I would like to plot a 3D surface using the Matlab surf function. The whole surface should be in gray scale, then I need to highlight a specific cut of the surface using a different color.
I thought this code would've worked but it doesn't.
Mat = randi(100); % Matrix to be plotted in gray scale
ind_highlight = 10; % Row of the matrix to be highlighted
Mat2 = Mat;
Mat2([1:ind_highlight-1, ind_highlight+1:end] ,:) = NaN;
figure
surf(X,Y,Mat)
colormap gray
hold on
% Highlight the ind_highlight row
surf(X,Y,Mat2)
colormap hsv
Any help would be highly appreciated!
It seems there is no way to use different colormap to obtain the desired effect since the colormap "belongs" to the figure.
I've found a possible solution which does not use colormap.
It is based on the specifying the color matrix in the call to surf, one for the whole matrix, one for the section to be highlighted, then superimposing the second one to the first one.
Unfortunately, I've not been able to set the first ad gray.
I've used the peaks matrix instead of your "randi" in order to have a more smooth surface to work with and inserted the script in a for loop to highlight different section of the matrix
% Mat = randi(100,100,100); % Matrix to be plotted in gray scale
% Alternative definition of the Matrix to be displayed
n_pt=50;
Mat=peaks(n_pt);
% Generate meshgrid
x=1:n_pt;
y=1:n_pt;
[X,Y]=meshgrid(x,y);
ind_highlight_2 = 5; % Number of rows of the matrix to be highlighted
% Generate two set of color matrix
% The first on for the whole surf
% The second one for the section to be highlighted
a=randi(2,n_pt,n_pt);
b=randi(10,n_pt,n_pt);
for i=1:n_pt-ind_highlight_2
ind_highlight_1 = i; % Starting row of the matrix to be highlighted
Mat2 = Mat;
% Modified set of data (in the original just one row was left
% Mat2([1:ind_highlight-1, ind_highlight+1:end] ,:) = NaN
Mat2(ind_highlight_1:ind_highlight_1+ind_highlight_2,:) = NaN;
COL=a;
COL(ind_highlight_1:ind_highlight_1+ind_highlight_2,:)=b(ind_highlight_1:ind_highlight_1+ind_highlight_2,:);
% Plot the surf specifying the color
s_h=surf(X,Y,Mat,COL);
shading interp
% view([0 90])
% f_name=['jpg_name_' num2str(i)]
% print('-djpeg75',f_name)
pause(.1);
end
Hope this helps.
Related
This question already has answers here:
Change color of 2D plot line depending on 3rd value
(5 answers)
Closed 5 years ago.
How do you create a color gradient in Matlab such that you plot a 2D line plot of y=y(x), and you color it using another variable that also depends on x such that z=z(x). A scatter or point plot is also fine by me.
I would also like to have a colormap legend kind of thing showing the color gradient and it's actual representation of z. This stuff is quite common in visualisation tools such as VisIt and ParaView but I could not yet FIGURE it out in Matlab.
If a scatter plot is fine, you can use the 4th input to scatter:
x = -10:0.01:10;
y = sinc(x);
z = sin(x);
scatter(x,y,[],z,'fill')
where z is the color.
The only way I know of to do this is with a little trick using surf:
% Create some sample data:
x = cumsum(rand(1,20)); % X data
y = cumsum(rand(1,20)); % Y data
z = 1:20; % "Color" data
% Plot data:
surf([x(:) x(:)], [y(:) y(:)], [z(:) z(:)], ... % Reshape and replicate data
'FaceColor', 'none', ... % Don't bother filling faces with color
'EdgeColor', 'interp', ... % Use interpolated color for edges
'LineWidth', 2); % Make a thicker line
view(2); % Default 2-D view
colorbar; % Add a colorbar
And the plot:
To manipulate the color of the line continuously, you'll want to use surface.
While at first look, this function looks most useful for plotting 3d surfaces, it provides more flexibility for line coloring than the basic plot function. We can use the edges of the mesh to plot our line, and take advantage of the vertex colors, C, to render interpolated color along the edge.
You can check out the full list of rendering properties, but the ones you are most likely to want are
'FaceColor', 'none', do not draw the faces
'EdgeColor', 'interp', interpolate between vertices
Here's an example adapted from MATLAB Answers post
x = 0:.05:2*pi;
y = sin(x);
z = zeros(size(x)); % We don't need a z-coordinate since we are plotting a 2d function
C = cos(x); % This is the color, vary with x in this case.
surface([x;x],[y;y],[z;z],[C;C],...
'FaceColor','none',...
'EdgeColor','interp');
Generate a colormap, e.g. jet(10). The example would generate a 10*3 matrix.
Use interp1 to interpolate between the values in the RGB space using your data by setting the first color as the lowest value and the last color as the highest value. This would generate a n*3 matrix where n is the number of data points.
Use scatter with the optional parameter c to plot the points with the interpolated colors.
activate colorbar to show the colorbar.
I'm trying to draw a set of rectangles, each with a fill color representing some value between 0 and 1. Ideally, I would like to use any standard colormap.
Note that the rectangles are not placed in a nice grid, so using imagesc, surf, or similar seems unpractical. Also, the scatter function does not seem to allow me to assign a custom marker shape. Hence, I'm stuck to plotting a bunch of Rectangles in a for-loop and assigning a FillColor by hand.
What's the most efficient way to compute RGB triplets from the scalar values? I've been unable to find a function along the lines of [r,g,b] = val2rgb(value,colormap). Right now, I've built a function which computes 'jet' values, after inspecting rgbplot(jet). This seems a bit silly. I could, of course, obtain values from an arbitrary colormap by interpolation, but this would be slow for large datasets.
So, what would an efficient [r,g,b] = val2rgb(value,colormap) look like?
You have another way to handle it: Draw your rectangles using patch or fill specifying the color scale value, C, as the third parameter. Then you can add and adjust the colorbar:
x = [1,3,3,1,1];
y = [1,1,2,2,1];
figure
for ii = 1:10
patch(x + 4 * rand(1), y + 2 * rand(1), rand(1), 'EdgeColor', 'none')
end
colorbar
With this output:
I think erfan's patch solution is much more elegant and flexible than my rectangle approach.
Anyway, for those who seek to convert scalars to RGB triplets, I'll add my final thoughts on the issue. My approach to the problem was wrong: colors should be drawn from the closest match in the colormap without interpolation. The solution becomes trivial; I've added some code for those who stumble upon this issue in the future.
% generate some data
x = randn(1,1000);
% pick a range of values that should map to full color scale
c_range = [-1 1];
% pick a colormap
colormap('jet');
% get colormap data
cmap = colormap;
% get the number of rows in the colormap
cmap_size = size(cmap,1);
% translate x values to colormap indices
x_index = ceil( (x - c_range(1)) .* cmap_size ./ (c_range(2) - c_range(1)) );
% limit indices to array bounds
x_index = max(x_index,1);
x_index = min(x_index,cmap_size);
% read rgb values from colormap
x_rgb = cmap(x_index,:);
% plot rgb breakdown of x values; this should fall onto rgbplot(colormap)
hold on;
plot(x,x_rgb(:,1),'ro');
plot(x,x_rgb(:,2),'go');
plot(x,x_rgb(:,3),'bo');
axis([c_range 0 1]);
xlabel('Value');
ylabel('RGB component');
With the following result:
I have a d1×d2 array A of integer values and want to color code display them on the xy-plane in a rectangle scaled to d1×d2 using colors that match the magnitude of the value of array at that location. I also want to display the color chart which indicates which color is which magnitude as in the following figure:-
Is there a simple code that can do this?
Or is this kind of charting need special packages?
Will this work ('A' is matrix with non-negative entries)?
function plot2Ddistprf(A, Length, Breadth)
Amax=max(A(:));
A=A/Amax;
G1 = linspace(0,Length,size(A,1));
G2 = linspace(0,Breadth,size(A,2));
[X,Y] = meshgrid(G1,G2);
% plot data
figure; % create a new figure
contourf(X,Y,A); % plot data as surface
caxis([1,100]); % set limits of colormap
colorbar; % display the colorbar
No external library or special package is needed to create such a plot. You can use contourf to plot the data. Then, set the colormap to gray. With caxis you can control the range of colors. colorbar shows the bar on the right side.
The result looks like this:
Here is the code:
% generate sample data
d1 = linspace(-3,3,200);
d2 = linspace(-3,3,200);
[X,Y] = meshgrid(d1,d2);
A = -abs(peaks(X,Y))+100;
% plot data
figure; % create a new figure
contourf(X,Y,A); % plot data as surface
colormap(gray); % use gray colormap
caxis([91,100]); % set limits of colormap
colorbar; % display the colorbar
title('The Title');
xlabel('y');
ylabel('x');
Try the contourf function and then add the colorbar
contourf(A)
colorbar
I want to plot a confusion matrix in MATLAB. Here's my code;
data = rand(3, 3)
imagesc(data)
colormap(gray)
colorbar
When I run this, a confusion matrix with a color bar is shown. But usually, I have seen confusion matrix in MATLAB will give counts as well as probabilities. How can I get them? How can I change the class labels which will be shown as 1,2,3, etc.?
I want a matrix like this:
If you do not have the neural network toolbox, you can use plotConfMat. It gets you the following result.
I have also included an independent example below without the need for the function:
% sample data
confmat = magic(3);
labels = {'Dog', 'Cat', 'Horse'};
numlabels = size(confmat, 1); % number of labels
% calculate the percentage accuracies
confpercent = 100*confmat./repmat(sum(confmat, 1),numlabels,1);
% plotting the colors
imagesc(confpercent);
title('Confusion Matrix');
ylabel('Output Class'); xlabel('Target Class');
% set the colormap
colormap(flipud(gray));
% Create strings from the matrix values and remove spaces
textStrings = num2str([confpercent(:), confmat(:)], '%.1f%%\n%d\n');
textStrings = strtrim(cellstr(textStrings));
% Create x and y coordinates for the strings and plot them
[x,y] = meshgrid(1:numlabels);
hStrings = text(x(:),y(:),textStrings(:), ...
'HorizontalAlignment','center');
% Get the middle value of the color range
midValue = mean(get(gca,'CLim'));
% Choose white or black for the text color of the strings so
% they can be easily seen over the background color
textColors = repmat(confpercent(:) > midValue,1,3);
set(hStrings,{'Color'},num2cell(textColors,2));
% Setting the axis labels
set(gca,'XTick',1:numlabels,...
'XTickLabel',labels,...
'YTick',1:numlabels,...
'YTickLabel',labels,...
'TickLength',[0 0]);
If you have the neural network toolbox you can use the function plotconfusion. You can create a copy and edit it to customise it further, for example to print custom labels.
Let's say I have 9 MxN black and white images that are in some way related to one another (i.e. time lapse of some event). What is a way that I can display all of these images on one surface plot?
Assume the MxN matrices only contain 0's and 1's. Assume the images simply contain white lines on a black background (i.e. pixel value == 1 if that pixel is part of a line, 0 otherwise). Assume images are ordered in such a way as to suggest movement progression of line(s) in subsequent images. I want to be able to see a "side-view" (or volumetric representation) of these images which will show the surface that a particular line "carves out" in its movement across the images.
Coding is done in MATLAB. I have looked at plot (but it only does 2D plots) and surf, which does 3D plots but doesn't work for my MxNx9 matrix of images. I have also tried to experiment with contourslice, but not sure what parameters to pass it.
Thanks!
Mariya
Are these images black and white with simple features on a "blank" field, or greyscale, with more dense information?
I can see a couple of approaches.
You can use movie() to display a sequence of images as an animation.
For a static view of sparse, simple data, you could plot each image as a separate layer in a single figure, giving each layer a different color for the foreground, and using AlphaData to make the background transparent so all the steps in the sequenc show through. The gradient of colors corresponds to position in the image sequence. Here's an example.
function plotImageSequence
% Made-up test data
nLayers = 9;
x = zeros(100,100,nLayers);
for i = 1:nLayers
x(20+(3*i),:,i) = 1;
end
% Plot each image as a "layer", indicated by color
figure;
hold on;
for i = 1:nLayers
layerData = x(:,:,i);
alphaMask = layerData == 1;
layerData(logical(layerData)) = i; % So each layer gets its own color
image('CData',layerData,...
'AlphaData',alphaMask,...
'CDataMapping','scaled');
end
hold off
Directly showing the path of movement a "line" carves out is hard with raster data, because Matlab won't know which "moved" pixels in two subsequent images are associated with each other. Don't suppose you have underlying vector data for the geometric features in the images? Plot3() might allow you to show their movement, with time as the z axis. Or you could use the regular plot() and some manual fiddling to plot the paths of all the control points or vertexes in the geometric features.
EDIT: Here's a variation that uses patch() to draw each pixel as a little polygon floating in space at the Z level of its index in the image sequence. I think this will look more like the "surface" style plots you are asking for. You could fiddle with the FaceAlpha property to make dense plots more legible.
function plotImageSequencePatch
% Made-up test data
nLayers = 6;
sz = [50 50];
img = zeros(sz(1),sz(2),nLayers);
for i = 1:nLayers
img(20+(3*i),:,i) = 1;
end
% Plot each image as a "layer", indicated by color
% With each "pixel" as a separate patch
figure;
set(gca, 'XLim', [0 sz(1)]);
set(gca, 'YLim', [0 sz(2)]);
hold on;
for i = 1:nLayers
layerData = img(:,:,i);
[x,y] = find(layerData); % X,Y of all pixels
% Reshape in to patch outline
x = x';
y = y';
patch_x = [x; x+1; x+1; x];
patch_y = [y; y; y+1; y+1];
patch_z = repmat(i, size(patch_x));
patch(patch_x, patch_y, patch_z, i);
end
hold off