I'm trying to plot several signals in one graph and i would like to restrict them and sort of minimize it so all my signals will be clear (more or less).
I have no idea how to do it. I'm adding an image so what i need to do will be clearer.
My data changes but in general it's the mean intensity of each column of a certain area in an intensity image.I tried to do it like with the same idea as you but i don't get the right plot as i wanted. A is the relevant matrix,b is the matrix with shifted values:
for i=1:20
b(i,:)=A(i,:)+(100*i);
plot(b(i,:))
hold on
end
I will also add 2 images: one is the plot of all the 20 signals that i get and the other one is the plot of only the first signal. I don't understand why do they look so different.
You can try something like that :
x = [1:100]; %Distance 1 to 100
y = F(x) % Your first function (signal)
y2 = 0.5*G(x) % Your second function (signal)
plot(x,y,x,y2); % plot both function in a single plot.
hleg1 = legend('Intensity t1,'Intensity t27');
So you have your signal at intensity t27 half cut for each value ( 0.5 ), so it shift down.
Related
Is it possible to make multiple vertical histograms plot in Matlab into one? Much like the excel sheet enclosed ( https://drive.google.com/file/d/1H_mbyrIoln3XrnK1hLajnVNBKn13y_np/view?usp=sharing )
I want to make a plot of many vertical histogram plots into one figure, by importing excel-files, where on the y axis it has the elevation, the x axis the distance between the histogram vertical lines and the length of the histogram bars is the values in the excel sheet. The vertical height of each bar is 5.
Is this even possible? I have to put in a number of conditions for Matlab to know where to plot, but could some one show me the basic methodology?
Help would be very much appreciated!
The problem is that the parent of a Baseline object is the Axis, which prevents us from doing something like
barh(bins1,counts1,'Basevalue',baseline1); hold on;
barh(bins2,counts2,'Basevalue',baseline2); hold off;
because the plots will automatically share the second baseline value set. There might be a workaround for this that I do not know of, so I invite anybody who knows it to show me how its done.
For now, I was able to sort-of replicate the plot you posted a picture of in a much less elegant way. I will post code below, but before I do, I would like to argue against the use of a plot like this. Why? Because I think it is confusing, as the x-axis both relates to the plot number as well as the bin count numbers. You are in fact trying to display a 3-D data set, the three dimensions being bins, bin counts, and 'histogram number'. A plethora of methods exist for displaying 3-D data, and a series of 2-D histograms may not be the best way to go.
That being said, here is a code that more-or-less creates the picture above, as promised. Any changes you may want to make will be more cumbersome than usual :-)
testData = randn(10000,1); % Generate some data
[counts,bins] = hist(testData); % Bin the data
% First histogram
baseline1 = 0;
p1=subplot(1,3,1); barh(bins,counts,'BaseValue',baseline1);
xticks(baseline1); xticklabels({0}); % Graph number on x axis at baseline (0)
box off; % Remove box on right side of plot
ylabel('Property');
% Second histogram
baseline2 = max(counts)*1.2;
sepdist = baseline2-baseline1; % Distance that separates two baselines
counts2 = baseline2 + counts;
p2=subplot(1,3,2); barh(bins,counts2,'BaseValue',baseline2)
xticks(baseline2); xticklabels({1}); % Graph number on x axis at baseline
box off;
Y=gca; Y.YAxis.Visible='off';
p1p=p1.Position; p2p=p2.Position;
p2p(1)=p1p(1)+p1p(3); p2.Position=p2p; % Move subplot so they touch
% Third histogram
baseline3 = baseline2 + sepdist;
counts3 = baseline3+counts;
p3=subplot(1,3,3); barh(bins,counts3,'BaseValue',baseline3)
xticks(baseline3); xticklabels({2});
Y=gca; Y.YAxis.Visible='off';
box off
p3p=p3.Position;
p3p(1)=p2p(1)+p2p(3); p3.Position=p3p;
% Add x-label when you are done:
xl=xlabel('Test xlabel'); xl.Units='normalized';
% Fiddle around with xl.Position(1) until you find a good centering:
xl.Position(1) = -0.49;
Result:
Is there a way to only plot half the nyquist plot in MATLAB? Nyquist usually has the two lines that go in opposite directions (one going up, and one going down). I only want to plot the one going down.
I know that I can only show the negative axis to "hide" the positive bit of the plot, but I want to show the whole chart, but only have the one line:
Okay, I got the answer. Use nyquistplot instead of nyquist and set the option ShowFullContour to off:
% This is an example contour
G = tf(80, [1 9 30 40]);
h = nyquistplot(G);
setoptions(h, 'ShowFullContour', 'off');
I want to assign vector to a contourf graph, in order to show the direction and magnitude of wind.
For this I am using contourf(A) and quiver(x,y), where as A is a matrix 151x401 and x,y are matrices with the same sizes (151x401) with magnitude and direction respectively.
When I am using large maps i get the position of the arrows but they are to densily placed and that makes the graph look bad.
The final graph has the arrows as desired, but they are to many of them and too close, I would like them to be more scarce and distributed with more gap between them, so as to be able to increase their length and at the same time have the components of the contour map visible.
Can anyone help , any pointers would be helpful
i know its been a long time since the question was asked, but i think i found a way to make it work.
I attach the code in case someone encounters the same issues
[nx,ny]= size(A) % A is the matrix used as base
xx=1:1:ny; % set the x-axis to be equal to the y
yy=1:1:nx; % set the y-axis to be equal to the x
contourf(xx,yy,A)
hold on, delta = 8; %delta is the distance between arrows)
quiver(xx(1:delta:end),yy(1:delta:end),B(1:delta:end,1:delta:end),C(1:delta:end,1:delta:end),1) % the 1 at the end is the size of the arrows
set(gca,'fontsize',12);, hold off
A,B,C are the corresponding matrices ones want to use
I am trying to plot a dataset and want to see a small portion of the plot in the display. The problem is that the dataset is huge and when I am running the algorithm on the whole dataset the significant change in the plot is not clear (visually). Thats why I want to run the algorithm on the whole dataset and want to view a portion of the resulting plot in the display, say 10% of the plot from the middle. Can anyone please help me how to cut the M-figure from the middle - 10% of the original plot? Thanks in advance.
Suppose you're plotting x.
L = length(x);
fraction = 0.1; %#plot 10% of signal
n = round(L*fraction); %#number of samples/points to plot
offset = 0.5 %#start plotting at 50% of the signal (middle)
s = round(L*offset) %#number of samples/points to skip before plotting
t = s:s+n-1; %#discrete 'time' vector, so you know where you are on the plot
plot(t,x(t)); %#plot the selected signal portion
Do xlim, ylim and zlim do what you want?
I've got a series of XY point pairs in MATLAB. These pairs describe points around a shape in an image; they're not a function, meaning that two or more y points may exist for each x value.
I can plot these points individually using something like
plot(B(:,1),B(:,2),'b+');
I can also use plot to connect the points:
plot(B(:,1),B(:,2),'r');
What I'm trying to retrieve are my own point values I can use to connect the points so that I can use them for further analysis. I don't want a fully connected graph and I need something data-based, not just the graphic that plot() produces. I'd love to just have plot() generate these points (as it seems to do behind the scenes), but I've tried using the linseries returned by plot() and it either doesn't work as I understand it or just doesn't give me what I want.
I'd think this was an interpolation problem, but the points don't comprise a function; they describe a shape. Essentially, all I need are the points that plot() seems to calculate; straight lines connecting a series of points. A curve would be a bonus and would save me grief downstream.
How can I do this in MATLAB?
Thanks!
Edit: Yes, a picture would help :)
The blue points are the actual point values (x,y), plotted using the first plot() call above. The red outline is the result of calling plot() using the second approach above. I'm trying to get the point data of the red outline; in other words, the points connecting the blue points.
Adrien definitely has the right idea: define a parametric coordinate then perform linear interpolation on the x and y coordinates separately.
One thing I'd like to add is another way to define your parametric coordinate so you can create evenly-spaced interpolation points around the entire shape in one pass. The first thing you want to do, if you haven't already, is make sure the last coordinate point reconnects to the first by replicating the first point and adding it to the end:
B = [B; B(1,:)];
Next, by computing the total distance between subsequent points then taking the cumulative sum, you can get a parametric coordinate that makes small steps for points close together and larger steps for points far apart:
distance = sqrt(sum(diff(B,1,1).^2,2)); %# Distance between subsequent points
s = [0; cumsum(distance)]; %# Parametric coordinate
Now, you can interpolate a new set of points that are evenly spaced around the edge along the straight lines joining your points using the function INTERP1Q:
sNew = linspace(0,s(end),100).'; %'# 100 evenly spaced points from 0 to s(end)
xNew = interp1q(s,B(:,1),sNew); %# Interpolate new x values
yNew = interp1q(s,B(:,2),sNew); %# Interpolate new y values
These new sets of points won't necessarily include the original points, so if you want to be sure the original points also appear in the new set, you can do the following:
[sAll,sortIndex] = sort([s; sNew]); %# Sort all the parametric coordinates
xAll = [B(:,1); xNew]; %# Collect the x coordinates
xAll = xAll(sortIndex); %# Sort the x coordinates
yAll = [B(:,2); yNew]; %# Collect the y coordinate
yAll = yAll(sortIndex); %# Sort the y coordinates
EXAMPLE:
Here's an example to show how the above code performs (I use 11 pairs of x and y coordinates, one of which is repeated for the sake of a complete example):
B = [0.1371 0.1301; ... %# Sample data
0.0541 0.5687; ...
0.0541 0.5687; ... %# Repeated point
0.0588 0.5863; ...
0.3652 0.8670; ...
0.3906 0.8640; ...
0.4090 0.8640; ...
0.8283 0.7939; ...
0.7661 0.3874; ...
0.4804 0.1418; ...
0.4551 0.1418];
%# Run the above code...
plot(B(:,1),B(:,2),'b-*'); %# Plot the original points
hold on; %# Add to the plot
plot(xNew,yNew,'ro'); %# Plot xNew and yNew
I'd first define some parametric coordinate along the different segments (i.e. between the data points)
s = 1:size(B,1);
Then, just use interp1 to interpolate in s space. e.g. If you want to generate 10 values on the line between data point 5 and 6 :
s_interp = linspace(5,6,10); % parametric coordinate interpolation values
x_coord = interp1(s,B(:,1),s_interp,'linear');
y_coord = interp1(s,B(:,2),s_interp,'linear');
This should do the trick.
A.
Actually there is a MATLAB function "improfile", which might help you in your problem. Lets say these are the 4 coordinates which you want to find the locations between these coordinates.
xi=[15 30 20 10];
yi=[5 25 30 50];
figure;
plot(xi,yi,'r^-','MarkerSize',12)
grid on
Just generate a random image and run the function
n=50; % total number of points between initial coordinates
I=ones(max([xi(:);yi(:)]));
[cx,cy,c] = improfile(I,xi,yi,n);
hold on, plot(cx,cy,'bs-','MarkerSize',4)
Hope it helps