How do I limit the range of the viridis colour scale?

geom_hex color scale
viridis color palette
viridis rgb values
color scale r
ggplot reverse color scale
using viridis palette in r
scale_fill_continuous(type = viridis)
scale_fill_viridis_c

I have two sets of data, which I want to present using a heat map with the viridis color scale. For the first data set, my values range from 0 to 1.2 and I can easily see the differences I want to see. However my second data set has some outliers, resulting in a range from 0 to 2. Now it's harder to see the differences in the interesting range between 0 and 1 and it's more diffucult to compare the two images directly. Is there a possibility to show the data from 0 to 1.2 using the viridis colour scale while showing the higher values in yellow ("highest" colour of the viridis scale)? Here is an example:

library(viridis)

#Create Data
DataSet1 <- expand.grid(x = 0:5, y = 0:5)
DataSet1$z <- runif(36, 0, 1.2)

DataSet2 <- expand.grid(x = 0:5, y = 0:5)
DataSet2$z <- runif(36, 0, 2)

#Plot Data
ggplot(DataSet1, aes(x, y, fill = z)) + 
  geom_tile() +
  scale_fill_viridis() +
  geom_text(aes(label = round(z, 2)), size = 2)

DataSet1: Differences between 0.5 and 0.7 are easy to see

ggplot(DataSet2, aes(x, y, fill = z)) + 
  geom_tile() +
  scale_fill_viridis() +
  geom_text(aes(label = round(z, 2)), size = 2)

DataSet2: Differences between 0.5 and 0.7 are diffucult to see


You can define an arbitrary rescaling function. Not sure this looks that great, would likely need some work with the legend, but in principle this mechanism allows you to map data values onto the scale in any way you want.

ggplot(DataSet2, aes(x, y, fill = z)) + 
  geom_tile() +
  scale_fill_viridis(rescaler = function(x, to = c(0, 1), from = NULL) {
    ifelse(x<1.2, 
           scales::rescale(x,
                           to = to,
                           from = c(min(x, na.rm = TRUE), 1.2)),
           1)}) +
  geom_text(aes(label = round(z, 2)), size = 2)

Viridis colour scales from viridisLite — scale_colour_viridis_d • ggplot2, The viridis scales provide colour maps that are perceptually uniform in both continuous_scale() , or binned_scale to control name, limits, breaks, labels and so forth. See rescale() for a convenience function to map an arbitrary range to� Sets the order of colors in the scale. If 1, the default, colors are ordered from darkest to lightest. If -1, the order of colors is reversed. option: A character string indicating the colormap option to use. Four options are available: "magma" (or "A"), "inferno" (or "B"), "plasma" (or "C"), "viridis" (or "D", the default option) and "cividis" (or "E").


@ClausWilke's solution is better because it shows in the legend, but sometimes one just needs a quick solution without having to write too much specific code. This one also relies on the scales package

ggplot(DataSet2, aes(x, y, fill = z)) + 
  geom_tile() +
  scale_fill_viridis(limits = c(0.2, 1), oob = scales::squish) +
  geom_text(aes(label = round(z, 2)), size = 2)

Viridis colour scales from viridisLite, The viridis scales provide colour maps that are perceptually uniform in both colour passed on to discrete_scale() or continuous_scale() to control name, limits, breaks, See rescale() for a convenience function to map an arbitrary range to� This is also true, though less so, for the “heat” colors. The other scales are more perceptually uniform, but “viridis” stands out for its large perceptual range. It makes as much use of the available color space as possible while maintaining uniformity.


Are you looking for something like this?

ggplot(DataSet2, aes(x, y, fill = z)) + 
  geom_tile() +
  scale_fill_gradient(low="green", high="red", limits=c(0, 1.2), 
                      na.value = "yellow") +
  geom_text(aes(label = round(z, 2)), size = 2)

Using the viridis colors, asper jazzurro recommendation.

ggplot(DataSet2, aes(x, y, fill = z)) + 
  geom_tile() + 
  scale_fill_gradientn(colors = viridis_pal()(9), limits=c(0, 1.2), 
                       na.value = "#FDE725FF") + 
  geom_text(aes(label = round(z, 2)), size = 2)

scale_color_viridis function, Viridis color scales. Uses the viridis color scale. Usage. scale_color_viridis(, alpha =� How to reverse/inverse the color scale of a viridis theme in ggplot. Package: viridis Function: scale_fill_viridis_c() (since it’s a continuous scaled value) with the option parameter. Paramater Direction: -1 (Default is +1)


It's not necessarily an improvement, but you could do something like this to show the higher values in yellow:

DataSet2A <- DataSet2 %>% filter(z <= 1.2)
DataSet2B <- DataSet2 %>% filter(z > 1.2)

ggplot(DataSet2A, aes(x, y, fill = z)) +
  geom_tile() +
  scale_fill_viridis(begin = 0, end = .75) +
  geom_text(aes(label = round(z, 2)), size = 2) +
  geom_tile(data = DataSet2B, aes(x, y), fill = "yellow")

Maybe if you play around with the cutoff as well as the begin= and end= parameters in the scale, which control the portion of the viridis scale that you're employing, you can achieve the result you want. (Note that you can only have one fill scale per plot, but you can set additional constant fills as I've done here with yellow.)

Limiting the range of colours in a featureplot - tidyverse, Limiting the range of colours in a featureplot So, to get yellow and blue, you would specify those colours, or use a palette/colour scale that's to https://cran.r- project.org/web/packages/viridis/vignettes/intro-to-viridis.html Sets the order of colors in the scale. If 1, the default, colors are as output by viridis_pal. If -1, the order of colors is reversed. discrete. generate a discrete palette? (default: FALSE - generate continuous palette) option. A character string indicating the colormap option to use.


4.2 Customizing ggplot2 Plots, We'll end the subsection by going over scales and color specifically. The graph on the right has added shading showing the range of daily death counts in July in across plots, and it also allows you to save room by limiting axis annotation. For example, to use the viridis color palette for a plot of time versus shots for the� I want to make a plot using a color palette from packages viridis or RColorBrewer, but I would like to set what point in the variable distribution should be considered as the middle point in the color gradient. For example, in the following plots, R takes 0.5 to be the middle point of the color range.


[PDF] Package 'viridis', Viridis color scales. Description. Uses the viridis color scale. Usage scale_color_viridis(, alpha = 1, begin = 0, end = 1, direction = 1, discrete = FALSE, option� Even in full color, this uneven brightness means that the eye will be drawn to certain portions of the color range, which will potentially emphasize unimportant parts of the dataset. It's better to use a colormap such as viridis (the default as of Matplotlib 2.0), which is specifically constructed to have an even brightness variation across the


Set reference value for color range in viridis � Issue #38 � sjmgarnier , I know viridis package already has begin and end arguments to set color range. Why don't you just use the limits argument to set the range of the scale? If the purpose is to zoom, use the limit argument in the coordinate system (see coord_cartesian () ). A function used to scale the input values to the range [0, 1]. This is always scales::rescale (), except for diverging and n colour gradients (i.e., scale_colour_gradient2 () , scale_colour_gradientn () ).