I am trying to reproduce a band-like diagram, like the one in figure from windows defrag.
In principle, it can be easily obtained by doing a contourf of a matrix which is constant along one dimension (corresponding to the vertical dimension in the picture).
Do you know if there are native ways to obtain such a diagram?
Try:
vec = [1*ones(1,10), 2*ones(1,5), 3*ones(1,20), 4*ones(1,15)];
image('CData',vec, 'CDataMapping','direct')
colormap(lines(4))
axis tight off
or maybe even:
imshow(repmat(vec,10,1), lines(4))
imshow(vec, lines(4), 'YData',[0 10])
This is using an indexed image with direct color mapping, where the value 1 gets mapped to first color, value 2 mapped to second color and so on.. You can of course use your own colormap by specifying a N-by-3 matrix.
Not sure if this is what you are requesting, but there is no specialised function in matlab to do this. However, you could easily implement your own function that uses line to draw a large number of lines based on your data. Using get/set on the handles of the lines would let you control their colour, width etc. (also based on the input to your function).
Related
I am trying to plot the result of Tsne using gscatter in Matlab.
I want to use specific color for training and other color for Anchors
Y=tsne(xtrain; xAnxhors]);
gscatter(Y(:,1),Y(:,2));
That is the code that I used but I got the figure in one color only so I want to show the diffrence of colors between xtrain and xAnchors
The function gscatter allows you to specify two more arguments. With the first one you can already define groups (a vector that indicates for each point what group it belongs to) which will automatically assign different colours to different groups. The second argument allows for an even more fine grained control about the actual choice of colours. For reference an example from the documentation:
Plot the Displacement values on the x-axis and the Horsepower values on the y-axis. gscatter uses the variable names as the default labels for the axes. Group the data points by Model_Year.
load carsmall
gscatter(Displacement,Horsepower,Model_Year)
I have 8 plots which I want to implement in my Matlab code. These plots originate from several research papers, hence, I need to digitize them first in order to be able to use them.
An example of a plot is shown below:
This is basically a surface plot with three different variables. I know how to digitize a regular plot with just X and Y coordinates. However, how would one digitize a graph like this? I am quite unsure, hence, the question.
Also, If I would be able to obtain the data from this plot. How would you be able to utilize it in your code? Maybe with some interpolation and extrapolation between the given data points?
Any tips regarding this topic are welcome.
Thanks in advance
Here is what I would suggest:
Read the image in Matlab using imread.
Manually find the pixel position of the left bottom corner and the upper right corner
Using these pixels values and the real numerical value, it is simple to determine the x and y value of every pixel. I suggest you use meshgrid.
Knowing that the curves are in black, then remove every non-black pixel from the image, which leaves you only with the curves and the numbers.
Then use the function bwareaopen to remove the small objects (the numbers). Don't forget to invert the image to remove the black instead of the white.
Finally, by using point #3 and the result of point #6, you can manually extract the data of the graph. It won't be easy, but it will be feasible.
You will need the data for the three variables in order to create a plot in Matlab, which you can get either from the previous research or by estimating and interpolating values from the plot. Once you get the data though, there are two functions that you can use to make surface plots, surface and surf, surf is pretty much the same as surface but includes shading.
For interpolation and extrapolation it sounds like you might want to check out 2D interpolation, interp2. The interp2 function can also do extrapolation as well.
You should read the documentation for these functions and then post back with specific problems if you have any.
When I use spy to check a sparsity pattern, it doesn't distinguish certain elements from others. Is there any way to do this? Say, for example, elements that are equal to 10 are red and all elements equal to 9 are blue. Can I get this in one spy plot?
I've only been able to change the size and style of the plot points.
Here is how you can do it:
spy(a,'k')
hold on
spy(a==10,'r')
spy(a==9,'b')
hold off
Another way is to use scatter instead of spy :
[x,y] = find(a);
clr = a(a~=0);
scatter(x,y,[],clr)
set(gca,'YDir','rev')
In this case the points will be colored by a values according to current figure colormap.
I want to create a 5 dimensional plotting in matlab. I have two files in my workspace. one is data(150*4). In this file, I have 150 data and each has 4 features. Since I want to classify them, I have another file called "labels" (150*1) that includes a label for each data in data files. In other words the label are the class of data and I have 3 class: 1,2,3
I want to plot this classification, but i can't...
Naris
You need to think about what kind of plot you want to see. 5 dimensions are difficult to visualize, unless of course, your hyper-dimensional monitor is working. Mine never came back from the repair shop. (That should teach me for sending it out.)
Seriously, 5 dimensional data really can be difficult to visualize. The usual solution is to plot points in a 2-d space (the screen coordinates of a figure, for example. This is what plot essentially does.) Then use various attributes of the points plotted to show the other three dimensions. This is what Chernoff faces do for you. If you have the stats toolbox, then it looks like glyphplot will help you out. Or you can plot in 3-d, then use two attributes to show the other two dimensions.
Another idea is to plot points in 2-d to show two of the dimensions, then use color to indicate the other three dimensions. Thus, the RGB assigned to that marker will be defined by the other three dimensions. Of course, that means you must be able to visualize what the RGB coordinates of a color represent, so you need to understand color as it is represented in an RGB space.
You can use scatter3 to plot your data, using three features of data as dimensions, the fourth as color, and the class as different markers
figure,hold on
markerList = 'o*+';
for iClass = 1:nClasses
classIdx = dataClass==iClass;
scatter3(data(classIdx,1),data(classIdx,2),data(classIdx,3),[],data(classIdx,4),...
'marker',markerList(iClass));
end
When you use color to represent one of the features, I suggest to use a good colormap, such as pmkmp from the Matlab File Exchange instead of the default jet.
Alternatively, you can use e.g. mdscale to transform your higher-dimensional data to 2D for standard plotting.
There's a model called SOM (Self-organizing Maps) which builds a 2-D image of a multidimensional space.
I have a 2D space in which a function value is defined (you can think of it as a manifold). Now I plotted the function value using contourf and changed the colormap to something softer than jet. So far it looks quite good.
Now I want to draw a line representing the state over time in my space. That is also possible using the the plot command. But I want some more improvements: There is an additional state that is hidden for now (value 0...50). I would like the line color to change according to this hidden state. So in a sense to apply a separate colormap to the line plotted by plot like for example in a waterfall plot.
Is this (or something similar) possible using matlab?
Thanks
If you want to either use interpolated shading or have the colours change with the colour map, then you want to plot your data as a mesh and set the edgecolor property appropriately. Note that in order to plot it as a mesh, then you will need to duplicate it so that it has a size of at least 2 in each direction.
h = mesh([X(:) X(:)], [Y(:) Y(:)], [Z(:) Z(:)], [C(:) C(:)], ...
'EdgeColor', 'interp', 'FaceColor', 'none');
You may also want to look at the MeshStyle property, if you want to plot multiple lines simultaneously.
This solution is also much nicer than the one used in cline because it only creates one graphics object, rather than n.
Have a look into the cline.m function from file exchange, I think it is exactly what you need.
I can recommend the Colored line entry from the file exchange. It has good feedback and uses the color map to define the displayed colours, I've use it sucessfully on a number of projects.