I am wondering if it is possible to label the contours of a MATLAB contour plot with a set of user-defined strings?
I am currently using the following code snipper to produce a labelled contour plot:
%Create Data
X = 0.01:0.01:0.10
Y = 0.01:0.01:0.10
Z = repmat(X.^2,length(X),1) + repmat(Y.^2,length(Y),1)';
%Create Plot
hold on
[C,h] = contourf(X,Y,Z);
%Add + Format Labels to Plot
hcl = clabel(C,h,'FontSize',10,'Color','k','Rotation',0);
set(hcl,'BackgroundColor',[1 1 1],'EdgeColor',[0 0 0],'LineStyle','-',)
hold off
The issue with this code is that the labels are automatically generated by MATLAB. Even as I can easily change the contours that are labels, I cannot change the labels that they get.
Ideally, I would like to label them with a set of strings that I define myself. However if that is not possible, then I am wondering if it is possible to change the numeric format of the labels. The reason for this is that the code above actually produce a contour plot for an error rate, which I would like to display as a % value (i.e. use 1% in the contour label, instead of 0.01 etc.).
In this case, hcl is actually an array which stores handles to every contour label on your plot. When you set properties using the array (as in your code),
set(hcl, 'name', 'value')
You will set the property of every label to the same value.
You can change the properties of individual labels by iterating over the array. For example, this is how you would add a percentage sign:
for i = 1:length(hcl)
oldLabelText = get(hcl(i), 'String');
percentage = str2double(oldLabelText)*100;
newLabelText = [num2str(percentage) ' %'];
set(hcl(i), 'String', newLabelText);
end
Related
I produced a plot that contains 50 curves and each of them corresponds to a specific value of a parameter called "Jacobi constant", so I have 50 values of jacobi constant stored in array called jacobi_cst_L1:
3.000900891023230
3.000894276927840
3.000887643313580
3.000881028967010
3.000874419173230
3.000867791975870
3.000861196034850
3.000854592397690
3.000847948043080
3.000841330136040
3.000834723697250
3.000828099771820
3.000821489088600
3.000814922863360
3.000808265737810
3.000801695858850
3.000795067776960
3.000788475204760
3.000781845363950
3.000775192199620
3.000768609354090
3.000761928862980
3.000755335851910
3.000748750854930
3.000742084743060
3.000735532899990
3.000728906460450
3.000722309400740
3.000715644446600
3.000709016645110
3.000702431180730
3.000695791284050
3.000689196186970
3.000682547292110
3.000675958537960
3.000669315388860
3.000662738391370
3.000656116141060
3.000649560630930
3.000642857256680
3.000636330415510
3.000629657944820
3.000623060310100
3.000616425935580
3.000609870077710
3.000603171772120
3.000596554947660
3.000590018845460
3.000583342259840
3.000576748353570
I want to use a colormap to color my curves and then show in a lateral bar the legend that show the numerical values corresponding to each color of orbit.
By considering my example image, I would want to add the array of constants in the lateral bar and then to color each curve according the lateral bar.
% Family of 50 planar Lyapunov orbits around L1 in dimensionless unit
fig = figure;
for k1 = 1:(numel(files_L1_L2_Ly_prop)-2)
plot([Ly_orb_filt(1).prop(k1).orbits.x],[Ly_orb_filt(1).prop(k1).orbits.y],...
"Color",my_green*1.1); hold on %"Color",my_green*1.1
colorbar()
end
axis equal
% Plot L1 point
plot(Ly_orb_filt_sys_data(1).x,Ly_orb_filt_sys_data(1).y,'.',...
'color',[0,0,0],'MarkerFaceColor',my_green,'MarkerSize',10);
text(Ly_orb_filt_sys_data(1).x-0.00015,Ly_orb_filt_sys_data(1).y-0.0008,'L_{1}');
%Primary bodies plots
plot(AstroData.mu_SEM_sys -1,0,'.',...
'color',my_blue,'MarkerFaceColor',my_blue,'MarkerSize',20);
text(AstroData.mu_SEM_sys-1,0-0.001,'$Earth + Moon$','Interpreter',"latex");
grid on;
xlabel('$x$','interpreter','latex','fontsize',12);
ylabel('$y$','interpreter','latex','FontSize',12);
How can I color each line based on its Jacobi constant value?
You can use any colour map to produce a series of RGB-triplets for the plotting routines to read (Or create an m-by-3 matrix with elements between 0 and 1 yourself):
n = 10; % Plot 10 lines
x = 1:15;
colour_map = jet(n); % Get colours. parula, hsv, hot etc.
figure;
hold on
for ii = 1:n
% Plot each line individually
plot(x, x+ii, 'Color', colour_map(ii, :))
end
colorbar % Show the colour bar.
Which on R2007b produces:
Note that indexing into a colour map will produce linearly spaced colours, thus you'll need to either interpolate or calculate a lot to get the specific ones you need. Then you can (need to?) modify the resulting colour bar's labels by hand to reflect your input values. I'd simply use parula(50), treat its indices as linspace(jacobi(1), jacobi(end), 50) and then my_colour = interp1(linspace(jacobi(1), jacobi(end), 50), parula(50), jacobi).
So in your code, rather than using "Color",my_green*1.1 for each line, use "Color",my_colour(kl,:), where my_colour is whatever series of RGB triplets you have defined.
I have a matlab code that generates 3D points , so I want to plot each 3D point with different colors.
My last code for generat all points are
figure(i),plot3(mx,my,mz,'r*');
and this one plot all peaks but with same color which are red.
instead of figure(i),plot3(mx,my,mz,'r*'); you can plot each datapoint separately and assign a different color using the property 'Color' of the plot3.
such an example would be:
figure(i),hold on
for j=1:length(mx)
plot3(mx(j),my(j),mz(j),'Color',rand(1,3));
end
hold off
The way each point is coloured is up to you just change the rand to something that makes sense.
What about using e.g. hsv:
M = length(mx);
cols = hsv(M); % specify M colors by hsv
figure(i);
hold on;
for pIdx = 1:M
plot3(mx(pIdx),my(pIdx),mz(pIdx),'Color',cols(pIdx,:));
end
I would like to visualize different responses of different systems in a single plot with Matlab's control toolbox, and to colorize the various curves so it is easy to differentiate between the different systems.
The response plots are easily created using the control toolbox - e.g. step response (using step), response to an arbitrary input (using lsim), etc.
When using separate model objects for different systems, It's easy to create multi-color plots, e.g., for a step response: step(Sys1, 'b', Sys2, 'r') would give one blue curve and one red cure, if Sys1 and Sys2 are both a single system model.
However, if plotting a model array, there's no way to differentiate between the various curves that belong to the same array. E.g.: step(SysArray, 'b') would make all curves blue. step(Sys,'b','r') is invalid - so no easy way to specify various colors.
Also, using the "Edit Plot" tool, selecting one curve effectively selects all curves, and any changes to the properties (e.g. line color) would affect all curves.
Is there any way to control the properties of each curve separately?
There's no built-in function to do this, so you have to roll your own functionality
% Create n-by-3 array of colours to use
coloursArray = rand(numel(stackedSystems),3); % for this example put in random colours
% Do the plot
step(stackedSystems);
title('My custom title');
grid on
% Change colours
ha = findobj(gcf,'type','axes','visible','on'); % Get handles of all axes (for MIMO responses)
for jdx = 1:numel(ha)
hl = findobj(ha(jdx),'type','line','visible','on'); % Get handles to all lines
for idx = 1:numel(hl)
set(hl(idx),'Color',coloursArray(idx,:)); % Change the colour
end
end
#Phil Goddard
There's no built-in function to do this, so you have to roll your
own functionality
% Create n-by-3 array of colours to use
coloursArray = rand(numel(stackedSystems),3); % for this example put in random colours
% Do the plot
step(stackedSystems);
title('My custom title');
grid on
% Change colours
ha = findobj(gcf,'type','axes','visible','on'); % Get handles of all axes (for MIMO responses)
for jdx = 1:numel(ha)
hl = findobj(ha(jdx),'type','line','visible','on'); % Get handles to all lines
for idx = 1:numel(hl)
set(hl(idx),'Color',coloursArray(idx,:)); % Change the colour
end
end
Thanks for the code!
Here are some slight changes to work better with model sampling through parameter variation, including the colorbar.
I was hoping it would also work with pzmap, for example, but it creates 2*n lines (poles and zeros), so it would need a bit more work.
function colorSamplingPlot(values,var)
% values is an array with parameter value assigned to each curve
% var is a string for the colorbar label
n = numel(findobj(gca,'type','line','visible','on'));
% Create n-by-3 array of colours to use
coloursArray = colormap(jet(n));
% Change colours
% Get handles of all axes (for MIMO responses)
ha = findobj(gcf,'type','axes','visible','on');
for jdx = 1:numel(ha)
% Get handles to all lines
hl = findobj(ha(jdx),'type','line','visible','on');
for idx = 1:numel(hl)
% Change the color; inverted color order to match colorbar
set(hl(idx),'Color',coloursArray(numel(hl)-idx+1,:));
end
end
colorbar;
caxis([min(values),max(values)]);
hcb = colorbar;
hcb.Label.String = vars;
end
Say I have a data set with x values of longitude and Y values of 1 to 100. How can I plot the whole data set and represent all Y values over 90 with a different symbol?
Thanks for the help!
The easiest way would be to plot the sets separately, and specify a different symbol for each set i.e.
plot(x(Y<=90),Y(Y<=90),'bx',x(Y>90),Y(Y>90),'bo');
You could also do different colors. The scatter function has the ability to specify a different color for each point with the syntax scatter(x,y,s,c). For your example, you could do:
% make data
rng(0,'twister'); theta = linspace(0,2*pi,150);
x = sin(theta) + 0.75*rand(1,150); x = x*100;
y = cos(theta) + 0.75*rand(1,150); y = y*100;
mask = y>90;
% plot with custom colors for each point
c = zeros(numel(x),3); % matrix of RGB colorspecs
c(mask,:) = repmat([1 0 0],nnz(mask),1); % red
c(~mask,:) = repmat([0 0 1],nnz(~mask),1); % blue
scatter(x,y,10,c,'+');
Or instead of and RGB colorspec matrix, you can index into the current colormap. This allows you to get a nice smooth variation with some value:
scatter(x,y,10,y+x,'o') % x+y is mapped to indexes into default colormap, jet(64)
You can combine this color mapping with the approach of separating the data into two sets to also get different markers. Split the data, plot the first set with scatter as above, hold on, and plot the second set with a different marker. For example,
cv = x+y; % or just y, but this is an interesting example
scatter(x(mask),y(mask),10,cv(mask),'+');
hold on
scatter(x(~mask),y(~mask),10,cv(~mask),'o');
The result is different marker styles, where '+' is used where y>90 and '+' elsewhere, and different colors, where color is determined by mapping the values of cv=x+y onto the current colormap. The idea here is to look at 2 different modes of variations, but you could just use cv=y.
I have a scatter plot that will overlay several sets of data. Each set of data currently displays as the next color in the default colormap. This is my code right now:
figure
hold on
for i=1:10
scatter(RunRawArea(i,:), RunRawNetLength(i,:));
end
hold off
What i would like is to color code each set of data (indexed by i) to be the next color on a gradient. For example, the data for i=1 would be blue, i=5 would be purple, and i=10 would be red.
How could I do this?
You should add another parameter to scatter - called CData
https://www.mathworks.com/help/matlab/ref/scatter.html
Description: scatter(x,y) creates a scatter plot with circles
at the locations specified by the vectors x and y. This type of graph
is also known as a bubble plot.
In your example:
figure
hold on
colorVec = linspace(1,0, size(RunRawNetLength,1));
colorVec = transpose(colorVec);
colorVec = repmat(colorVec,[1 3]);
for i=1:10
scatter(RunRawArea(i,:), RunRawNetLength(i,:),'CData', colorVec );
end
hold off
Method 1:
You can vectorize your data, so you don't need a loop and than add a color by series:
% specify your color map:
colorCode = lines(size(RunRawNetLength,1)); % or any other colormap...
% define the correct color for each series:
coloVev = repmat(colorCode,size(RunRawNetLength,1),1);
% plot it all at once without a loop:
scatter(RunRawArea(:),RunRawNetLength(:),[],coloVev)
Method 2:
If you have the Statistics and Machine Learning Toolbox you can also do this with gscatter:
% define the series of data:
group = repmat(1:size(RunRawNetLength,1),1,size(RunRawNetLength,1));
% plot it all at once without a loop:
gscatter(RunRawArea(:),RunRawNetLength(:),group,colorCode);
if your colormap has not enough colors for all the series, then the function loops over and start from the first one.
Result:
In both cases the result for some random data will be (the main difference is that gscatter fill the data points and add the legend by default):
Note that I used the colormap lines which has only 7 entries, so in this example with 10 series it repeats itself.