I am trying to get better quality phase plots of complex functions made with the Complex Function Explorer of E. Wegert CFE. For this purpose I apply the Matlab anti-aliasing function myaa.m to the phase plots that are made with the CFEGUI.m. For the example screenshot of the result window below I used the setting myaa([8 8]) in the Matlab command window which means that the supersampling enlarge the figure 8x and then downscale it to 1/8 to get the original h x w.
As one can see the window of the figure has no operation icons or menu options for save or print. My question is what to do with such a figure (beside making screenshots)? Can I somehow use export-fig to save such a figure or load it in an image array and if yes, how?
It is also possible to use the setting myaa([8 1]) which results in a very large figure window that is larger than my screen (and has the unpleasant attribute that it can not be moved). It would be even better if such a whole figure could be saved (not only the visible part).
You can use getframe to grab current figure information in pixels.
However, while I do not know how this affects you, notice that MATLAB versions above 2014b (included) have already anti-aliasing. The code you linked seem to be from 2008, I am not 100% sure if it has become obsolete now.
I'm currently using the Matlab/Octave online IDE at http://www.tutorialspoint.com/execute_matlab_online.php and I'm trying to save a graph that I'm plotting to .pdf format. I've done the following:
- octave
- x = [ 1: 10 ]
- y = x
- plot(x,y)
- print -dpdf graph.pdf
I then refresh the the files and folders to the left, double click on the graph.pdf file and am always greeted with a black filled rectangle. I've then attempted to run the following:
- axis("off")
- print -dpdf graph2.pdf
And the graph appears to save to pdf correctly. However, without the axes. Could you please assist me in finding a solution?
P.S. I have already attempted octave --force-gui and graphics_toolkit('gnu_toolkit')/graphics_toolkit('fltk') with no luck.
At the site hosted, the only graphics toolkit available is gnuplot, which support in octave was mostly dropped several versions ago.
gnuplot has the bug you've described. In the link, people got plotting working by rolling back to previous gnuplot versions.
Guess the only way of getting printing working on the site would be signalling about the issue to its administration.
Also, note that octave crudely depicts the copy of the plot in terminal window. That might suffice for correctness check of the plotting code itself.
Alternatively, you can save octave graphics objects with hgsave command, those then can be loaded in octave on another computer to obtain same plot as one that would be drawn there. (Although, at this point there might be no reason for using online interpreter then.)
I am using jupyter-notebook to write some python code and generate figures. As I wanted to add tooltips on mouse hovering and other interactions with the generated graphs, I now use mpld3 to display the graph.
However, as I have quite a lot of things to plot, I need to increase the figure size. So, I putfig = plt.figure(figsize=(20, 10)).
When I display with the standard way, I can see all the figure in my notebook (with horizontal sliders if I increase a bit more the figsize).
But with the mpld3 display, the size of the zone where the figure is displayed seems to be fixed, and hence, I can only see the upper left part of my figure. There are no sliders or anything to increase the displaying zone size.
For example, this code generate a graphic, for which you will see only the upper left part:
fig = plt.figure(figsize=(20, 10))
plt.plot([3,1,4,1,5], 'ks-')
mpld3.display(fig)
Does anyone know how to deal with this ? That is, how to increase the default display zone size, in order to have bigger graphs ?
Thanks
Edit after comment:
Here is a screenshot of how it is displayed on my machine...
And I would like it to be displayed just as it is on yours !
So I guess the problem comes from elsewhere... do you have any idea of how to solve this ?
I hope I do understand your question correctly but in Ipython Notebooks you can only use excisting space and not flip the notebook into wide screen mode or alike. In my notebook the graphic is also displayed like you show.
However, there is an easy fix, simply reduce the figsize to for example (10, 5). The main idea with interactive plotting with mpld3 is that the user can zoom in to specific interesting details. For the presented example it would not make much sense but richer graphs are great to be explored interactively.
I have table of l,a,b values and want to visualise these colors in matlab (or any other suitable software). Is there any quick way like series of rectangles filled with color values from the table?
There are several versions of the Lab color space, but presumably you're referring to most common, CIELAB. You can use imwrite in Matlab to create a TIFF image with 'cielab' specified for the 'Colorspace' option. I wouldn't trust Matlab as a viewer for the resultant images though. Photoshop in lab mode (from the menu bar: Image > Mode > Lab Color) would be a good choice if you want work with and see the closest thing to the actual CIELAB space. Other viewers/editors may convert to RGB or CMYK before rendering to the screen (likely without warning you), but maybe you don't mind. If you just want to convert from CIELAB to RGB, you might find these functions useful.
After lots of research, I found out there is a plugin called 'color inspector' that can be used along with ImageJ (all opensource tools). Have excellent capacity to view and analyse different color space. Even it has some color tools that matlab yet to have. here is imageJ: http://rsbweb.nih.gov/ij/download.html
and the plugin
http://rsb.info.nih.gov/ij/plugins/color-inspector.html
Hope this is useful to someone
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.