Built-in Continuous Color Scales in MATLAB®
How to use Built-in Continuous Color Scales in MATLAB® with Plotly.
Change Colormap for Figure
Create a surface plot and set the colormap to winter
.
surf(peaks)
colormap winter
fig2plotly(gcf);
Set Colormap Back to Default
First, change the colormap for the current figure to summer
.
surf(peaks)
colormap summer
fig2plotly(gcf);
Now set the colormap back to your system's default value. If you have not specified a different default value, then the default colormap is parula
.
surf(peaks)
colormap default
fig2plotly(gcf);
Use Different Colormaps for Each Axes in Figure
Starting in R2019b, you can display a tiling of plots using the tiledlayout
and nexttile
functions. Call the tiledlayout
function to create a 2-by-1 tiled chart layout. Call the nexttile
function to create the axes objects ax1
and ax2
. Specify a different colormap for each axes by passing the axes object to the colormap
function. In the upper axes, create a surface plot using the spring
colormap. In the lower axes, create a surface plot using the winter
colormap.
tiledlayout(2,1)
ax1 = nexttile;
surf(peaks)
colormap(ax1,spring)
ax2 = nexttile;
surf(peaks)
colormap(ax2,winter)
fig2plotly(gcf);
Specify Number of Colors for Colormap
Specify the number of colors used in a colormap by passing an integer as an input argument to the built-in colormap. Use five colors from the parula colormap.
mesh(peaks)
colormap(parula(5))
fig2plotly(gcf);
Create Custom Colormap
Create a custom colormap by defining a three-column matrix of values between 0.0 and 1.0. Each row defines a three-element RGB triplet. The first column specifies the red intensities. The second column specifies the green intensities. The third column specifies the blue intensities.
Use a colormap of blue values by setting the first two columns to zeros.
map = [0 0 0.3
0 0 0.4
0 0 0.5
0 0 0.6
0 0 0.8
0 0 1.0];
surf(peaks)
colormap(map)
fig2plotly(gcf);
Return Colormap Values Used in Plot
Create a surface plot of the peaks
function and specify a colormap.
mesh(peaks)
colormap(autumn(5))
fig2plotly(gcf);
Return the three-column matrix of values that define the colors used in the plot. Each row is an RGB triplet color value that specifies one color of the colormap.
mesh(peaks)
colormap(autumn(5))
cmap = colormap
cmap = 1.0000 0 0 1.0000 0.2500 0 1.0000 0.5000 0 1.0000 0.7500 0 1.0000 1.0000 0
Return Colormap Values for Specific Axes
Return the colormap values for a specific axes by passing the axes object to the colormap
function.
Create a tiling of two plots using the tiledlayout
and nexttile
functions, which are new functions starting in R2019b. Call the tiledlayout
function to create a 2-by-1 tiled chart layout. Call the nexttile
function to create the axes objects ax1
and ax2
. Then display two filled contour plots with different colormaps.
tiledlayout(2,1)
ax1 = nexttile;
contourf(peaks)
colormap(ax1,hot(8))
ax2 = nexttile;
contourf(peaks)
colormap(ax2,pink)
fig2plotly(gcf);
Unrecognized field name "Fill". We had trouble parsing the contour object. This trace might not render properly. Unrecognized field name "Fill". We had trouble parsing the contour object. This trace might not render properly.
Return the colormap values used in the upper plot by passing ax1
to the colormap
function. Each row is an RGB triplet color value that specifies one color of the colormap.
tiledlayout(2,1)
ax1 = nexttile;
contourf(peaks)
colormap(ax1,hot(8))
ax2 = nexttile;
contourf(peaks)
colormap(ax2,pink)
cmap = colormap(ax1)
cmap = 0.3333 0 0 0.6667 0 0 1.0000 0 0 1.0000 0.3333 0 1.0000 0.6667 0 1.0000 1.0000 0 1.0000 1.0000 0.5000 1.0000 1.0000 1.0000
Change Colormap for Figure with Image
Load the spine
data set that returns the image X
and its associated colormap map
. Display X
using the image
function and set the colormap to map
.
load spine
image(X)
colormap(map)
fig2plotly(gcf);
Unrecognized field name "Fill". We had trouble parsing the contour object. This trace might not render properly.