Custom scale_color with gradient and manual value

Question

I want to build a ggplot with a color gradient containing an exception.

For instance, say that I want the gradient to go from blue to black, but with the special value 21 being red.

This can be done using 2 geoms with data filtering:

library(tidyverse)
mtcars %>%
  ggplot(aes(x = qsec, y = wt, color = mpg)) +
  geom_point(size = 3, data=~filter(.x, mpg==21), color="red") +
  geom_point(size = 3, data=~filter(.x, mpg>21)) +
  scale_color_gradient(low="blue", high="black",
                        transform = "log")

ggplot output

^{Created on 2024-12-08 with reprex v2.1.1}

However, using this technique has annoying side effects, one being that the legend doesn't contain the red value.

Is there a way to achieve the same result with one standard geom?

Allan Cameron · Accepted Answer · 2024-12-08 22:13:31Z

2

If you want the ability to specify any value as the red one (rather than only the minimum value) and have only a very specific value as the red one rather than a reddish range, you will probably need to precalculate the values and colours of a scale_color_gradientn

library(tidyverse)

mycol <- colorRampPalette(c("blue", "black"))(3)[2]
myval <- approx(log(range(mtcars$mpg)), 0:1, xout = log(21))$y

mtcars %>%
  ggplot(aes(x = qsec, y = wt, color = mpg)) +
  geom_point(size = 3) +
  scale_color_gradientn(values = c(0, myval - 1e-6, myval, myval + 1e-6, 1),
                        colours = c("blue", mycol, "red", mycol, "black"),
                        transform = "log")

answered Dec 8, 2024 at 22:13

Allan Cameron

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2 Comments

Dan Chaltiel Over a year ago

Great, thanks! However, is there a way to make the red appear on the legend? Specifying limits didn't work for me.

Allan Cameron Over a year ago

@DanChaltiel If you widen the values we put as a buffer around the red value, say by changing 1e-6 to 1e-2, that should be visible on the legend.

lailaps · Accepted Answer · 2024-12-09 09:17:47Z

[Corrected updated version 09.12.24] you can use scale_color_gradientn:

df %>%
      ggplot(aes(x = qsec, y = wt, color = !!sym(column_name))) +
      geom_point(size = 3) +
      scale_color_gradientn(
        colours = c("blue", "red", "black"),
        values = c(0, 0.5, 1),
        transform = "log"
      )

The colours are the colours used at the specific datapoints within the mpg column (0 = blue, 0.5 = red, 01 = blue). The scale_color_gradientn will then scale the colours in between these values.

Using this we could build a custom function highlight_color that takes a dataframe df and a column column_name to apply the colour ramp to. highlight_val marks the value which should be marked as red!

Note: If the highlighted value is near the max/min, then the colour red will applied +- threshold_to_highlightValue around this value.

library(tidyverse)
library(scales)
# Create a custom color scale function
highlight_color <- function(df, column_name, highlight_val = 21, threshold_to_highlightValue = 0.01) {
  # Convert column_name from string to actual column reference
  col <- df[[column_name]]
  
  # Ensure the column is numeric for calculations
  if (!is.numeric(col)) {
    stop("The column must be numeric.")
  }
  
  # Check if highlight_val exists in the column
  if (highlight_val %in% col) {
    # Calculate the normalized position of the highlight value in the scale
    pos_in_df <- (highlight_val - min(col)) / (max(col) - min(col))
    
    # Define color palette and corresponding values
    if (pos_in_df == 0) {
      colors <- c("red", "blue", "black")
      values <- c(0, threshold_to_highlightValue, 1)
    } else if (pos_in_df == 1) {
      colors <- c("black", "blue", "red")
      values <- c(0, 1 - threshold_to_highlightValue, 1)
    } else {
      colors <- c("cadetblue1", "blue", "red","blue", "black")
      values <- c(0, pos_in_df - threshold_to_highlightValue, pos_in_df, pos_in_df + threshold_to_highlightValue, 1)
    }
    
    # Create and return the plot with the customized gradient
    p <- df %>%
      ggplot(aes(x = qsec, y = wt, color = !!sym(column_name))) +
      geom_point(size = 3) +
      scale_color_gradientn(
        colours = colors,
        values = values,
        rescaler = scales::rescale,  # Ensures proper handling of normalized values
        limits = range(col)          # Ensure the color scale fits the data range
      ) +
      theme_minimal() +
      labs(color = column_name)  # Add dynamic label for the legend
    
    return(p)
  } else {
    # If highlight value is not in the column, return a message
    stop(paste0("Value ", highlight_val, " is not in column ", column_name))
  }
}

# Example usage
highlight_color(mtcars, "mpg", highlight_val = 21, threshold_to_highlightValue = 0.01)

which generates:

I did something similar, the problem is that you now have pinkish dots that should not be there.
Hey @DanChaltiel. You are right, that was because of the +-0.1 threshold. I updated my answer code now and it works as expected! Consider including arguments for x/y values like x_column_name and y_column_name. Maybe you could also let the user define the color-ramp colors!

Seth · Accepted Answer · 2024-12-08 21:58:45Z

1

Specifying the values argument in scale_color_gradient gives you control over color positions along the gradient.

library(ggplot2)
library(dplyr)


mtcars |>
  filter(mpg >= 21) |>
  ggplot(aes(x = qsec, y = wt, color = mpg)) +
  geom_point(size = 3) +
  scale_color_gradientn(colours = c('red', 'blue', 'black'),
                        values = c(0,0.01,1),
                        transform = 'log')

answered Dec 8, 2024 at 21:58

Seth

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2 Comments

Allan Cameron Over a year ago

This works well if we always want the lowest value in red but gradient otherwise, though doesn't allow any value to be specified as the red one

Dan Chaltiel Over a year ago

Great, thanks! Although Allan is right that this is a special case of the question, it happens that this is exactly what I wanted! Any chance that we can make the red appear on the legend? Specifying limits didn't work for me.

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