How can I individually colour the labels of a dendrogram so that they match the colours of the clusters in MATLAB?
Here is an example desired output generated using the code in my answer below (note the lables are just the 50 charater series 'A':'r'):
If there is a more straightforward way to do this, please do post an answer as I was unable to find the solution to this by googling. If not, the code is below for posterity.
I could not find a definitive answer to this but I managed to piece the following together from a couple of ideas (shown in the comments) I found online. Hopefully this is useful to someone.
I'm assuming that your data you are clustering is in the matrix data and that labels are stored in a cell array called labels:
%% Hierarchical clustering
T = linkage(data,'average','spearman');
D = pdist(data, 'spearman');
leafOrder = optimalleaforder(T, D);
th = 0.726;
H = dendrogram(T, 0,'ReOrder', leafOrder, 'Orientation', 'left', 'ColorThreshold', th);
h = gca;
set(h, 'YTickLabel', labels(leafOrder));
%Changing the colours
%First get a list of the colours of each line object
lineColours = cell2mat(get(H,'Color'));
colourList = unique(lineColours, 'rows');
% For each cluster (i.e. for each unique colour)
for colour = 1:size(colourList,1)
% see http://stackoverflow.com/a/16677119/1011724 for the idea of
% copying the axis
ax = copyobj(gca, gcf);
% see http://undocumentedmatlab.com/blog/customizing-axes-rulers for
% more on YRuler. This might not work on older versions of MATLAB.
yruler = ax.YRuler;
rgb = floor(colourList(colour,:)'*255);
% Make all the datalabels of the new axis the current colour. (We will
% later make those labels that aren't this colour empty.)
yruler.TickLabels.ColorData = uint8([rgb;255]);
% Might not be necessary, but stopped me getting errors
pause(0.1)
% The hard bit is figuring out which line object matches which label
% Note that there might be an easier way if you are willing to alter your dendrogram.m file: http://www.mathworks.com/matlabcentral/newsreader/view_thread/134997
idx = ismember(lineColours, colourList(colour,:), 'rows');
clusterNodes = [T(idx,1);T(idx,2)];
% Cluster nodes greater than the number of data points are none terminal
% nodes and thus not of interest.
[~,c]=find(bsxfun(#eq,clusterNodes(clusterNodes < length(labels)+1),leafOrder))
% Convert to a logical index
idx = ~ismember(1:(size(lineColours,1)+1), c);
n = sum(idx);
% Set the labels we don't want to colour (this iteration) to be empty
% char arrays.
yruler.TickLabels.String(idx) = mat2cell(repmat(char(),n,1),zeros(n,1),0);
end
Related
Given a .fig file of a Matlab boxplot (i.e. underlying data not available), is it possible to change the PlotStyle attribute (from 'traditional' to 'compact')?
This question is kind of tricky because not like other graphic objects in Matlab, boxplot is a group of lines. As so, all the properties that are set while you create it are inaccessible (and in fact does not exist) after plotting.
One option to deal with that is to create a 'dummy' boxplot, and then alter it to your data. Because boxplot has no simple properties of XData and YData, at least not as we use to them, it takes some work to do that.
Here is a short code to demonstrate that:
% this is just to make a figure for example:
X = normrnd(10,1,100,1);
boxplot(X) % this is the 'Traditional' figure that you load
% you start here, after you load your figure:
bx = findobj('tag','boxplot');
% get the properties of the axes:
axlimx = bx.Parent.XLim;
axlimy = bx.Parent.YLim;
% get all needed properties for plotting compact box plot
txt = bx.Parent.XAxis.TickLabels;
med = get(findobj(bx,'tag','Median'),'YData'); % Median
out = get(findobj(bx,'tag','Outliers'),'YData'); % Outliers
box = get(findobj(bx,'tag','Box'),'YData'); % the Box
whis = cell2mat(get([findobj(bx,'tag','Lower Whisker')...
findobj(bx,'tag','Upper Whisker')],'YData')); % Whisker
minmax = #(R) [min(R(:)) max(R(:))]; % helper function
close all
% Now we closed the original figure, and create a new one for manipulation:
boxplot(normrnd(10,1,100,1),'PlotStyle','Compact');
bxc = findobj('tag','boxplot');
% set the properties of the axes:
bxc.Parent.XLim = axlimx;
bxc.Parent.YLim = axlimy;
% set all properties of the compact box plot:
bxc.Children(1).String = txt;
set(bxc.Children(2),'YData',out) % Outliers
set(bxc.Children(3:4),'YData',med(1)) % MedianInner & MedianOuter
set(bxc.Children(5),'YData',minmax(box)) % the Box
set(bxc.Children(6),'YData',minmax(whis)) % Whisker
Another way to alter the boxplot to 'compact' style, is to change the graphics directly. In this case, we don't create a new dummy figure but work on the loaded figure.
Here is a code for that approach:
% this is just to make a figure for example:
X = normrnd(10,1,100,1);
boxplot(X) % this is the 'Traditional' figure that you load
% you start here, after you load your figure:
bx = findobj('tag','boxplot');
minmax = #(R) [min(R(:)) max(R(:))]; % helper function
% get the whisker limits:
whis = cell2mat(get([findobj(bx,'tag','Lower Whisker')...
findobj(bx,'tag','Upper Whisker')],'YData')); % Whisker
set(findobj(bx,'tag','Upper Whisker'),{'YData','Color','LineStyle'},...
{minmax(whis),'b','-'})
% set the median:
set(findobj(bx,'tag','Median'),{'XData','YData','LineStyle','Marker',...
'Color','MarkerSize','MarkerFaceColor'},...
{1,min(get(findobj(bx,'tag','Median'),'YData')),'none','o','b',6,'auto'});
% set the box:
set(findobj(bx,'tag','Box'),{'XData','YData','LineWidth'},...
{[1 1],minmax(get(findobj(bx,'tag','Box'),'YData')),4});
im_med = copyobj(findobj(bx,'tag','Median'),bx);
im_med.Marker = '.';
% set the outliers:
out = get(findobj(bx,'tag','Outliers'),'YData'); % Outliers
set(findobj(bx,'tag','Outliers'),{'XData','LineStyle','Marker','MarkerEdgeColor',...
'MarkerSize','MarkerFaceColor'},{0.9+0.2*rand(size(out)),'none','o','b',4,'none'});
% rotate x-axis labels:
bx.Parent.XAxis.TickLabelRotation = 90;
% delete all the rest:
delete(findobj(bx,'tag','Lower Whisker'))
delete(findobj(bx,'tag','Lower Adjacent Value'))
delete(findobj(bx,'tag','Upper Adjacent Value'))
To be exact I need the four end points of the road in the image below.
I used find[x y]. It does not provide satisfying result in real time.
I'm assuming the images are already annotated. In this case we just find the marked points and extract coordinates (if you need to find the red points dynamically through code, this won't work at all)
The first thing you have to do is find a good feature to use for segmentation. See my SO answer here what-should-i-use-hsv-hsb-or-rgb-and-why for code and details. That produces the following image:
we can see that saturation (and a few others) are good candidate colors spaces. So now you must transfer your image to the new color space and do thresholding to find your points.
Points are obtained using matlab's region properties looking specifically for the centroid. At that point you are done.
Here is complete code and results
im = imread('http://i.stack.imgur.com/eajRb.jpg');
HUE = 1;
SATURATION = 2;
BRIGHTNESS = 3;
%see https://stackoverflow.com/questions/30022377/what-should-i-use-hsv-hsb-or-rgb-and-why/30036455#30036455
ViewColoredSpaces(im)
%convert image to hsv
him = rgb2hsv(im);
%threshold, all rows, all columns,
my_threshold = 0.8; %determined empirically
thresh_sat = him(:,:,SATURATION) > my_threshold;
%remove small blobs using a 3 pixel disk
se = strel('disk',3');
cleaned_sat = imopen(thresh_sat, se);% imopen = imdilate(imerode(im,se),se)
%find the centroids of the remaining blobs
s = regionprops(cleaned_sat, 'centroid');
centroids = cat(1, s.Centroid);
%plot the results
figure();
subplot(2,2,1) ;imshow(thresh_sat) ;title('Thresholded saturation channel')
subplot(2,2,2) ;imshow(cleaned_sat);title('After morpphological opening')
subplot(2,2,3:4);imshow(im) ;title('Annotated img')
hold on
for (curr_centroid = 1:1:size(centroids,1))
%prints coordinate
x = round(centroids(curr_centroid,1));
y = round(centroids(curr_centroid,2));
text(x,y,sprintf('[%d,%d]',x,y),'Color','y');
end
%plots centroids
scatter(centroids(:,1),centroids(:,2),[],'y')
hold off
%prints out centroids
centroids
centroids =
7.4593 143.0000
383.0000 87.9911
435.3106 355.9255
494.6491 91.1491
Some sample code would make it much easier to tailor a specific solution to your problem.
One solution to this general problem is using impoint.
Something like
h = figure();
ax = gca;
% ... drawing your image
points = {};
points = [points; impoint(ax,initialX,initialY)];
% ... generate more points
indx = 1 % or whatever point you care about
[currentX,currentY] = getPosition(points{indx});
should do the trick.
Edit: First argument of impoint is an axis object, not a figure object.
I have got a cell, which is like this : Data={[2,3],[5,6],[1,4],[6,7]...}
The number in every square brackets represent x and y of a point respectively. There will be a new coordinate into the cell in every loop of my algorithm.
I want to plot these points into a time-changing curve, which will tell me the trajectory of the point.
As a beginner of MATLAB, I have no idea of this stage. Thanks for your help.
Here is some sample code to get you started. It uses some basic Matlab functionalities that you will hopefully find useful as you continue using it. I added come data points to you cell array for illustrative purposes.
The syntax to access elements into the cell array might seem weird but is important. Look here for details about cell array indexing.
In order to give nice colors to the points, I generated an array based on the jet colormap built-in in Matlab. Basically issuing the command
Colors = jet(N)
create a N x 3 matrix in which every row is a 3-element color ranging from blue to red. That way you can see which points were detected before other (i.e. blue before red). Of course you can change that to anything you want (look here if you're interested).
So here is the code. If something is unclear please ask for clarifications.
clear
clc
%// Get data
Data = {[2,3],[5,6],[1,4],[6,7],[8,1],[5,2],[7,7]};
%// Set up a matrix to color the points. Here I used a jet colormap
%// available from MATLAB but that could be anything.
Colors = jet(numel(Data));
figure;
%// Use "hold all" to prevent the content of the figure to be overwritten
%// at every iterations.
hold all
for k = 1:numel(Data)
%// Note the syntax used to access the content of the cell array.
scatter(Data{k}(1),Data{k}(2),60,Colors(k,:),'filled');
%// Trace a line to link consecutive points
if k > 1
line([Data{k-1}(1) Data{k}(1)],[Data{k-1}(2) Data{k}(2)],'LineStyle','--','Color','k');
end
end
%// Set up axis limits
axis([0 10 0 11])
%// Add labels to axis and add a title.
xlabel('X coordinates','FontSize',16)
ylabel('Y coordinates','FontSize',16)
title('This is a very boring title','FontSize',18)
Which outputs the following:
This would be easier to achieve if all of your data was stored in a n by 2 (or 2 by n) matrix. In this case, each row would be a new entry. For example:
Data=[2,3;
5,6;
1,4;
6,7];
plot(Data(:, 1), Data(:, 2))
Would plot your points. Fortunately, Matlab is able to handle matrices which grow on every iteration, though it is not recommended.
If you really wanted to work with cells, there are a couple of ways you could do it. Firstly, you could assign the elements to a matrix and repeat the above method:
NumPoints = numel(Data);
DataMat = zeros(NumPoints, 2);
for I = 1:NumPoints % Data is a cell here
DataMat(I, :) = cell2mat(Data(I));
end
You could alternatively plot the elements straight from the cell, though this would limit your plot options.
NumPoints = numel(Data);
hold on
for I = 1:NumPoints
point = cell2mat(Data(I));
plot(point(1), point(2))
end
hold off
With regards to your time changing curve, if you find that Matlab starts to slow down after it stores lots of points, it is possible to limit your viewing window in time with clever indexing. For example:
index = 1;
SamplingRate = 10; % How many times per second are we taking a sample (Hertz)?
WindowTime = 10; % How far into the past do we want to store points (seconds)?
NumPoints = SamplingRate * WindowTime
Data = zeros(NumPoints, 2);
while running
% Your code goes here
Data(index, :) = NewData;
index = index + 1;
index = mod(index-1, NumPoints)+1;
plot(Data(:, 1), Data(:, 2))
drawnow
end
Will store your data in a Matrix of fixed size, meaning Matlab won't slow down.
I have a dataset the red line.
I'm trying to find the minimum points highlighted in yellow if I take the reflection/mirror image of a data set.
See example code / plot below I'm trying to find a way to find the minimum points highlighted in yellow of the reflection/mirror image of a dataset (the blue line) that is below the reflection line (the black line).
Please note this is just a simple dataset there will be much larger datasets around 100000+
PS: I'm using Octave 3.8.1 which is like matlab
clear all,clf, clc,tic
x1=[0.;2.04;4.08;6.12;8.16;10.2;12.24;14.28;16.32;18.36]
y1=[2;2.86;4;2;1;4;5;2;7;1]
x2=[0.;2.04;4.08;6.12;8.16;10.2;12.24;14.28;16.32;18.36]
y2=abs(y1-max(y1));
data1 = y2;
reflection_line=max(y1)/2
[pks3 idx3] = findpeaks(data1,"DoubleSided","MinPeakHeight",0.1);
line([min(x1) max(x1)], [reflection_line reflection_line]);
hold on;
plot(x1,reflection_line)
hold on;
plot(x1,y1,'-r',x2,y2,'-b')
I am not reflecting your original data, but rather find the local maxima of the original values, that are larger than your given line.
Using a DIY alternative to findpeaks:
A value is a local maximum, if it's larger than (or equal to) its predecessor and successor.
%% Setup
x1 = [0.;2.04;4.08;6.12;8.16;10.2;12.24;14.28;16.32;18.36];
y1 = [2;2.86;4;2;1;4;5;2;7;1];
reflection_line = max(y1)/2;
%% Sort by x value
[x1, I] = sort(x1);
y1 = y1(I);
%% Compute peaks
maxima = #(y) [true; y(2:end)>=y(1:end-1)] & ... % Value larger than predecessor
[y(1:end-1)>=y(2:end); true]; % Value larger than successor
maximaLargerThanLine = maxima(y1) & (y1>reflection_line);
%% Plotting
plot(x1,y1);
hold on;
plot(x1(maximaLargerThanLine),y1(maximaLargerThanLine),'rx');
line([min(x1) max(x1)], [reflection_line reflection_line]);
I'm trying to find a way to nicely plot my measurement data of digital signals.
So I have my data available as csv and mat file, exported from an Agilent Oscilloscope. The reason I'm not just taking a screen shot of the Oscilloscope screen is that I need to be more flexible (make several plots with one set of data, only showing some of the lines). Also I need to be able to change the plot in a month or two so my only option is creating a plot from the data with a computer.
What I'm trying to achieve is something similar to this picture:
The only thing missing on that pic is a yaxis with 0 and 1 lines.
My first try was to make a similar plot with Matlab. Here's what I got:
What's definitely missing is that the signal names are right next to the actual line and also 0 and 1 ticks on the y-axis.
I'm not even sure if Matlab is the right tool for this and I hope you guys can give me some hints/a solution on how to make my plots :-)
Here's my Matlab code:
clear;
close all;
clc;
MD.RAW = load('Daten/UVLOT1 debounced 0.mat'); % get MeasurementData
MD.N(1) = {'INIT\_DONE'};
MD.N(2) = {'CONF\_DONE'};
MD.N(3) = {'NSDN'};
MD.N(4) = {'NRST'};
MD.N(5) = {'1V2GD'};
MD.N(6) = {'2V5GD'};
MD.N(7) = {'3V3GD'};
MD.N(8) = {'5VGD'};
MD.N(9) = {'NERR'};
MD.N(10) = {'PGD'};
MD.N(11) = {'FGD'};
MD.N(12) = {'IGAGD'};
MD.N(13) = {'GT1'};
MD.N(14) = {'NERRA'};
MD.N(15) = {'GT1D'};
MD.N(16) = {'GB1D'};
% concat vectors into one matrix
MD.D = [MD.RAW.Trace_D0, MD.RAW.Trace_D1(:,2), MD.RAW.Trace_D2(:,2), MD.RAW.Trace_D3(:,2), ...
MD.RAW.Trace_D4(:,2), MD.RAW.Trace_D5(:,2), MD.RAW.Trace_D6(:,2), MD.RAW.Trace_D7(:,2), ...
MD.RAW.Trace_D8(:,2), MD.RAW.Trace_D9(:,2), MD.RAW.Trace_D10(:,2), MD.RAW.Trace_D11(:,2), ...
MD.RAW.Trace_D12(:,2), MD.RAW.Trace_D13(:,2), MD.RAW.Trace_D14(:,2), MD.RAW.Trace_D15(:,2)];
cm = hsv(size(MD.D,2)); % make colormap for plot
figure;
hold on;
% change timebase to ns
MD.D(:,1) = MD.D(:,1) * 1e9;
% plot lines
for i=2:1:size(MD.D,2)
plot(MD.D(:,1), MD.D(:,i)+(i-2)*1.5, 'color', cm(i-1,:));
end
hold off;
legend(MD.N, 'Location', 'EastOutside');
xlabel('Zeit [ns]'); % x axis label
title('Messwerte'); % title
set(gca, 'ytick', []); % hide y axis
Thank you guys for your help!
Dan
EDIT:
Here's a pic what I basically want. I added the signal names via text now the only thing that's missing are the 0, 1 ticks. They are correct for the init done signal. Now I just need them repeated instead of the other numbers on the y axis (sorry, kinda hard to explain :-)
So as written in my comment to the question. For appending Names to each signal I would recommend searching the documentation of how to append text to graph. There you get many different ways how to do it. You can change the position (above, below) and the exact point of data. As an example you could use:
text(x_data, y_data, Var_Name,'VerticalAlignment','top');
Here (x_data, y_data) is the data point where you want to append the text and Var_Name is the name you want to append.
For the second question of how to get a y-data which contains 0 and 1 values for each signal. I would do it by creating your signal the way, that your first signal has values of 0 and 1. The next signal is drawn about 2 higher. Thus it changes from 2 to 3 and so on. That way when you turn on y-axis (grid on) you get values at each integer (obviously you can change that to other values if you prefer less distance between 2 signals). Then you can relabel the y-axis using the documentation of axes (check the last part, because the documentation is quite long) and the set() function:
set(gca, 'YTick',0:1:last_entry, 'YTickLabel',new_y_label(0:1:last_entry))
Here last_entry is 2*No_Signals-1 and new_y_label is an array which is constructed of 0,1,0,1,0,....
For viewing y axis, you can turn the grid('on') option. However, you cannot chage the way the legends appear unless you resize it in the matlab figure. If you really want you can insert separate textboxes below each of the signal plots by using the insert ->Textbox option and then change the property (linestyle) of the textbox to none to get the exact same plot as above.
This is the end result and all my code, in case anybody else wants to use the good old ctrl-v ;-)
Code:
clear;
close all;
clc;
MD.RAW = load('Daten/UVLOT1 debounced 0.mat'); % get MeasurementData
MD.N(1) = {'INIT\_DONE'};
MD.N(2) = {'CONF\_DONE'};
MD.N(3) = {'NSDN'};
MD.N(4) = {'NRST'};
MD.N(5) = {'1V2GD'};
MD.N(6) = {'2V5GD'};
MD.N(7) = {'3V3GD'};
MD.N(8) = {'5VGD'};
MD.N(9) = {'NERR'};
MD.N(10) = {'PGD'};
MD.N(11) = {'FGD'};
MD.N(12) = {'IGAGD'};
MD.N(13) = {'GT1'};
MD.N(14) = {'NERRA'};
MD.N(15) = {'GT1D'};
MD.N(16) = {'GB1D'};
% concat vectors into one matrix
MD.D = [MD.RAW.Trace_D0, MD.RAW.Trace_D1(:,2), MD.RAW.Trace_D2(:,2), MD.RAW.Trace_D3(:,2), ...
MD.RAW.Trace_D4(:,2), MD.RAW.Trace_D5(:,2), MD.RAW.Trace_D6(:,2), MD.RAW.Trace_D7(:,2), ...
MD.RAW.Trace_D8(:,2), MD.RAW.Trace_D9(:,2), MD.RAW.Trace_D10(:,2), MD.RAW.Trace_D11(:,2), ...
MD.RAW.Trace_D12(:,2), MD.RAW.Trace_D13(:,2), MD.RAW.Trace_D14(:,2), MD.RAW.Trace_D15(:,2)];
cm = hsv(size(MD.D,2)); % make colormap for plot
figure;
hold on;
% change timebase to ns
MD.D(:,1) = MD.D(:,1) * 1e9;
% plot lines
for i=2:1:size(MD.D,2)
plot(MD.D(:,1), MD.D(:,i)+(i-2)*2, 'color', cm(i-1,:));
text(MD.D(2,1), (i-2)*2+.5, MD.N(i-1));
end
hold off;
%legend(MD.N, 'Location', 'EastOutside');
xlabel('Zeit [ns]'); % x axis label
title('Messwerte'); % title
% make y axis and grid the way I want it
set(gca, 'ytick', 0:size(MD.D,2)*2-3);
grid off;
set(gca,'ygrid','on');
set(gca, 'YTickLabel', {'0'; '1'});
ylim([-1,(size(MD.D,2)-1)*2]);