Provide more semantics around customization of the colorscale

Heatmap does not use all the colors specified in the colors argument when data passed to z value has skewed distribution. Here is a small example to illustrate the problem.

library(plotly)
library(RColorBrewer)

# create a dataframe where z has a skewed distribution
set.seed(1)
df = data.frame(x = rep(1:50, 20) , y = rep(1:20,each =50), z = rgamma(1000, 2, 0.5))

# check distribution of z 
plot_ly(data = df, x = ~z, type = "histogram")%>% 
    layout(title = "histogram of z")  

# original heatmap
# pass the column z with screwed distribution to z argument
plot_ly(data=df, x=~x, y=~y, z=~z, type="heatmap",  
        colors = "Spectral") %>% 
    layout(title = "original heatmap")

I currently work around the issue by creating a new variable according to the quantiles of the original variable, and pass it to the z argument.

# some data processing work 
# find unique quantiles of z 
quantiles = unique(quantile(df$z, seq(0,1,0.1)))

# create a dummy column z1 of discrete values using the quantiles as cut off
# the ideas is to arrage the data to subgroups of roughly the same size 
df$z1= cut(df$z, breaks =  c(quantiles[1]-1,quantiles[-1]), right = TRUE, labels = FALSE)

# check distribution of z1 
plot_ly(data = df, x = ~z1, type = "histogram")%>% 
    layout(title = "histogram of z1")

# new heatmap 
# passes the new column z1 to z argument 
plot_ly(data=df, x=~x, y=~y, z=~z1, type="heatmap",  
        # make sure hovering over displays original z
        text =~z, hoverinfo = "text", 
        # use the color palettes from RColorBrewer, 
        # or your customized colorscale
        colors = "Spectral",  
        # map the label of the colorbar back to the quantiles
        colorbar=list(tickmode="array", tickvals = 1:(length(quantiles)-1), ticktext = round(quantiles,2)[-1], title = "z")) %>% 
layout(title = "new heat map")

Here is the link to the heatmaps before and after data processing. The new heatmap picks up more colors from the "Spectral" palette to differentiate between smaller values.
https://i.stack.imgur.com/TymlR.png

I would like to see features in plotly to force heatmap use all the user specified colors.

Thanks!

Reproduce the supplied R heatmap example with the skewed gamma-distributed z values and compare it with the quantile-based workaround. Start by tracing the heatmap colors argument and determine the intended semantics for using all specified colors; done should include a defined behavior for skewed distributions and a verified example.