I have multiple histograms that I would like to overlay on top of each other but I don't know how to do it. I found the code below but I don't know how to modify it to run on a loop instead of just two histograms.
data1 = randn(100,1); % data of one size
data2 = randn(25, 1); % data of another size!
myBins = linspace(-3,3,10); % pick my own bin locations
% Hists will be the same size because we set the bin locations:
y1 = hist(data1, myBins);
y2 = hist(data2, myBins);
% plot the results:
figure(3);
bar(myBins, [y1;y2]');
title('Mixed size result');
or what is a better way of comparing histograms if they are more than 10 or 20.
Your question is very general. Firstly I do not understand why you insist on a for loop.
Personally I don't like the included bar plot. It quickly gets messy (especially since the bars are not at the "original" location)
If you got a lot of histograms I would consider a stairstep plot as it doesn't fill the plot area so much. Or you could come up with your own - eg using transparent patches.
If it get's lots of curves there are many ways to visualize them google for "multivariate visualization" and be amazed. One of the most amusing ways would be Chernoff faces.
it's much easier now:
histogram(data1, myBins);
hold on;
histogram(data2, myBins);
You could do the following, although it's not the only way:
data = cell(1, N);
y = cell(1, N);
yBar = zeros(N, 10);
for i=1:N
data{1, i} = randn(10*round(rand(1,1)), 1);
y{1, i} = hist(data{1, i}, myBins);
yBar(i, :) = y{1, i};
end
yBar = yBar';
figure(3);
bar(myBins, yBar);
title('Mixed size result');
Using the y cell is not obligatory of course, I left it there to actually show what's happening.
I would suggest this. It's simple and does not require for loops:
bar([y1.' y2.'],'stacked')
Here's a way that was useful to me:
I'm plotting a histogram for each column of the matrix ao.
The code was:
for i = 1:size(ao,2)
[h, y] = hist(ao(:,i), linspace(-5,10,100));
h = i + (0.95./max(h(:))) .* h;
barh(y, h, 'BarWidth', 1, 'BaseValue', i, 'LineStyle', 'none');
hold on;
end
grid;
Note that just changing barh to bar will give the same thing but going up-down instead of left-right (i.e. the figure rotated by 90° anti-clockwise).
Related
I want to plot something like this http://www.nature.com/nprot/journal/v9/n6/fig_tab/nprot.2014.090_F7.html or like this one http://file.scirp.org/Html/11-2200285/ff6819f9-5db9-4121-852d-a8d5c302a5a4.jpg I have a 2D matrix.
I tried to plot it like this but did not work
figure;
hold on
for i = 1:size(X,1)
plot(X(i,:)+10)
end
Since you do not specify what exactly does not work, I am having some difficulties to answer your question directly (I do not have enough reputation for a comment).
The following code results in an image like the ones you link. Maybe you forgot to multiply the y-shift with the iteration number i.
N = 200;
x = 1:N;
M = 5;
X = sin(kron(x,ones(M,1)));
figure; hold all;
for i=1:N
plot(X(i,:)+i*5);
end
Is there an easy way to put a bitmap image in the background of a Matlab plot which does not fill the whole available space und keeps its aspect ratio when the figure is resized?
TIA
I'm not quite sure to understand what you mean by
plot which does not fill the whole available space
however the following solution should help you solve your problem (or at least get you started).
Basically read an image (here grayscale) and display it using the imagesc command along with the grayscale colormap, then issue the hold on command and plot the data. Notice that you need to reverse the direction of the x-axis in order to get the right direction for the plot.
Here is the code:
clear
clc
close all
A = imread('cameraman.tif');
x = 1:10;
y = x;
figure
%// Notice the fliplr(A) to reverse the direction of the x data
imagesc([min(x(:)) max(x(:))], [min(y(:)) max(y(:))],fliplr(A));
colormap gray
%// Here reverse the direction of the x axis, otherwise the plot is
%// reversed
set(gca,'XDir','reverse')
hold on
plot(x,y,'--r')
axis off
And the result:
If your background image is RGB, you can use the image function: (modified from answer here): You need to flip the x data from the image for each channel separately, because fliplr only accepts 2D arguments:
DataXImage = linspace(min(x), max(x), size(A, 2));
DataYImage = linspace(min(y), max(y), size(A, 1));
%// flip dimensions for each channel
B = cat(3,fliplr(A(:,:,1)),fliplr(A(:,:,2)),fliplr(A(:,:,3)));
image(DataXImage, DataYImage, B, 'CDataMapping', 'scaled');
which, using the peppers.png image, gives this:
Is this what you had in mind? If not please tell me!
img = imread('myimage.png');
% set the range of the axes
% The image will be stretched to this.
min_x = 0;
max_x = 8;
min_y = 0;
max_y = 6;
% make data to plot - just a line.
x = min_x:max_x;
y = (6/8)*x;
imagesc([min_x max_x], [min_y max_y], img);
hold on;
plot(x,y);
i'm simulating a wave propogation in time and place. i want to make a colormap of its values for every time step, in space. i mean, i want to make a figure of 2 axes (x and y) and displays the wave's values at those points by color (the wave varible is V).
how can i do it?
i'v tried:
for ind1 = 1:length(t)
figure()
trisurf(x1,y1,V(:,ind1),'EdgeColor', 'None', 'facecolor', 'interp');
view(2);
end
but i got a message that z (=V) suppose to be a function and not a scalar.
any suggestions?
I have two options, I don't think they will be perfect, but it might help.
First, interpolate the data onto a rectangular mesh and use contourf:
F=scatteredInterp(x,y,V(:,ind1));
X=linspace(min(x),max(x));
Y=linspace(min(y),max(y));
contourf(X,Y,F(X,Y))
Secondly, use scatter to plot points with varying colour:
scatter(x,y,25,V(:,ind1))
where the 25 controls the size of each marker, you may have to experiment with it.
Hope that gives you some ideas.
i've made a loop that finally works:
clear heart_movie
Vnorm = mat2gray(V(:,1:2000));
x1_new = x1-min(x1)+1;
y1_new = y1-min(y1)+1;
for ind1 = 1:2000
heart = zeros(max(x1_new),max(y1_new));
z = Vnorm(:,ind1);
for ind2 = 1:length(z);
heart(y1_new(ind2),x1_new(ind2))= z(ind2);
end
colormap(jet);
imagesc(flipud(heart));
end
I am doing vlfeat in Matlab and I am following this question here.
These below are my simple testing images:
Left Image:
Right Image:
I did a simple test with 2 simple images here (the right image is just rotated version of the left), and I got the result accordingly:
It works, but I have one more requirement, which is to match the SIFT points of the two images and show them, like this:
I do understand that vl_ubcmatch returns 2 arrays of matched indices, and it is not a problem to map them for which point goes to which point on two images. However, I am currently stuck in matlab's procedure. I found this. But that only works if the subplot stays that way. When you add an image into the subplot, the size changes and the normalization failed.
Here is my code: (im and im2 are images. f, d and f2, d2 are frames and descriptors from vl_sift function from 2 images respectively)
[matches score] = vl_ubcmatch(d,d2,threshold);%threshold originally is 1.5
if (mode >= 2)%verbose 2
subplot(211);
imshow(uint8(im));
hold on;
plot(f(1,matches(1,:)),f(2,matches(1,:)),'b*');
subplot(212);
imshow(uint8(im2));
hold on;
plot(f2(1,matches(2,:)),f2(2,matches(2,:)),'g*');
end
if (mode >= 3)%verbose 3
[xa1 ya1] = ds2nfu( f(1,matches(1,:)), f(2,matches(1,:)));
[xa2 ya2] = ds2nfu( f2(1,matches(2,:)), f2(2,matches(2,:)));
for k=1:numel(matches(1,:))
xxa1 = xa1(1, k);
yya1 = ya1(1, k);
xxa2 = xa2(1, k);
yya2 = ya2(1, k);
annotation('line',[xxa1 xxa2],[yya1 yya2],'color','r');
end
end
The code above yields this:
I think subplot isn't a good way to go for something like this. Is there a better method for this in Matlab? If possible, I want something like an empty panel that I can draw my image, draw lines freely and zoom freely, just like drawing 2D games in OpenGL style.
From zplesivcak's suggestion, yes, it is possible, and not that problematic after all. Here is the code:
% After we have applied vl_sift with 2 images, we will get frames f,f2,
% and descriptor d,d2 of the images. After that, we can apply it into
% vl_ubcmatch to perform feature matching:
[matches score] = vl_ubcmatch(d,d2,threshold); %threshold originally is 1.5
% check for sizes and take longest width and longest height into
% account
if (size(im,1) > size(im2,1))
longestWidth = size(im,1);
else
longestWidth = size(im2,1);
end
if (size(im,2) > size(im2,2))
longestHeight = size(im,2);
else
longestHeight = size(im2,2);
end
% create new matrices with longest width and longest height
newim = uint8(zeros(longestWidth, longestHeight, 3)); %3 cuz image is RGB
newim2 = uint8(zeros(longestWidth, longestHeight, 3));
% transfer both images to the new matrices respectively.
newim(1:size(im,1), 1:size(im,2), 1:3) = im;
newim2(1:size(im2,1), 1:size(im2,2), 1:3) = im2;
% with the same proportion and dimension, we can now show both
% images. Parts that are not used in the matrices will be black.
imshow([newim newim2]);
hold on;
X = zeros(2,1);
Y = zeros(2,1);
% draw line from the matched point in one image to the respective matched point in another image.
for k=1:numel(matches(1,:))
X(1) = f(1, matches(1, k));
Y(1) = f(2, matches(1, k));
X(2) = f2(1, matches(2, k)) + longestHeight; % for placing matched point of 2nd image correctly.
Y(2) = f2(2, matches(2, k));
line(X,Y);
end
Here is the test case:
By modifying the canvas width and height of one of the images from the question, we see that the algorithm above will take care of that and display the image accordingly. Unused area will be black. Furthermore, we see that the algorithm can match the features of two images respectively.
EDIT:
Alternatively, suggested by Maurits, for cleaner and better implementation, check out Lowe SIFT matlab wrappers.
If you have Matlab Computer Vision Library installed on your disc already, you can simply use
M1 = [f(1, match(1, :)); f(2, match(1, :)); ones(1, length(match))];
M2 = [f2(1, match(2, :)); f2(2, match(2, :)); ones(1, length(match))];
showMatchedFeatures(im,im2,[M1(1:2, :)]',[M2(1:2, :)]','montage','PlotOptions',{'ro','g+','b-'} );
I have a 3-dimensional data to be plotted in matlab. The data set are built by stacking 10 exponential curves with different parameters along y directions such as
x = 0:0.01:15;
x0 = 0.5;
y = [beta1, beta2, beta3, beta4, beta5, beta6, beta7, beta8, beta9, beta10];
Z(1, :) = A*exp(-(x-x0).^2/beta1);
Z(2, :) = A*exp(-(x-x0).^2/beta2);
Z(3, :) = A*exp(-(x-x0).^2/beta3);
Z(4, :) = A*exp(-(x-x0).^2/beta4);
...
Z(10, :) = A*exp(-(x-x0).^2/beta10);
% here A could be change based on beta too (no code shown here)
I am trying to plot Z with waterfall except for I don't want the height (i.e. the vertical line) appears on the edge. I don't know if there is any other way to plot the data as waterfall-like curves but without those vertical lines. Thanks
"it is plotted with lines instead of patch with surface".
In other words, you want the boundary lines to be invisible. Well that's no trivial feat as the boundary lines are separate from any color scheme you can directly include. What you need to do is get the data after it drawn then modify it accordingly:
e.g.
[X,Y,Z] = peaks(30);
h = waterfall (X,Y,Z);
CD = get (h, 'CData');
CD(1,:) = nan;
CD(end-2:end,:) = nan;
set (h, 'CData', CD)
note that CD(1,:) is for the "rising" boundary, while CD(end-2:end-1,:) is for the falling boundary, and CD(end,:) is for the bottom.
i know this is an old post, but the below will make the region under the curve transparent:
figure;
[X,Y,Z] = peaks(10);
handle_figure = waterfall( X, Y, Z );
set( handle_figure, 'FaceColor', 'none' );