesian 在方面

Question

coord_cartesian不允许设置每个方面的坐标，并且使用其他范围限制往往会在特定极端上产生一条直线。由于我们有广泛变化的 y 范围，我们不能对所有方面都设置相同的限制；geom_line在 plot 之前限制数据对/ geom_path( https://stackoverflow.com/a/27319786/3358272 )不友好，因为插入数据以到达边缘然后插入NAs 以打破上线。（最终，获得所需结果的唯一方法就是这样做，这对于其他数据可能有点繁琐。）

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)

在以前的版本中ggplot2，该要点定义coord_panel_ranges并能够控制每个方面的坐标。右侧的两个方面应缩小到 1-6（ish）的 y 轴，以便爆炸置信区间脱离屏幕并允许方面主要关注数据的“正常范围”。（注意：test_data这个 vis 不是我的，它取自要点。虽然我的需求有些相似，但我认为最好留在要点的数据和代码的范围内。）

不幸的是，这对我来说现在失败了ggplot2-3.3.0。与最近丢失的相关的初始错误ggplot2::scale_range，我试图通过对 burchill 代码（使用其他ggplot2:::内部函数）的这种改编来减轻这些错误：

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

我对扩展不是很熟悉ggplot2，我怀疑 ggproto 中缺少一些东西。以下是 proto 的返回值：

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至少包含一个break_positions_minor函数的列表元素，或者是否需要继承其他东西以确保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))

score 8 · Accepted Answer

我修改了函数train_cartesian以匹配（在此处view_scales_from_scale定义）的输出格式，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
  ))

原始答案

我以前曾欺骗过类似的问题。

# 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)

score 6 · Accepted Answer

非常感谢 Z.Lin 开始修复我的问题，这个答案无疑帮助我克服了错误并学习了一种更合适的ggproto对象处理方式。

该答案作为一种更灵活的方法发布，用于解决多面图中每个面板限制的潜在问题。我的第一批代码的主要问题是它依赖于方面的顺序，在我的一些其他（私人）用例中，这并不总是事先知道（好吧，不受控制）。因此，我希望明确确定每个面板的限制。

我已经更改了函数名称（和 args）以表示两点：（1）这似乎是模仿/替换coord_cartesian，以及（2）我不知道它会在coord_*没有调整的情况下转换为其他函数。欢迎在我的要点上发表评论/补丁。

在前面，可以通过以下方式完美复制 Z.Lin 的结果：

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_cartesian_panels(
  panel_limits = tibble::tribble(
    ~DataType, ~ExpType, ~ymin, ~ymax
  , "A"      , "X"     ,     1,     4
  , "A"      , "Y"     ,     1,     6
  , "B"      , "Y"     ,     1,     7
  )
)

并且消失的是哪个面板是列表中的哪个参数的歧义（原始代码引入）。由于它使用 adata.frame来匹配（通常merge）与layout绘图的，所以行的顺序无关紧要。

笔记：

引用的panel_limits字段是：xmin、xmax、ymin和ymax, 在所需的任何构面变量之上；
NA在特定字段（或缺失字段）中的 an 表示使用先前定义的限制；
当所有faceting-variables 匹配（在panel_limits和定义的布局之间facet_*）时，在各个面板上设置限制；这种一对一的映射是关于这个函数的假设；
当一些（但不是全部）变量匹配时，限制设置在面板的子集上（例如，在面板的一个轴上，取决于分面方法）；
当没有变量匹配并且panel_limits是单行时，则不加选择地为所有面板设置限制；和
panel_limits匹配中没有任何内容的刻面行layout会被默默忽略。

错误：

panel_limits布局中不存在的任何构面变量（即，未在中指定facet_*）；或者
多于一行panel_limits匹配一个特定的面板。

作为扩展，这也处理了 faceting 变量的一个子集，所以如果我们只想限制所有 facet ExpType，那么

# set the limits on panels based on one faceting variable only
p + coord_cartesian_panels(
  panel_limits = tibble::tribble(
    ~ExpType, ~ymin, ~ymax
  , "X"     ,    NA,     4
  , "Y"     ,     1,     5
  )
) + labs(title = "panel_limits, one variable")

# set the limits on all panels
p + coord_cartesian_panels(
  panel_limits = tibble::tribble(
    ~ymin, ~ymax
  , NA,     5
  )
) + labs(title = "panel_limits, no variables")

（最后一个例子看起来很傻，但是如果面/图是以编程方式构建的，并且不能先验地保证存在各个面，那么这将导致合理的默认行为，假设一切都是明确的。）

进一步的扩展可能允许NA一个方面变量匹配所有，例如

# does not work
p + coord_cartesian_panels(
  panel_limits = tibble::tribble(
    ~DataType, ~ExpType, ~ymin, ~ymax
  , "A"      , NA      ,     1,     4
  , NA       , "Y"     ,     1,     6
  )
)

这需要merge理解这NA意味着“所有/任何”，而不是文字NA。我现在不打算扩展merge来处理这个问题，所以我不会让这个函数复杂化来尝试这样做。如果有一个合理的merge替代品可以进行这种微积分，请告诉我:-)

非常感谢...

burchill为最初的努力和要点；和
Z.Lin，帮助将功能提升到ggplot2-3.3.0.

UniquePanelCoords <- ggplot2::ggproto(
  "UniquePanelCoords", ggplot2::CoordCartesian,
  
  num_of_panels = 1,
  panel_counter = 1,
  layout = NULL,
  
  setup_layout = function(self, layout, params) {
    self$num_of_panels <- length(unique(layout$PANEL))
    self$panel_counter <- 1
    self$layout <- layout # store for later
    layout
  },
  
  setup_panel_params =  function(self, scale_x, scale_y, params = list()) {
    train_cartesian <- function(scale, limits, name, given_range = c(NA, NA)) {
      if (anyNA(given_range)) {
        expansion <- ggplot2:::default_expansion(scale, expand = self$expand)
        range <- ggplot2:::expand_limits_scale(scale, expansion, coord_limits = limits)
        isna <- is.na(given_range)
        given_range[isna] <- range[isna]
      }
      out <- list(
        ggplot2:::view_scale_primary(scale, limits, given_range),
        sec = ggplot2:::view_scale_secondary(scale, limits, given_range),
        arrange = scale$axis_order(),
        range = given_range
      )
      names(out) <- c(name, paste0(name, ".", names(out)[-1]))
      out
    }

    this_layout <- self$layout[ self$panel_counter,, drop = FALSE ]
    self$panel_counter <- 
      if (self$panel_counter < self$num_of_panels) {
        self$panel_counter + 1
      } else 1

    # determine merge column names by removing all "standard" names
    layout_names <- setdiff(names(this_layout),
                            c("PANEL", "ROW", "COL", "SCALE_X", "SCALE_Y"))
    limits_names <- setdiff(names(self$panel_limits),
                            c("xmin", "xmax", "ymin", "ymax"))

    limit_extras <- setdiff(limits_names, layout_names)
    if (length(limit_extras) > 0) {
      stop("facet names in 'panel_limits' not found in 'layout': ",
           paste(sQuote(limit_extras), collapse = ","))
    } else if (length(limits_names) == 0 && NROW(self$panel_limits) == 1) {
      # no panels in 'panel_limits'
      this_panel_limits <- cbind(this_layout, self$panel_limits)
    } else {
      this_panel_limits <- merge(this_layout, self$panel_limits, all.x = TRUE, by = limits_names)
    }

    if (isTRUE(NROW(this_panel_limits) > 1)) {
      stop("multiple matches for current panel in 'panel_limits'")
    }

    # add missing min/max columns, default to "no override" (NA)
    this_panel_limits[, setdiff(c("xmin", "xmax", "ymin", "ymax"),
                                names(this_panel_limits)) ] <- NA

    c(train_cartesian(scale_x, self$limits$x, "x",
                      unlist(this_panel_limits[, c("xmin", "xmax"), drop = TRUE])),
      train_cartesian(scale_y, self$limits$y, "y",
                      unlist(this_panel_limits[, c("ymin", "ymax"), drop = TRUE])))
  }
)

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

score 3 · Accepted Answer

在某些时候，我遇到了与此类似的问题。结果是一个稍微冗长但也更灵活的选项，可以在每个方面自定义位置比例的许多方面。由于某些技术性，它scales::oob_keep()在标尺上使用等效的 as oob 参数，从而就好像坐标确定了限制一样。

library(ggh4x)
library(tidyverse)

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) +
  facetted_pos_scales(
    x = list(
      scale_x_continuous(limits = c(8, 64)),
      scale_x_continuous(limits = c(64, 8), trans = "reverse"),
      NULL,
      scale_x_continuous(limits = c(8, 64), labels = scales::dollar_format())
    ),
    y = list(
      scale_y_continuous(limits = c(1, 4), guide = "none"),
      scale_y_continuous(limits = c(1, 6), breaks = 1:3),
      NULL,
      scale_y_continuous(limits = c(1, 7), position = "right")
    )
  )

r - ggplot2::coord_cartesian 在方面

3 回答 3

原始答案

非常感谢...

Related

Reference