Change color of 2D plot line depending on 3rd value

Question

I have a data set that looks like this

 140400 70.7850 1
 140401 70.7923 2
 140402 70.7993 3
 140403 70.8067 4
 140404 70.8139 5
 140405 70.8212 3

Where the first column corresponds to time (one second intervals between data points) and will be on the x axis, the second column corresponds with distance and will be on the y axis. The third column is a number (one through five) that is a qualification of the movement.

I want to make a plot that changes the color of the line between two points depending on what the number of the previous data point was. For example, I want the line to be red between the first and second data points because the qualification value was 1.

I've seen a lot of posts about making a sliding scale of colors depending on an intensity value, but I just want 5 colors: (red, orange, yellow, green, and blue) respectively.

I tried doing something like this:

plot(x,y,{'r','o','y','g','b'})

But with no luck.

Any ideas of how to approach this? Without looping if possible.

Answer 1

You can also do it with a trick which works with Matlab version anterior to 2014b (as far back as 2009a at least).
However, is will never be as simple as you expected (unless you write a wrapper for one of the solution here you can forget about plot(x,y,{'r','o','y','g','b'})).

The trick is to use a surface instead of a line object. Surfaces benefit from their CData properties and a lot of useful features to exploit color maps and texture.

Matlab surf does not handle 1D data, it needs a matrix as input so we are going to give it by just duplicating each coordinate set (for example xx=[x,x]).
Don't worry though, the surface will stay as thin as a line, so the end result is not ugly.

%% // your data
M=[140400 70.7850 1
 140401 70.7923 2
 140402 70.7993 3
 140403 70.8067 4
 140404 70.8139 5
 140405 70.8212 3];

x = M(:,1) ; %// extract "X" column
y = M(:,2) ; %// same for "Y"
c = M(:,3) ; %// extract color index for the custom colormap

%% // define your custom colormap
custom_colormap = [
    1  0 0 ; ... %// red
    1 .5 0 ; ... %// orange
    1  1 0 ; ... %// yellow
    0  1 0 ; ... %// green
    0  0 1 ; ... %// blue
    ] ;

%% // Prepare matrix data
xx=[x x];           %// create a 2D matrix based on "X" column
yy=[y y];           %// same for Y
zz=zeros(size(xx)); %// everything in the Z=0 plane
cc =[c c] ;         %// matrix for "CData"

%// draw the surface (actually a line)
hs=surf(xx,yy,zz,cc,'EdgeColor','interp','FaceColor','none','Marker','o') ;

colormap(custom_colormap) ;     %// assign the colormap
shading flat                    %// so each line segment has a plain color
view(2) %// view(0,90)          %// set view in X-Y plane
colorbar

---

will get you:

---

As an example of a more general case:

x=linspace(0,2*pi);
y=sin(x) ;

xx=[x;x];
yy=[y;y];
zz=zeros(size(xx));

hs=surf(xx,yy,zz,yy,'EdgeColor','interp') %// color binded to "y" values
colormap('hsv')
view(2) %// view(0,90)

will give you a sine wave with the color associated to the y value:

Answer 2

Do you have Matlab R2014b or higher?

Then you could use some undocumented features introduced by Yair Altman:

n = 100;
x = linspace(-10,10,n); y = x.^2;
p = plot(x,y,'r', 'LineWidth',5);

%// modified jet-colormap
cd = [uint8(jet(n)*255) uint8(ones(n,1))].' %'

drawnow
set(p.Edge, 'ColorBinding','interpolated', 'ColorData',cd)

Answer 3

My desired effect was achieved below (simplified):

        indices(1).index  = find( data( 1 : end - 1, 3) == 1);
        indices(1).color  = [1 0 0]; 
        indices(2).index  = find( data( 1 : end - 1, 3) == 2 | ...
                                  data( 1 : end - 1, 3) == 3);
        indices(2).color  = [1 1 0];
        indices(3).index  = find( data( 1 : end - 1, 3) == 4 | ...
                                  data( 1 : end - 1, 3) == 5);
        indices(3).color  = [0 1 0];
        indices(4).index  = find( data( 1 : end - 1, 3) == 10);
        indices(4).color  = [0 0 0];
        indices(5).index  = find( data( 1 : end - 1, 3) == 15);
        indices(5).color  = [0 0 1];

    % Loop through the locations of the values and plot their data points
    % together (This will save time vs. plotting each line segment
    % individually.)

    for iii = 1 : size(indices,2)

        % Store locations of the value we are looking to plot
        curindex = indices(iii).index;

        % Get color that corresponds to that value
        color = indices(iii).color;

            % Create X and Y that will go into plot, This will make the line
            % segment from P1 to P2 have the color that corresponds with P1
            x = [data(curindex, 1), data(curindex + 1, 1)]';
            y = [data(curindex, 2), data(curindex + 1, 2)]';

            % Plot the line segments
            hold on
            plot(x,y,'Color',color,'LineWidth',lineWidth1)            

    end

Answer 4

When the result figure of two variables plotted is a circle, will be necessary to add the time in z axes.

For example the figure of induction machine rotor velocity vs electric torque in one laboratory test is: 2d plot figure

In the last figure the direction of the time point plotting could be clockwise or counter clockwise. For the last reason will be added time in z axis.

% Wr vs Te
x =  logsout.getElement( 'Wr' ).Values.Data; 
y =  logsout.getElement( '<Te>' ).Values.Data;
z =  logsout.getElement( '<Te>' ).Values.Time;
% % adapt variables for use surf function
xx = zeros( length( x ) ,2 );
yy = zeros( length( y ) ,2 );
zz = zeros( length( z ) ,2 );
xx (:,1) = x; xx (:,2) = x;
yy (:,1) = y; yy (:,2) = y;
zz (:,1) = z; zz (:,2) = z;
% % figure(1) 2D plot
figure (1)
hs = surf(xx,yy,zz,yy,'EdgeColor','interp') %// color binded to "y" values
colormap('hsv')
view(2) 
% %
figure(2)
hs = surf(xx,yy,zz,yy,'EdgeColor','interp') %// color binded to "y" values
colormap('hsv')
view(3) 

Finally we can view the 3d form and detect that counterwise is the real direction of the time plotting is: 3d plot

Answer 5

Scatter can plot the color according to the value and shows the colormap of the range of values. It's hard to interpolate the color though if you want continuous curves.

Try:

figure
i = 1:20;
t = 1:20;
c = rand(1, 20) * 10;
scatter(i, t, [], c, 's', 'filled')
colormap(jet)

The figure looks like