The Generic Mapping Tools

The Julia Interface

Joaquim F. Luis

Pål (Paul) Wessel

SOEST, University of Hawai’i at Manoa

# 1. Introduction¶

The Julia wrapper is a companion to the MATLAB wrapper that works in very similar way, making use of the relative similarity of the two languages.

# 2. Installing¶

Contrary to the rest of all GMT products the Julia wrapper has to live in a Github repository. At the time of this writing the wrapper was not yet registered within the Julia package manager, so to install it one has to access the Github address directly. After installing Julia and from within its shell (aka the REPL) issue this command: (but refer to Julia’s package manager)

Pkg.add("GMT")


Now you are ready to start using the GMT wrapper and the only condition for it to work is that the GMT shared libs are listed in your path. On Windows the GMT installer takes care of that but be careful that no other previous version is found first.

On UNIX things are more complicated (surprise). On OSX, the only other OS tested so far by us, we got a working version by running, in the Julia REPL

push!(Libdl.DL_LOAD_PATH, "/Users/j/programs/gmt5/lib")


this adds, for one particular user case, the gmt/lib directory to the list of system locations searched for valid libraries. There might be more problems finding other gmt dependencies but with Homebrew builds it works because those dependencies are located at /usr/local/lib and the system finds them with no other help. To make that line permanent, add it to your ~/.juliarc.jl file (if don’t have one yet, create it).

# 3. Using¶

The Julia wrapper was designed to work in a way the closest as possible to the command line version. 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

using GMT
gmt("coast -Rg -JA280/30/3.5i -Bg -Dc -A1000 -Gnavy -P > GMT_lambert_az_hemi.ps")


Note the using GMT command. We need to do that to load the GMT.jl wrapper and the first time it will take a little longer because it will need to JIT compile the module’s code. Following commands, however, will run at same speed as the command line calls to GMT.

However, the above example 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 Julia 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 (actually a Julia’s type) holding the grid and it’s metadata. See the grid type 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 -Ggridname 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 they are used in the exact same order as the options in the command string.

To illustrate another aspect on the importance of the order of input data let us see how to plot a sinus 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("plot -R-3.2/3.2/-1.1/1.1 -JX12c -Sc0.1c -C -P -Ba > seno.ps", xyz, cpt)


The poin here is that we had to give cpt, xyz and not xyz, cpt (which would error) because input data associated with an option letter always comes first and has to respect the corresponding options order in command string.

To plot text strings we send in the input data wrapped in a cell array. Example:

lines = Any["5 6 Some label", "6 7 Another label"];
gmt("text -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("gmtinfo", 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 has to be sent in to GMT we use Julia variables holding the data in matrices or structures or cell arrays depending on the case. 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. The file gallery.jl in test directory, that reproduces the examples in the Gallery section of the GMT documentation, has many (not so trivial) examples on usage of the Julia/GMT API.

To run the examples in gallery.jl we have to load the file first, which is located in your .julia directory. For me it lives in C:/j/.julia/v0.4/GMT/test/gallery.jl and we have to edit it to set the path to the GMT root dir so that the data file used in examples can be found. After that, run

include("C:/j/.julia/v0.4/GMT/test/gallery.jl")


now the examples are wrapped in functions named ex01, ex02, … ex45 (not all are yet ported/working) and we just call them with

ex01()

type GMTgrid                  # The type holding a local header and data of a GMT grid
proj4::String              # Projection string in PROJ4 syntax (Optional)
wkt::String                # Projection string in WKT syntax (Optional)
range::Array{Float64,1}    # 1x6 vector with [x_min x_max y_min y_max z_min z_max]
inc::Array{Float64,1}      # 1x2 vector with [x_inc y_inc]
registration::Int          # Registration type: 0 -> Grid registration; 1 -> Pixel registration
nodata::Float64            # The value of nodata
title::String              # Title (Optional)
comment::String            # Remark (Optional)
command::String            # Command used to create the grid (Optional)
datatype::String           # 'float' or 'double'
x::Array{Float64,1}        # [1 x n_columns] vector with XX coordinates
y::Array{Float64,1}        # [1 x n_rows]    vector with YY coordinates
z::Array{Float32,2}        # [n_rows x n_columns] grid array
x_units::String            # Units of XX axis (Optional)
y_units::String            # Units of YY axis (Optional)
z_units::String            # Units of ZZ axis (Optional)
layout::String             # A three character string describing the grid memory layout
end


Definition of the grid type that holds a grid and its metadata.

type GMTimage                 # The type holding a local header and data of a GMT image
proj4::String              # Projection string in PROJ4 syntax (Optional)
wkt::String                # Projection string in WKT syntax (Optional)
range::Array{Float64,1}    # 1x6 vector with [x_min x_max y_min y_max z_min z_max]
inc::Array{Float64,1}      # 1x2 vector with [x_inc y_inc]
registration::Int          # Registration type: 0 -> Grid registration; 1 -> Pixel registration
nodata::Float64            # The value of nodata
title::String              # Title (Optional)
comment::String            # Remark (Optional)
command::String            # Command used to create the image (Optional)
datatype::String           # 'uint8' or 'int8' (needs checking)
x::Array{Float64,1}        # [1 x n_columns] vector with XX coordinates
y::Array{Float64,1}        # [1 x n_rows]    vector with YY coordinates
image::Array{UInt8,3}      # [n_rows x n_columns x n_bands] image array
x_units::String            # Units of XX axis (Optional)
y_units::String            # Units of YY axis (Optional)
z_units::String            # Units of ZZ axis (Optional) ==> MAKES NO SENSE
colormap::Array{Clong,1}   #
alpha::Array{UInt8,2}      # A [n_rows x n_columns] alpha array
layout::String             # A four character string describing the image memory layout
end


Definition of the image type that holds an image and its metadata.

type GMTdataset
data::Array{Float64,2}
text::Array{Any,1}
comment::Array{Any,1}
proj4::String
wkt::String
end


Definition of the daset type.

type GMTcpt
colormap::Array{Float64,2}
alpha::Array{Float64,1}
range::Array{Float64,2}
minmax::Array{Float64,1}
bfn::Array{Float64,2}
depth::Cint
hinge::Cdouble
cpt::Array{Float64,2}
model::String
comment::Array{Any,1}   # Cell array with any comments
end


Definition of the cpt type that holds a CPT palette.

type GMTps
postscript::String      # Actual PS plot (text string)
length::Int             # Byte length of postscript
mode::Int               # 1 = Has header, 2 = Has trailer, 3 = Has both
comment::Array{Any,1}   # Cell array with any comments
end


Definition of the PotScript type.