What I want to do is very simple, I just cannot seem to get MATLAB to do it. I would like to plot contours using my 2D data set.
My data set is large; 2 x 844240. I can do a scatter plot just fine,
scatter(Data(1,:), Data(2,:));
Reading through the forums I found Scatter plot with density in Matlab, where a hisogram was plotted. This would suffice, however, I would like to overlay the plots.
The issue is that they have different axis, my scatter data has an axis of [0 0.01 0 2500]; whereas the histogram is [0 100 0 100].
Is there a way to change the axis values of the histogram without modifying the image?
Thanks!
If I understand correctly, you are using hist3 to construct a histogram and then using imagesc to plot it. You can use the second output argument of hist3 to get the histogram bin centers, and then pass those on to imagesc, e.g.
nBins_x = 100;
nBins_y = 100;
[counts, bin_centers] = hist3(Data, [nBins_x nBins_y]);
x_bin_centers = bin_centers{1};
y_bin_centers = bin_centers{2};
imagesc(x_bin_centers, y_bin_centers, counts)
A couple other notes:
In your case, you will need to transpose your [2 x N] matrix when passing it to hist3, which expects an [N x 2] matrix.
imagesc puts the first axis (which I've been calling the "x" axis) on the vertical axis and the second on the horizontal axis. If you want to flip it, you can use:
imagesc(y_bin_centers, x_bin_centers, counts')
If you want to specify the histogram bins explicitly (e.g. to match your scatterplot) you can specify that in the arguments to hist3:
x_bin_centers = linspace(0, .01, 100);
y_bin_centers = linspace(0, 2500, 100);
counts = hist3(Data, {x_bin_centers, y_bin_centers};
And if you want a contour plot, you can use (note that contour takes the axes arguments in a different order than imagesc):
contour(x_bin_centers, y_bin_centers, counts');
If you are unhappy with the jaggedness of the contours, you may consider using a kernel density estimate instead of a histogram (check out ksdensity) (oops, looks like ksdensity is 1-D only. But there are File Exchange submissions for bivariate kernel density estimation).
Related
Hope the title gave an adequate description of my problem. Basically, I am generating a contour plot in MATLAB using the contourf (x,y,z) function, where x and y are vectors of different lengths and z is a matrix of data with dimensions of x times y. The contourf plot is fine, however, I am looking to overlay this plot with the actual data points from the matrix z. I have tried using the scatter function, but I am getting an error message informing me that X and Y must be vectors of the same length - which they're not. Is there any other way to achieve this?
Thanks in advance for any help/suggestions!
I think meshgrid should help you.
z = peaks; %// example 49x49 z data
x = 1:20;
y = 1:49;
z = z(y,x); %// make dimensions not equal so length(x)~=length(y)
[c,h] = contourf(x,y,z);
clabel(c,h); colorbar;
[xx,yy]=meshgrid(x,y); %// this is what you need
hold on;
plot(xx,yy,'k.'); %// overlay points on contourf
Notice plot suffices instead of scatter. If you insist, scatter(xx(:),yy(:),10), for example, does the trick. Although my example isn't particularly interesting, this should hopefully get you started toward whatever you're going for aesthetically.
So I have data in the form [x y z intensity] that I plot on a scatter3 figure with xyz axes. The colour of the data is used to dictate the intensity value. Problem is, using a scatter plot means the data points show up as discrete points. What I need, is a smooth shape - so I guess I need some kind of interpolation between the points?
I've tried using trisurf, but the problem with this one is that it interpolates between points that it shouldn't. So where I should have 'gaps' in my surface, it joins up the edges instead so it fills in the gaps. See the attached pics for clarification.
Does anyone have any suggestions?
The code I use is as below (the commented out scatter3 is what does the scatter plot, the rest does the trisurf):
% Read in data
dataM = csvread('3dDispersion.csv');
% scatter3(dataM(:,1), dataM(:,2), dataM(:,3), 5, dataM(:,4),'filled');
% Plot
hold on;
x = dataM(:,1);
y = dataM(:,2);
freq = dataM(:,3);
tri = delaunay(x,y);
h = trisurf(tri, x, y, freq);
% Make it pretty
% view(-45,30);
view(3);
axis vis3d;
lighting phong;
shading interp;
Use the boundary function in Matlab. This will apply a mesh similar to shrinkwrap over your points. In order to reduce the "gap closers", you will want to increase the "shrink factor".
Try K = boundary(X,Y,Z,0.9)
Where X, Y & Z are the vectors of your data points
https://www.mathworks.com/help/matlab/ref/boundary.html
You can then use trimesh or related surface plotting functions depending on how you want to display it.
I'm trying to draw ROC curves using an existing set of values using the following command
plot(X1,Y1,'--rs',X2,Y2,'-*g');
Where X1,Y1,X2 and Y2 are matrices that have the same size
However, the lines produced by this command are straight ones.
How can I make them curved lines.
Thanks
Aziz
MATLAB by default uses straight line approximation to draw your graph in between control points. If you want, you can interpolate in between the points to produce a more realistic graph. Try using interp1 with the 'spline' option and see how that goes. As such, figure out the minimum and maximum values of both X1 and X2, then define a grid of points in between the minimum and maximum that have finer granularity. Once you do this, throw this into interp1 and plot your curve. Something like:
%// Find dynamic range of domain for both Xs
minX1 = min(X1);
maxX1 = max(X1);
minX2 = min(X2);
maxX2 = max(X2);
%// Generate grid of points for both Xs
x1Vals = linspace(minX1, maxX1, 100);
x2Vals = linspace(minX2, maxX2, 100);
%// Interpolate the curves
y1Vals = interp1(X1, Y1, x1Vals, 'spline');
y2Vals = interp1(X2, Y2, x2Vals, 'spline');
%// Plot the results
plot(x1Vals,y1Vals,'--rs',x2Vals,y2Vals,'-*g');
linspace generates a grid of points from one end to another, and I specified 100 of these points. I then use interp1 in the way we talked about where you specify control points (X1,Y1,X2,Y2), then specify the values I want to interpolate with. I use the output values after interpolation and draw the curve.
I need to make a plot with only points and tried something like
plot(x,y)
where x and y are vectors: collection of points.
I do not want matlab to connect these points itself. I want to plot as if plotted with
for loop
plot;hold on;
end
I tried
plot(x,y,'.');
But this gave me too thick points.
I do not want to use forloop because it is time expensive. It takes a lot of time.
You're almost there, just change the MarkerSize property:
plot(x,y,'.','MarkerSize',1)
Try:
plot(x,y,'*');
or
plot(x,y,'+');
You can take a look to the documentation: http://www.mathworks.nl/help/matlab/creating_plots/using-high-level-plotting-functions.html
help scatter
IIRC: where S is the size of the scatter points:
scatter(x,y,S)
You may try this piece of code that avoid using loops. The plot created does not have lines but markers of different colors corresponding to each column of matrices x and y.
%some data (matrix)
x = repmat((2:10)',1,6);
y = bsxfun(#times, x, 1:6);
set(0,'DefaultAxesColorOrder', jet(6)); %set the default matlab color
figure('Color','w');
plot(x,y,'p'); %single call to plot
axis([1 11 0 70]);
box off;
legend(('a':'f')');
This gives
I have made a contour plot in matlab using the inbuilt contour function. It plots a group of lines in a figure, each of which represents a contour. I would like to obtain the data points that comprise each of these contours. How can I do this?
So given a contour plot how would I get the actual underlying data points that make up the equation for each contour line. For example, if the contours ended up being straight lines and one of the contour lines went through the origin, I would like to be able to obtain data points that describe this line. e.g. [0 0.1 0.2 0.3 0.4 ; 0 0.25 0.5 0.75 1].
Thanks.
[C,h] = contour(...) returns a contour matrix, C, that contains the x, y coordinates and contour levels for contour lines derived by the low-level contourc function, and a handle, h, to a contourgroup object. The clabel function uses contour matrix C to label the contour lines. ContourMatrix is also a read-only contourgroup property that you can obtain from the returned handle.
If X or Y is irregularly spaced, contour calculates contours using a regularly spaced contour grid, and then transforms the data to X or Y.
By the way, this text was taken from Matlab documentation...