I'm trying to create an app for data analysis.
I have multiple channels of acquisition of the same length, including a time vector.
Vectors as therefore synchronized (same index value corrispond to the same time instant for every array).
I display data on different figures (UIAxes) in my app figure.
To better and more easily use the application I would like the following to happen: each time the user hovers the cursor on any plot a vertical bar at the corrisponding x position of the cursor is displayed, on all the figures. All the figures display the same range of x values.
I also have a scatter figure with points from gps, still with the same length of the other arrays.
On that figure I'd really like to have, instead of the vertical line, a crosshair.
I've found this part of code here but I can't adapt it to App Designer and it's also pretty old.
Any kind of help is very welcome.
EDIT: Matlab Version 2020b
I have created an overlay of 100 curves. I thought the image looked impressive but one of my reviewers stated that I should only show the averaged line. Meaning, only show a line that is the average of the 100 curves. Is this possible using the xtline feature, or do I need to get deeper into programming code to produce the graphic? Alternatively, it would be great if I could show both (the 100 curves and the averaged curve) in the same graphic.
You don't need anything complicated here. Just calculate the mean across the panel and show it directly. Here is some technique. I am guessing that in your real example with 100 curves a legend is pointless. Note the c(L) and read the help to find what it does.
webuse grunfeld, clear
set scheme s1color
gen log_invest = log(invest)
egen mean_log_invest = mean(log_invest), by(year)
line log_invest year, legend(off) lc(gs12) c(L) || line mean_log_invest year, c(L) scheme(s1color) ytitle(something sensible)
In Matlab, I would like to visualize the test results in a figure with several charts and text. The figure is divided into rows and colums: 3 rows and 5 colums. For better understanding, here a screenshot of the figure with a orange grid which shows the subplot division:
Now I have several questions:
A) How can I include text into a specific section within the figure? i.e. test settings into subplot(6 and 11) and test results into subplot (7, 8, 9, 10).
B) Is it possible to "draw" separator lines between the subplots? i.e. to separate the test settings from the test result subplots for a better visualization.
C) Is it possible to set a title over several subplots such as "input data" and "output data"?
Thanks for your help!
Cheers,
Kevin
I have come this problem many times and haven't yet figured out a decent way to solve it. However what you can do is:
A) Include a Label (help label) in the subplot you want. Alternatively use a "edit locked" edit text field.
B) Yes in a way. Check out panels. Create a subplot, then inside a panel that fills the plot area. with the panel as parent create a figure (or label as in A) )
C) Thats a tricky one and I would use panels again, but I am not sure if that works.
These things are always a pain to do in Matlab itself. I usually ended up exporting my figures, writing a small HTML generator that places the images in divs and a decent CSS to make it look nice. It is way easier to do so if it is only for representing data. If you want it to be interactive you have to do it inside the UI.
Hope that helps
Benjamin
I've been working on an image segmentation problem and can't seem to get a good idea for my most recent problem.
This is what I have at the moment:
Click here for image. (This is only a generic example.)
Is there a robust algorithm that can automatically discard the right square as not belonging to the group of the other four squares (that I know should always be stacked more or less on top of each other) ?
It can sometimes be the case, that one of the stacked boxes is not found, so there's a gap or that the bogus box is on the left side.
Your input is greatly appreciated.
If you have a way of producing BW images like your example:
s = regionprops(BW, 'centroid');
centroids = cat(1, s.Centroid);
xpos = centroids(:,1); should then be the x-positions of the boxes.
From here you have multiple ways to go, depending on whether you always have just one separated box and one set of grouped boxes or not. For the "one bogus box far away, rest closely grouped" case (away from Matlab, so this is unchecked) you could even do something as simple as:
d = abs(xpos-median(xpos));
bogusbox = centroids(d==max(d),:);
imshow(BW);
hold on;
plot(bogusbox(1),bogusbox(2),'r*');
Making something that's robust for your actual use case which I am assuming doesn't consist of neat boxes is another matter; as suggested in comments, you need some idea of how close together the positioning of your good boxes is, and how separate the bogus box(es) will be.
For example, you could use other regionprops measurements such as 'BoundingBox' or 'Extrema' and define some sort of measurement of how much the boxes overlap in x relative to each other, then group using that (this could be made to work even if you have multiple stacks in an image).
I have 42 variables and I have calculated the correlation matrix for them in Matlab. Now I would like to visualize it with a schemaball. Does anyone have any suggestions / experiences how this could be done in Matlab? The following pictures will explain my point better:
In the pictures each parabola between variables would mean the strength of correlation between them. The thicker the line is, the more correlation. I prefer the style of picture 1 more than the style in picture 2 where I have used different colors to highlight the strength of correlation.
Kinda finished I guess.. code can be found here at github.
Documentation is included in the file.
The yellow/magenta color (for positive/negative correlation) is configurable, as well as the fontsize of the labels and the angles at which the labels are plotted, so you can get fancy if you want and not distribute them evenly along the perimeter/group some/...
If you want to actually print these graphs or use them outside matlab, I suggest using vector formats (eg eps). It's also annoying that the text resizes when you zoom in/out, but I don't know of any way to fix that without hacking the zoom function :/
schemaball % demo
schemaball(arrayfun(#num2str,1:10,'uni',false), rand(10).^8,11,[0.1587 0.8750],[0.8333 1],2*pi*sin(linspace(0,pi/2-pi/20,10)))
schemaball(arrayfun(#num2str,1:50,'uni',false), rand(50).^50,9)
I finished and submitted my version to the FEX: schemaball and will update the link asap.
There are a some differences with Gunther Struyf's contribution:
You can return the handles to the graphic object for full manual customization
Labels are oriented to allow maximum left-to-rigth readability
The figure stretches to fit labels in, leaving the axes unchanged
Syntax requires only correlations matrix (but allows optional inputs)
Optimized for performance.
Follow examples of demo, custom labels and creative customization.
Note: the first figure was exported with saveas(), all others with export_fig.
schemaball
x = rand(10).^3;
x(:,3) = 1.3*mean(x,2);
schemaball(x, {'Hi','how','is','your','day?', 'Do','you','like','schemaballs?','NO!!'})
h = schemaball;
set(h.l(~isnan(h.l)), 'LineWidth',1.2)
set(h.s, 'MarkerEdgeColor','red','LineWidth',2,'SizeData',100)
set(h.t, 'EdgeColor','white','LineWidth',1)
The default colormap:
To improve on screen rendering you can launch MATLAB with the experimental -hgVersion 2 switch which produces anti/aliased graphics by default now (source: HG2 update | Undocumented Matlab). However, if you try to save the figure, the file will have the usual old anti-aliased rendering, so here's a printscreen image of Gunther's schemaball:
Important update:
You can do this in Matlab now with the FileExchange submission:
http://www.mathworks.com/matlabcentral/fileexchange/48576-circulargraph
There is an exmample by Matlab in here:
http://uk.mathworks.com/examples/matlab/3859-circular-graph-examples
Which gives this kind of beautiful plots:
Coincidentally, Cleve Moler (MathWorks Chief Mathematician) showed an example of just this sort of plot on his most recent blog post (not nearly as beautiful as the ones in your example, and the connecting lines are straight rather than parabolic, but it looks functional). Unfortunately he didn't include the code directly, but if you leave him a comment on the post he's usually very willing to share things.
What might be even nicer for you is that he also applies (and this time includes) code to permute the rows/columns of the array in order to maximize the spatial proximity of highly connected nodes, rather than randomly ordering them around the circumference. You end up with a 'crescent'-shaped envelope of connecting lines, with the thick bit of the crescent representing the most highly connected nodes.
Unfortunately however, I suspect that if you need to enhance his code to get the very narrow, high-resolution lines in your example plots, then MATLAB's currently non-anti-aliased graphics aren't quite up to it yet.
I've recently been experimenting with MATLAB data and the D3 visualization library for similar graphs - there are several related types of circular visualizations you may be interested in and many of them are interactive. Another helpful, well-baked, and freely available option is Circos which is probably responsible for most of the prettier versions of these graphs you've seen in popular press.