I have a sequence with data and an offset. I'm asked to plot a stem() graph of the data, starting at the offset. I have figured out the data part (the easy part) and how to change the window to include the offset, but when I plot the graph, it shows the offset with a value of zero and zeros until 1 where the sequence.data will start and plot points.
methods
function s = sequence(data, offset)
s.data = data;
s.offset = offset;
end
function stem(x)
% STEM Display a Matlab sequence, x, using a stem plot.
stem(x.offset,x.data);
axis([x.offset x.offset+length(x.data) 'auto' 'auto']);
end
I need to figure out how to "move" my x.data to my x.offset and start stem plotting there.
I don't understand why you simply can't add an x offset while keeping the y data the same?
For instance, given your example in your comments above:
x = 0:4;
y = 1:5;
This is what the original graph looks like, as well as shifting the graph to the left by 3 (-3):
stem(x,y,'b');
hold on;
stem(x-3,y,'r');
This is what I get:
The blue data is the original, while the red is the shifted instance to the left by 3. As you can see, the y data is the same, but the x points move to the left by 3. What your code is actually doing is that it does not shift the actual data. You are only changing the display range of your stem plot. As such, you should really be doing this:
methods
function s = sequence(data, offset)
s.data = data;
s.offset = offset;
end
function stem(x)
% STEM Display a Matlab sequence, x, using a stem plot.
%// First define sequence from [0,N-1]
vals = 0:numel(x.data)-1;
%// Now use the above and manually shift the x coordinate
stem(vals+x.offset,x.data);
end
I'm going to assume that your data on the x-axis starts counting at 0, and so we will declare a sequence from 0 up to N-1 where N is the total number of elements that you have. Once we declare this sequence, when it's time to draw the stem plot, we simply add an offset to this sequence and use this as the x data. The y data should stay the same.
However, I would argue that creating a custom class for implementing this addition to stem is less readable than what I originally did above. If this is a requirement for whatever you're developing, then certainly go ahead and do it this way, but I don't really think it's necessary.
Related
I make point plots like this one:
But now I need to plot all the lines between the points as well to create rectangular mesh under a deformation (i.e. do the connection to the closest neighbors in x and y direction - not connect all the points with all the points).
How can I convince matlab/octave to do that?
The code I have used is here:
%T,H,W and k are defined above, it doesn't matter for the plot.
for ii=1:2:H
for jj=1:2:W
k=0.1;
x=jj;
y=ii;
U(ii,jj)=7*exp(0.05*(y-H))*cos(k*x-T);
V(ii,jj)=4*exp(0.1*(y-H))*sin(k*x-T);
X(ii,jj)=jj;
Y(ii,jj)=ii;
end
end
plot(X+U,Y+V,'k.');
A plot as you want it is easily done with mesh(X,Y,Z).
The problem with your code is that you have a lot of zeros in your matrices. These might be intentional. In that case I could provide another solution. But mesh() connects neighboring points in a matrix. Therefore having the 0 in every second line and row would connect every point to (0,0). The easiest way is to just let your ii,jj grow in steps of 1.
%T,H,W and k are defined above, it doesn't matter for the plot.
H = 20;
W = 40;
T = 2*pi;
for ii=1:1:H
for jj=1:1:W
k=0.1;
x=jj;
y=ii;
U(ii,jj)=7*exp(0.05*(y-H))*cos(k*x-T);
V(ii,jj)=4*exp(0.1*(y-H))*sin(k*x-T);
X(ii,jj)=jj;
Y(ii,jj)=ii;
end
end
plot(X+U,Y+V,'k.');
hold on
mesh(X+U, Y+V, zeros(size(X)));
So i have this code to obtain radial gravity on Earth in function of the latitude:
G=6.6e-11;
M=5.976e24;
N=1000;
r=6371000;
w=2*pi/(24*3600);
for i=1:1:360
Theta=i*pi/180;
x(i)=i;
Vi(i)=-G*M/(r*r);
Phii(i)=r*w*w*sin(Theta)*sin(Theta);
gr(i)=Vi(i)+Phii(i);
end
plot(x,gr)
And it runs well. I want to make a graph of a circle made of a border of points (representing angle (i)) that change colour according to the value of gr(I want to set ranges of values of gr so that if the value obtained falls in a specific category, the point will have a specific colour).
I'm really new to MATLAB. Is there any possible way to make this?
Thanks in advance.
Here is the basic algorithm that I would do:
Determine how many colours you want to represent in your plot.
Create a colour map that has this many points for what you want to compute.
Determine a linearly increasing vector that varies from the minimum value of gr to the maximum value of gr with as many points as you have determined in Step #2
For each point in gr:
a. Determine which point yields the closest distance of this point to the vector in Step #3
b. Use this to index which colour you want.
c. Convert your angle into Cartesian co-ordinates, then plot this point with the colour found in Step 4b.
Let's tackle each point in detail.
Step #1 - Determine how many colours you want
This is pretty simple. Just determine how many colours you want. For now, let's assume that you want 20 colours, so:
num_colours = 20;
Step #2 - Create a colour map
What we can do is create a 20 x 3 matrix where each row determines a RGB tuple that denotes the amount of red, green and blue that each colour will occupy. MATLAB has built-in colour maps that will help you facilitate this. Here are all of the available colour maps that MATLAB has:
Each colour map has a special variable where you can provide it an integer number, and it'll return this 2D matrix of as many rows as the number you have provided. Each row gives you an RGB triplet which denotes the proportion of red, green and blue respectively. This matrix varies from the beginning of the colour map (top row) to the end (bottom row). All you have to do is use any name seen in the figure I've shown you above to create a colour map of that type. For example, if you wanted to get a bones colour map of 15 points, simply do:
colour_map = bones(15);
If you wanted to get a jet colour map of 25 points, simply do:
colour_map = jet(25);
.... you get the idea right? I like hsv so let's use the HSV colour map. You can use any colour map you want, but let's just stick with HSV for the sake of this example.
As such:
colour_map = hsv(num_colours);
Step #3 - Get that linearly increasing vector
You want certain colours to map into certain ranges, which is why this step is important. Given a value in gr, we want to figure out which colour we want to choose, and all you have to do is determine which value in gr is the closest to a value in this vector in Step #3. Therefore, you can use linspace to do this for you:
bin_vector = linspace(min(gr), max(gr), num_colours);
This will create a num_colours 1D array where the beginning of this array starts at the minimum value of gr and varies up to the maximum value of gr and each value is equally spaced such that we generate a num_colours array.
Step #4 - Bring it all home
Now, for each point in gr, we need to figure out which point is the closest to that vector in Step #3, we then use this to figure out the colour we want, then we need to convert our angle into Cartesian co-ordinates, then plot this point.
For illustration purposes, I'm going to assume your radius is 1. You can figure out how to get the x and y co-ordinates by simply doing cos(theta) and sin(theta), where theta is the angle you are examining. Since your gr array has 360 slots, I'm going to assume a resolution of 1 degree per slot. Therefore, you can easily do this in a for loop. Make sure you use hold on because we are going to call plot multiple times, and we don't want to overwrite the plot each time we call plot. You want all of the points to stay in the plot.
Without further ado:
figure; %// Create blank figure
hold on; %// Remember all points
%// For each point in our array...
for idx = 1 : 360
%// Find the closest slot between gr and our vector in Step #3
[~,min_idx] = min(abs(gr(idx) - bin_vector));
%// Grab this colour
clr = colour_map(min_idx,:);
%// Plot the point with this colour
plot(cosd(idx), sind(idx), '.', 'Color', clr, 'MarkerSize', 10);
end
Take notice that cosd and sind take in degrees as the input argument while cos and sin take in radians. Also, take note that I also changed the size of the point so that it's bigger. With the above logic, and your array in gr, this is what I get:
If you want the radius to get larger, all you have to do is multiply each cosd and sind term with your radius. Therefore, you can do something like this:
radius = 2;
for idx = 1 : 360
... %// Insert colour code here
...
...
%// Now plot
plot(radius*cosd(idx), radius*sind(idx), '.', 'Color', clr, 'MarkerSize', 10);
end
Just leave the code the same, but for the plot command, just multiply each x and y value by the radius.
Minor note in efficiency
The way you're calculating your gr array is using an inefficient for loop. There are some situations (like mine above) where you need to use a for loop, but for simple computations there is no need. It's better if you vectorize its creation. Therefore, you can get rid of the for loop to calculate your gr array like so:
x = 1 : 360;
Theta = x*pi/180;
Phii = r*w*w*sin(Theta).*sin(Theta);
Vi = -G*M/(r*r);
gr = Vi + Phii;
x is simply a vector going from 1 to 360, and that's done in the first line. Also, Vi is just an array which contains a single value and if you know how operations work between a scalar and an array, you can just do an addition with this single value and it'll add every value in your array by this much. As such, there's no need to create an array for Vi. Also, take a look at how I calculated Phii. I'm using element-by-element operations as Theta is now an array. You want to create an array Phii that takes corresponding values of Theta, and applies that formula to each value in Theta to produce Phii.
Hope this helps. Good luck!
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'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.
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