如何在R plotly色標中強制將零映射為白色

Question

我的代碼如下，但我希望將白色映射到 0 而不是 data_bydate$avg_score 的最大值和最小值的中間值

g <- plot_ly(data_bydate, x = ~Date, y = ~avg_score, color =data_bydate$avg_score, colors = c("#FF0000","#FFFFFF", "#008000"), mode ='markers', marker = list(size=3)) %>%
layout(legend = list(orientation = 'h'), 
       xaxis = list(title = "",
                    zeroline = FALSE,
                    tickformat="%X",
                    showline = TRUE), 
       yaxis = list(title = "",
                    zeroline = FALSE,
                    showline = TRUE ))

Answer 1

您可以創建自己的colorscale ，從紅色（最小）到白色（零）再到綠色（最大）。 colorscale是一個數組列表，它由兩個單獨的色標組成，一個用於低於零的部分，從紅色到白色，另一個用於高於零的部分，從白色到綠色。

library(plotly)
library(scales)

set.seed(42)
colorlength <- 100

data_bydate <- data.frame(Date = c(1:23),
                          avg_score = c(runif(10, -5, -1), 
                                        rep(0,3), 
                                        runif(10, 1, 10)
                                        )
                          )

null_value <- (0 - min(data_bydate$avg_score)) / (max(data_bydate$avg_score) - min(data_bydate$avg_score))        
border <- as.integer(null_value * colorlength)
colorscale <- as.list(1:colorlength)

#colorscale below zero
s <- scales::seq_gradient_pal("#FF0000", "#FFFFFF", "Lab")(seq(0,1,length.out=border))
for (i in 1:border) {
    colorscale[[i]] <- c((i - 1) / colorlength, s[i])
}

#colorscale above zero
s <- scales::seq_gradient_pal("#FFFFFF", "#008000", "Lab")(seq(0,1,length.out=colorlength - border))
for (i in 1:(colorlength - border)) {
  colorscale[[i + border]] <- c((i + border) / colorlength, s[i])
}

plot_ly(data_bydate, 
        x = ~Date, 
        y = ~avg_score, 
        type = 'scatter',
        mode ='markers', 
        marker = list(size = 10,
                      color = ~avg_score,
                      colorscale = colorscale,
                      colorbar = list(len=1))) %>%
  layout(plot_bgcolor = 'black')

Answer 2

一個簡單的方法是設置限制，這里min是-2，max是2，0在中間。

colorbar(title = "Change (%)", limits = c(-2, 2))

並選擇一個發散的調色板；

colorscale = "RdBu",
reversescale = TRUE,

發散的調色板是：BrBG、PiYG、PRGn、PuOr、RdBu、RdGy、RdYlBu、RdYlGn、Spectral。

反轉比例會反轉色階的方向。

Answer 3

只是為了增加 Maximilian Peters 的出色答案，在某些應用程序中，可能需要一個不對稱的色標來反映數據中的不對稱性。 在馬克西米利安回答的示例中，這意味着 -4 的紅色陰影與值 4 的綠色陰影的亮度相當。

這可以通過以下方式實現：

library(plotly)
library(scales)

set.seed(42)
colorlength <- 100

data_bydate <- data.frame(Date = c(1:23),
                          avg_score = c(runif(10, -5, -1), 
                                        rep(0,3), 
                                        runif(10, 1, 10)
                                        )
                          )

null_value <- (0 - min(data_bydate$avg_score)) / (max(data_bydate$avg_score) - min(data_bydate$avg_score))        
border <- as.integer(null_value * colorlength)
colorscale <- as.list(1:colorlength)


if (border < colorlength / 2) {
    ## colorscale below zero
    border_neg <- colorlength - border
    s <- scales::seq_gradient_pal("#FF0000", "#FFFFFF", "Lab")(seq(0,1,length.out=border_neg))
    for (i in 1:border) {
        colorscale[[i]] <- c((i - 1) / colorlength, s[i + border_neg - border - 1])
    }

    ## colorscale above zero
    border_pos <- border
    s <- scales::seq_gradient_pal("#FFFFFF", "#008000", "Lab")(seq(0,1,length.out=colorlength - border_pos))
    for (i in 1:(colorlength - border_pos)) {
        colorscale[[i + border_pos]] <- c((i + border) / colorlength, s[i])
    }
} else {
    ## colorscale below zero
    border_neg <- border
    s <- scales::seq_gradient_pal("#FF0000", "#FFFFFF", "Lab")(seq(0,1,length.out=border_neg))
    for (i in 1:border_neg) {
        colorscale[[i]] <- c((i - 1) / colorlength, s[i])
    }

    ## colorscale above zero
    border_pos <- colorlength - border
    s <- scales::seq_gradient_pal("#FFFFFF", "#008000", "Lab")(seq(0,1,length.out=border))
    for (i in 1:border_pos) {
        colorscale[[i + border]] <- c((i + border) / colorlength, s[i])
    }
}


plot_ly(data_bydate, 
        x = ~Date, 
        y = ~avg_score, 
        type = 'scatter',
        mode ='markers', 
        marker = list(size = 10,
                      color = ~avg_score,
                      colorscale = colorscale,
                      colorbar = list(len=1))) %>%
  layout(plot_bgcolor = 'black')