There are several example data sets in Matlab, for example wind and mri. If you execute the command load wind you will load the data in the data set wind. Some are included in toolboxes and some appear to be included in standard Matlab. These example data sets are valuable as test data when developing algorithms.
Where can one find a list of all such data sets included in Matlab?
You can enter demo in matlab to get a list. The wind table is part of Example — Stream Line Plots of Vector Data, etc.
For the tables on your computer, have a look at:
C:\Program Files\MATLAB\R2007b\toolbox\matlab\demos
The example data is located in .mat files in ../toolbox/matlab/demos.
The following data is available in MATLAB 2014a:
% in matlab run:
> H=what('demos')
> display(H.mat)
You can also use your favorite Linux console:
/usr/local/MATLAB/R2014a/toolbox/matlab/demos$ ls *.mat -1 | sed -e "s/.mat//g"
This is my list for readers who can not try it on their machine while reading this answer:
accidents
airfoil
cape
census
clown
detail
dmbanner
durer
earth
flujet
gatlin
gatlin2
integersignal
logo
mandrill
membrane
mri
patients
penny
quake
seamount
spine
stocks
tetmesh
topo
topography
trimesh2d
trimesh3d
truss
usapolygon
usborder
vibesdat
west0479
wind
xpmndrll
While the command demo in MATLAB 2018b will start a help browser with some demos:
You can find a list of all available dataset and their description in the following link :
https://www.mathworks.com/help/stats/sample-data-sets.html
Related
Many of Matlab's Mapping toolbox examples require "topo60c" world map data. Here's an example
load topo60c
axesm hatano
meshm(topo60c,topo60cR)
zlimits = [min(topo60c(:)) max(topo60c(:))];
demcmap(zlimits)
colorbar
However, when I run the above script, Matlab displays a file not found error for "topo60c". Does anyone know why I'm getting this error? I have the Mapping toolbox installed, and it works with other Mapping sample code that doesn't reference that file.
In the acknowledgements section of the mapping toolbox docs there is a note about example data sources:
https://uk.mathworks.com/help/map/dedication-and-acknowledgment.html
Except where noted, the information contained in example and sample data files (found in matlabroot/examples/map/data and matlabroot/toolbox/map/mapdata) is derived from publicly available digital data sets. These data files are provided as a convenience to Mapping Toolbox™ users. MathWorks® makes no claims that any of this data is free of defects or errors, or that the representations of geographic features or names are up to date or authoritative.
You can open these folders from MATLAB (on Windows) using
winopen( fullfile( matlabroot, 'examples/map/data' ) )
winopen( fullfile( matlabroot, 'toolbox/map/mapdata' ) )
Or simply use the fullfile commands above to identify the paths and navigate there yourself.
I can see (MATLAB R2020b) the topo60c file within the first of these folders, which isn't on your path by default because it's within "examples" and not a toolbox directory:
So you could either:
Add this folder to your path so that MATLAB can see the file: addpath(fullfile(matlabroot,'examples/map/data'));
Reference the full file path to the data when running examples: load(fullfile(matlabroot,'examples/map/data/topo60c.mat'));
I would prefer option 2 to avoid changing the path.
Additionally, there is another note in the Raster Geodata section of the docs which details what that dataset should contain
https://uk.mathworks.com/help/map/raster-geodata.html
When raster geodata consists of surface elevations, the map can also be referred to as a digital elevation model/matrix (DEM), and its display is a topographical map. The DEM is one of the most common forms of digital terrain model (DTM), which can also be represented as contour lines, triangulated elevation points, quadtrees, octree, or otherwise.
The topo60c MAT-file, which contains global terrain data, is an example of a DEM. In this 180-by-360 matrix, each row represents one degree of latitude, and each column represents one degree of longitude. Each element of this matrix is the average elevation, in meters, for the one-degree-by-one-degree region of the Earth to which its row and column correspond.
Given that it's generated from publically available data anyway (ref the first docs quote) and you now know what data it represents (ref the 2nd docs quote), you could replicate some replacement data if really needed.
I designed a filter and applied it to a random noise signal using SPTool in MATLAB. My noise signal was x = (1/sqrt(2))*(randn(1024,1)+j*randn(1024,1))
Once I've applied my filter to this noise signal, how can I take that filtered signal and use it as a file source in GNU Radio Companion (which I will connect to QT GUI Frequency Sink)? I tried exporting the signal using SPTool but I'm unsure what file extension I can use for GNU Radio. Thanks in advance.
Use fwrite with the right precision parameter that gives you float 32 binaries.
Or just use the octave/Matlab scripts in GNU Radio that do exactly that: write raw binary data. For more info, see the GNU Radio FAQ entry on the file format. (On https://wiki.gnuradio.org )
If you have a .mat file, another option is to use a Vector Source block putting in the Vector field:
loadmat('filename')['varname'].flatten()
For this to work you need to:
import numpy
from scipy.io import loadmat
Note this loads the whole file in memory (but you can specify which variables to load from the file if that's a problem). Also if the data is stored as float64 (as is the norm in Matlab) then I think there could be some rounding/truncation since GR Vector Source expects float32 (don't know enough about how SWIG handles that).
In Matlab help section, there's a very helpful example to solve classification problems under "Digit Classification Using HOG Features". You can easily execute the full script by clikcing on 'Open this example'. However, I'm wondering if there's a way to store the output of "fitcecoc" in a database so you don't have to keep training and classifying each and everytime you run the code. Here is the section of the code that's relevant to my question:
% fitcecoc uses SVM learners and a 'One-vs-One' encoding scheme.
classifier = fitcecoc(trainingFeatures, trainingLabels);
So, all I want to do is store 'classifier' in a database and retrieve it for the following code:
predictedLabels = predict(classifier, testFeatures);
Look at Database Toolbox in Matlab.
You could just save the classifier variable in a file:
save('classifier.mat','classifier')
And then load it before executing predict:
load('classifier.mat')
predictedLabels = predict(classifier, testFeatures);
I have done PCA for 21 images of the same person in different conditions. LAst step of the PCA is projection of original data : signals=PC'*data. Size of signals is 21*21, now I want to write this to a CSV file with a label as +1. Please guide me how to do this in matlab. I tried csvwrite but it does not write the labels, only the data.
[signals,V]=pca(im2double(inputdata));
for i=1:length(signals)
for j=1:1
label(i,j)=+1;
end(both for)
csvwrite('f1.csv',[label signals]);
Ok, so this question is related to my ongoing task of getting text data categorized, you can refer to this question for more details on how I approached this problem.
I used the standard matlab function "nctool" (neural clustering tool) to get my inputs organized on a plane of 10x10 SOM nodes. I also got the output of this map (i.e. which of my inputs ended up on which node) saved in to the "output" variable in my workspace.
I would now like to get this data out and see if I can write another script. I'm aware of the 'save' and some of the export functions in MATLAB, however it seems that MATLAB does not support ascii export of this variable since it is a sparse matrix.
I am currently writing a script to get this thing exported out, however if someone already has a solution, please post. Otherwise I will do so after I finish testing it.
Update: I found a workaround to this fairly easily:
% convert a sparse matrix to full
output = full(output);
% output this to a file (excel)
xlswrite('test.csv',output);