R：使用ggplot更改风险热图中的colorPalette颜色

I can hardly think of a different way than to map your desired colors to specific value ranges. See below. Please check how I reduced your code, there were lots of unnecessary calls, (I guess you've copied it from a script where you have tried different stuff). Also, I have changed the colorRampPalette call - this is a function generator, no need to use function() here.

Notice you would need to manually define the values, and I guess this would be your researcher decision how to present the data. You need to scale it to a range 0:1

library(RColorBrewer)
library(dplyr)
library(ggplot2)

myData <- matrix(c(2,2,3,3,3,1,2,2,3,3,1,1,2,2,3,1,1,2,2,2,1,1,1,1,2), nrow = 5, ncol = 5, byrow = TRUE)
longData <- reshape2::melt(myData)
colnames(longData) <- c("Likelihood", "Consequence", "value")
longData <- mutate(longData, value = Consequence * Likelihood)
mycols <- rev(c("red4","red2","tomato2","orange","gold1","forestgreen"))
cols <- colorRampPalette(mycols)

myvals <- c(0, 8, 9, 10, 11, 25)
scaled_val <- scales::rescale(myvals, 0:1)

ggplot(longData, aes(x = Consequence, y = Likelihood, fill = value)) +
  geom_tile() +
  scale_fill_gradientn(colours = cols(length(mycols)), 
                       values = scaled_val) +
  theme(axis.text.y = element_text(angle = 90, hjust = 1), legend.position = "none") +
  scale_x_continuous(name = "Probability", breaks = seq(1, 5, 1), expand = c(0, 0)) +
  scale_y_reverse(name = "Severity", breaks = seq(1, 5, 1), expand = c(0, 0)) +
  geom_hline(yintercept = seq(1.5, 5.5)) +
  geom_vline(xintercept = seq(1.5, 5.5)) +
  coord_fixed()

另外，您可以定义渐变的起点。我已经在最近的一个线程中展示了如何执行此操作。请注意，您所需的输出与值不匹配（我已经将它们叠加以证明这一点）。还要注意，所有这些显然都是您自己定义的-我选择的那些值是随机的，您可以根据自己的喜好进行调整。

myvals <- c(0, 6, 7, 9, 10, 11, 25)
scaled_val <- scales::rescale(myvals, 0:1)

ggplot(longData, aes(x = Consequence, y = Likelihood, fill = value)) +
  geom_tile() +
  geom_text(aes(label = value)) +
  scale_fill_gradientn(colours = c(mycols[1], mycols), 
                       values = scaled_val) +
  theme(axis.text.y = element_text(angle = 90, hjust = 1), legend.position = "none") +
  scale_x_continuous(name = "Probability", breaks = seq(1, 5, 1), expand = c(0, 0)) +
  scale_y_reverse(name = "Severity", breaks = seq(1, 5, 1), expand = c(0, 0)) +
  geom_hline(yintercept = seq(1.5, 5.5)) +
  geom_vline(xintercept = seq(1.5, 5.5)) +
  coord_fixed()