Question

我想在ggplot2中重现此色阶：（Source）

过去我found创建了ggplot2之间带有标签的离散色标可能会很棘手。

这可以完成吗？我最近提出的一个类似但不完全相同的问题是this一个。

Answer 1

感谢Tjebo's answer，我设法创建了一个函数，用于绘制一个漂亮的颜色条，通过使用cowplot，patchwork或其他类似的软件包（如他的示例）添加到图中。

这是：编辑：你也可以在github

找到它

plot_discrete_cbar = function(
    breaks, # Vector of breaks. If +-Inf are used, triangles will be added to the sides of the color bar
    palette = "Greys", # RColorBrewer palette to use
    colors = RColorBrewer::brewer.pal(length(breaks) - 1, palette), # Alternatively, manually set colors
    direction = 1, # Flip colors? Can be 1 or -1
    spacing = "natural", # Spacing between labels. Can be "natural" or "constant"
    border_color = NA, # NA = no border color
    legend_title = NULL,
    legend_direction = "horizontal", # Can be "horizontal" or "vertical"
    font_size = 5,
    expand_size = 1, # Controls spacing around legend plot
    spacing_scaling = 1, # Multiplicative factor for label and legend title spacing
    width = 0.1, # Thickness of color bar
    triangle_size = 0.1 # Relative width of +-Inf triangles
) {
    require(ggplot2)
    if (!(spacing %in% c("natural", "constant"))) stop("spacing must be either 'natural' or 'constant'")
    if (!(direction %in% c(1, -1))) stop("direction must be either 1 or -1")
    if (!(legend_direction %in% c("horizontal", "vertical"))) stop("legend_direction must be either 'horizontal' or 'vertical'")
    breaks = as.numeric(breaks)
    new_breaks = sort(unique(breaks))
    if (any(new_breaks != breaks)) warning("Wrong order or duplicated breaks")
    breaks = new_breaks
    if (class(colors) == "function") colors = colors(length(breaks) - 1)
    if (length(colors) != length(breaks) - 1) stop("Number of colors (", length(colors), ") must be equal to number of breaks (", length(breaks), ") minus 1")
    if (!missing(colors)) warning("Ignoring RColorBrewer palette '", palette, "', since colors were passed manually")

    if (direction == -1) colors = rev(colors)

    inf_breaks = which(is.infinite(breaks))
    if (length(inf_breaks) != 0) breaks = breaks[-inf_breaks]
    plotcolors = colors

    n_breaks = length(breaks)

    labels = breaks

    if (spacing == "constant") {
        breaks = 1:n_breaks
    }

    r_breaks = range(breaks)

    cbar_df = data.frame(stringsAsFactors = FALSE,
        y = breaks,
        yend = c(breaks[-1], NA),
        color = as.character(1:n_breaks)
    )[-n_breaks,]

    xmin = 1 - width/2
    xmax = 1 + width/2

    cbar_plot = ggplot(cbar_df, aes(xmin=xmin, xmax = xmax, ymin = y, ymax = yend, fill = factor(color, levels = 1:length(colors)))) +
        geom_rect(show.legend = FALSE,
                  color=border_color)

    if (any(inf_breaks == 1)) { # Add < arrow for -Inf
        firstv = breaks[1]
        polystart = data.frame(
            x = c(xmin, xmax, 1),
            y = c(rep(firstv, 2), firstv - diff(r_breaks) * triangle_size)
        )
        plotcolors = plotcolors[-1]
        cbar_plot = cbar_plot +
            geom_polygon(data=polystart, aes(x=x, y=y),
                        show.legend = FALSE,
                        inherit.aes = FALSE,
                        fill = colors[1],
                        color=border_color)
    }
    if (any(inf_breaks > 1)) { # Add > arrow for +Inf
        lastv = breaks[n_breaks]
        polyend = data.frame(
            x = c(xmin, xmax, 1),
            y = c(rep(lastv, 2), lastv + diff(r_breaks) * triangle_size)
        )
        plotcolors = plotcolors[-length(plotcolors)]
        cbar_plot = cbar_plot +
            geom_polygon(data=polyend, aes(x=x, y=y),
                        show.legend = FALSE,
                        inherit.aes = FALSE,
                        fill = colors[length(colors)],
                        color=border_color)
    }

    if (legend_direction == "horizontal") { #horizontal legend
        mul = 1
        x = xmin
        xend = xmax
        cbar_plot = cbar_plot + coord_flip()
        angle = 0
        legend_position = xmax + 0.1 * spacing_scaling
    } else { # vertical legend
        mul = -1
        x = xmax
        xend = xmin
        angle = -90
        legend_position = xmax + 0.2 * spacing_scaling
    }

    cbar_plot = cbar_plot +
        geom_segment(data=data.frame(y = breaks, yend = breaks),
            aes(y=y, yend=yend),
            x = x - 0.05 * mul * spacing_scaling, xend = xend,
            inherit.aes = FALSE) +
        annotate(geom = 'text', x = x - 0.1 * mul * spacing_scaling, y = breaks,
                label = labels,
                size = font_size) +
        scale_x_continuous(expand = c(expand_size,expand_size)) +
        scale_fill_manual(values=plotcolors) +
        theme_void()

    if (!is.null(legend_title)) { # Add legend title
        cbar_plot = cbar_plot +
            annotate(geom = 'text', x = legend_position, y = mean(r_breaks),
                label = legend_title,
                angle = angle,
                size = font_size)
    }

    cbar_plot
}

使用示例：

plot_discrete_cbar(c(1:10))

plot_discrete_cbar(c(0,2,5,10,20, Inf), palette="Reds")

plot_discrete_cbar(c(0,2,5,10,20, Inf), colors=rainbow, legend_direction="vertical", legend_title="A title! WOW!", border_color="red")

plot_discrete_cbar(c(-Inf, -8, -4, -2, -1, 1, 2, 4, 8, Inf), palette="BrBG", legend_title="Precipitation bias (mm/day)")

plot_discrete_cbar(c(-Inf, -8, -4, -2, -1, 1, 2, 4, 8, Inf), palette="BrBG", legend_title="Precipitation bias (mm/day)", spacing="constant")

Answer 2

受@Henrik 's answer in this question启发，可能的解决方法是制作一个看起来像传奇的情节：）

require(ggplot2)
require(cowplot)


values <- c(0,1,2,5,10) # this vector is needed not only for the data frame cbar, but also for plotting
group <- letters[1:5]
diff_values <- c(0, diff(values))
cbar_df <- data.frame(x = 1, y = values, diff_values,group,  stringsAsFactors = FALSE)
#that's for the fake legend

iris2 <- iris #don't want to mess with your iris data set
              #I used iris because you hadn't provided data
iris2$cuts <- cut(iris2$Petal.Length, values) #the already offered 'cut-approach' 


p1  <- ggplot(iris2, aes(Sepal.Length, y = Sepal.Width, color = cuts))+ 
          geom_point() +
          scale_color_brewer("", palette = "Reds")

cbar_plot <- ggplot(cbar_df, aes(x, y = diff_values, fill = c(NA, rev(group[2:5])))) + 
  # I had to do implement this 'fill=' workaround 
  # in creating a new vector introducing an NA, 
  # and I had to flip the fills in order to fit to the scale... 
    geom_col(width = 0.1, show.legend = FALSE)  +
    geom_segment(y = values, yend = values, x = 0.9, xend = 1.05) +
    annotate(geom = 'text', x = 0.85, y = values, label = values) +
  # the numbers are quasi-randomly chosen but define the length of your ticks, obviously
    scale_x_continuous(expand = c(1,1)) + 
  # you might need to play around with the expand argument for the width of your legend
    scale_fill_brewer("", palette = "Reds", direction = -1) +  
  # don't know why you have to flip this again... 
    coord_flip() +
    theme_void()

plot_grid(p1, cbar_plot, nrow = 2)

我的意思是 - 肯定有很大的改进空间（使传说情节更小......等等）。但你怎么看？

#P.S. 
sessionInfo() 
cowplot_0.9.2 ggplot2_2.2.1

Answer 3

我认为以下答案足够不同，值得第二个答案。 ggplot2在过去的两年中发生了巨大变化（！），现在有诸如scale_..._binned之类的新功能，以及诸如scale_..._fermenter

之类的特定渐变创建功能

这使得离散梯度条的创建相当简单。

有关“完全分隔符”而不是刻度的信息，请参见user teunbrands post。

library(ggplot2)

ggplot(iris, aes(Sepal.Length, y = Sepal.Width, fill = Petal.Length))+
  geom_point(shape = 21) +
  scale_fill_fermenter(breaks = c(1:3,5,7), palette = "Reds") + 
  guides(fill = guide_colorbar(
    ticks = TRUE, 
    even.steps = FALSE,
    frame.linewidth = 0.55, 
    frame.colour = "black", 
    ticks.colour = "black",
    ticks.linewidth = 0.3)) +
  theme(legend.position = "bottom")

我今天早些时候发布的另一个选项（我将留给后代使用）是创建手动中断并计算需要重复多少次颜色，这涉及相当数量的代数。它还使用了经过修改的functions from Claus Wilke。

library(ggplot2)
#importFrom RColorBrewer brewer.pal

mybreaks <- c(0,1,2,5,10) 

new_breaks <- seq(mybreaks[1], mybreaks[length(mybreaks)], sect_x(mybreaks))
my_lims <- c(mybreaks[1], mybreaks[length(mybreaks)])
rep_times <- (diff(mybreaks)[!is.na(diff(mybreaks))])/sect_x(mybreaks)
mycols <- rep(RColorBrewer::brewer.pal(length(mybreaks)-1, "Reds"), rep_times) 

ggplot(iris, aes(Sepal.Length, y = Sepal.Width, fill = Petal.Length))+
  geom_point(shape = 21) +
  scale_fill_discrete_gradient(limits = my_lims,
    breaks = mybreaks, colors = mycols, bins = length(mycols),
    guide = guide_colourbar(frame.colour = "black", 
                            ticks.colour = "black", # you can also remove the ticks with NA
                            barwidth=20)
  ) +
  theme(legend.position = "bottom")

选项2的功能

## from Claus Wilke
discrete_gradient_pal <- function(colours, bins = 5) {
  ramp <- scales::colour_ramp(colours)
  
  function(x) {
    if (length(x) == 0) return(character())
    
    i <- floor(x * bins)
    i <- ifelse(i > bins-1, bins-1, i)
    ramp(i/(bins-1))
  }
}
## modified to "fill" from Claus Wilke
scale_fill_discrete_gradient <- 
  function(..., colours, bins = 5, 
           na.value = "grey50", 
           guide = "colourbar", 
           aesthetics = "fill", colors)  {
    colours <- if (missing(colours)) 
      colors
    else colours
    continuous_scale(
      aesthetics,
      "discrete_gradient",
      discrete_gradient_pal(colours, bins),
      na.value = na.value,
      guide = guide,
      ...
    )
  } 

## https://stackoverflow.com/a/5173906/7941188
decimalplaces <- function(x) {
    if ((x %% 1) != 0) {
      nchar(strsplit(sub('0+$', '', as.character(x)), ".", fixed=TRUE)[[1]][[2]])
    } else {
      return(0)
    }
  }

## find the number by which each element is divisible as an integer
# importFrom numbers divisors
sect_x <- function(x){
  diff_x <- diff(x)[!is.na(diff(x))]
  diff_x <- round(diff_x, 2)
  max_dec <-  max(sapply(diff_x, decimalplaces))
  ## https://math.stackexchange.com/a/3732661/662220
  m_int <- 10^(-1*max_dec)
  x_div <- as.integer(round(diff_x / m_int, 0))
  x_div <- x_div[x_div != 0]
  max_divisor <- max(Reduce(intersect, lapply(x_div, numbers::divisors)))
  fac_div <- m_int * max_divisor
  fac_div
}

Answer 4

您可以使用

scale_fill_gradientn (guide = guide_colourbar(nbin = 255))

实现。

您可以将nbin设置为任意值。

Answer 5

你可以试试。对于第一个答案，另请参阅here

# data
set.seed(1324)
dat <- data.frame(x=0:100, y=runif(101, 0, 10), z=seq(0, 12, len=101))
# add discrete values
dat$col <- cut(include.lowest = T,
  dat$z, 
  breaks=c(0, 2, 4, 6, 8, max(dat$z)), 
  labels=c(2, 4, 6, 8, 10)
)
# Discete
ggplot(dat, aes(x,y,fill=col)) + 
  geom_point(aes(col=col),size=8, show.legend = F) +   
  geom_col(alpha=0)+
  scale_fill_brewer("", palette = "Reds")+
  scale_colour_brewer("", palette="Reds")+
  scale_alpha_discrete(range=c(0,1))+
  guides(fill = guide_legend(nrow=1,override.aes = list(alpha = 1), 
                             label.position="bottom",
                             label.hjust = -0.05)) +
  theme(legend.position="bottom",
        legend.key.width = unit(3, "cm"), 
        legend.key.height = unit(1, "cm"))

# Continuous
ggplot(dat, aes(x,y,color=y)) + 
  geom_point(size=8) +   
  scale_colour_continuous("",limits=c(0,10), 
                          breaks=c(0, 2, 4, 6, 8, 10),low = "white", high = "red")+
  theme(legend.position="bottom",
        legend.key.width = unit(3, "cm"), 
        legend.key.height = unit(1, "cm"))

创建具有不同间隔宽度且图例级别之间没有间距的离散颜色条

5 个答案: