https://github.com/GenericMappingTools/gmtmex/wiki
The GMT MATLAB interface makes it possible to access all GMT modules from MATLAB. Users of MATLAB can write MATLAB scripts that call upon GMT modules to do any of the things GMT normally can do, and return the results (grids, data-tables, CPTs, text-files, and even final images via psconvert) to MATLAB variables. MATLAB matrices can be given as input to GMT modules. Examples below will give you the general idea.
The Windows installers come already with the gmtmex.mexw64|32 and gmt.m files necessary run the MEX. Only make sure that the GMT6.4 binary dir is either in the Windows path (the installer does that for you) and in the MATLAB path (you have to do it yourself). If you want to (re)build the MEX file yourself, see the compile_mex.bat in the source SVN repository.
We have successfully built the MATLAB interface under macOS. However, due to the way MATLAB handles shared libraries it is a delicate process, with several caveats. This may change over time as we work with MathWorks to straighten out the kinks. The following works:
- Install the GMT macOS Bundle
- Run the gmt_prepmex.sh script in the bundle's share/tools directory. This will duplicate the GMT 6.4 installation into /opt/gmt and re-baptize all the shared libraries.
- Use gmtswitch to make /opt/gmt the current active GMT version
- Checkout the gmtmex project via git into some directory, i.e.,
git clone https://github.com/GenericMappingTools/gmtmex.git - In
gmtmex/, run autoconf then configure --enable-matlab (and maybe --enable-debug) is you can help debug things. - Run make which builds the gmtmex.mexmaci64 (x86_64) or gmtmex.mexmaca64 (arm64). This executable is accessed by the gmt.m script.
- Set your MATLAB path so these two can be found (or copy them to a suitable directory).
- Make sure your gmt.conf file has the entry GMT_CUSTOM_LIBS=/opt/gmt/lib/gmt/plugins/supplements.so.
You can also build your own bundle (see CMakeLists.txt in main GMT directory). The above works with UNIX installations from fink or HomeBrew but fails for us if under MacPorts (then, MATLAB will complain about wrong shared HDF5 library and we crash). If you wish to help debug in XCode then see the gmtmex wiki for more details. While the latest 2023b MATLAB version works with XCode 14, earlier versions may require an older Xcode version. We used the 2023b MATLAB version to build the interface.
Preliminary experiments indicate we will have to fight the shared library dilemma here as well. Volunteers on Linux wishing to run the GMT MATLAB interface are needed to make progress.
The MATLAB wrapper was designed to work in a way the closest as possible to the command line version
and yet to provide all the facilities of the MATLAB IDE (the ML command line desktop). In this sense,
all GMT options are put in a single text string that is passed, plus the data itself when it applies,
to the gmt() command. For example to reproduce the CookBook example of an Hemisphere map using a
Azimuthal projection
gmt('pscoast -Rg -JA280/30/3.5i -Bg -Dc -A1000 -Gnavy -P > GMT_lambert_az_hemi.ps')
but that is not particularly interesting as after all we could do the exact same thing on the a shell command line. Things start to get interesting when we can send data in and out from MATLAB to GMT. So, consider the following example
t = rand(100,3) * 150;
G = gmt('surface -R0/150/0/150 -I1', t);
Here we just created a random data 100x3 matrix and told GMT to grid it using it's program
surface. Note how the syntax follows closely the standard usage but we sent the data to be
interpolated (the t matrix) as the second argument to the gmt() function. And on return we
got the G variable that is a structure holding the grid and it's metadata. See the
grid struct for the details of its members.
Imagining that we want to plot that random data art, we can do it with a call to grdimage, like
gmt('grdimage -JX8c -Ba -P -Cblue,red > crap_img.ps', G)
Note that we now sent the G grid as argument instead of the -G gridname that we would have used in the command line. But for readability we could well had left the -G option in command string. E.g:
gmt('grdimage -JX8c -Ba -P -Cblue,red -G > crap_img.ps', G)
While for this particular case it makes no difference to use or not the -G, because there is only one input, the same does not hold true when we have more than one. For example, we can run the same example but compute the CPT separately.
cpt = gmt('grd2cpt -Cblue,red', G);
gmt('grdimage -JX8c -Ba -P -C -G > crap_img.ps', G, cpt)
Now we had to explicitly write the -C & -G (well, actually we could have omitted the -G because it's a mandatory input but that would make the things more confusing). Note also the order of the input data variables. It is crucial that any required (primary) input data objects (for grdimage that is the grid) are given before any optional (secondary) input data objects (here, that is the CPT object). The same is true for modules that return more than one item: List the required output object first followed by optional ones.
To illustrate another aspect on the importance of the order of input data let us see how to plot a sine curve made of colored filled circles.
x = linspace(-pi, pi)'; % The *xx* var
seno = sin(x); % *yy*
xyz = [x seno seno]; % Duplicate *yy* so that it can be colored
cpt = gmt('makecpt -T-1/1/0.1'); % Create a CPT
gmt('psxy -R-3.2/3.2/-1.1/1.1 -JX12c -Sc0.1c -C -P -Ba > seno.ps', xyz, cpt)
The point here is that we had to give xyz, cpt and not cpt, xyz (which would error) because optional input data associated with an option letter always comes after the required input.
To plot text strings we send in the input data wrapped in a cell array. Example:
lines = {'5 6 Some label', '6 7 Another label'};
gmt('pstext -R0/10/0/10 -JM6i -Bafg -F+f18p -P > text.ps', lines)
and we get back text info in cell arrays as well. Using the G grid computed above we can run gmtinfo on it
info = gmt('info', G)
At the end of an GMT session work we call the internal functions that will do the house keeping of freeing no longer needed memory. We do that with this command:
gmt('destroy')
So that's basically how it works. When numeric data have to be sent in to GMT we use MATLAB variables holding the data in matrices or structures or cell arrays, depending on data type. On return we get the computed result stored in variables that we gave as output arguments. Things only complicate a little more for the cases where we can have more than one input or output arguments, since the order or the arguments matter (Remember the rule: primary first, secondary second). The file gallery.m, that reproduces the examples in the Gallery section of the GMT documentation, has many (not so trivial) examples on usage of the MEX GMT API.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent