Global (SRTM) Bathymetry Map


The following is an 20x downsampled SRTM global bathymetry map made with Python and Basemap.

Full resolution can be found on wikimedia.

One can notice the depth of the ocean floor, on a global scale, ranges between -2000 and -6000 meters. In some regions though like the Pacific exceed this range and reach 11 kilometers below the sea surface. One such region is the deepest point on Earth, the Mariana trench as shown below followed by a map for a perspective of its location.


Location of the Mariana trench. Wikimedia commons.


Python wrappers for the Generic Mapping Tools on the way


An interface for interoperability between the Generic Mapping Tools (GMT), a tool used by geophysicists to create research-quality figures, and Matlab has recently been developed that allows GMT users to interact with Matlab and Matlab users to make use of GMT.

GMT wrappers are currently also being developed for the Python programming language, particularly to be used in the IPython/Jupyter notebook due to an initiative by Leonardo Uieda (and his professor Paul Wessel) whose Postdoc is being funded by the NSF. You can watch his talk at the SciPy 2017 conference below.

Some of the mentioned advantages to which I attest  include:

  • Begin and End statements are introduced to eliminate the need to pipe postscript results into a file in each line of code being written. This also eliminates the need to use the -K and -O flags which keep the file open and updates it, respectively. The -K and -O flags are a major confusion for newcomers to GMT.
  • temporary files are created under the /tmp directory, in Linux, so they will automatically be cleaned once the jupyter notebook is closed or the operating system is rebooted. Moreover, every project will have its own  directory so files from different projects don’t get mixed up.
  • GMT documentation straight in the Jupyter notebook
  • Matplotlib- & Basemap-like behaviour, particularly inline viewing of figures, using
  • Pythonic aliases make the compact GMT flags

To contribute:


Cook, T. (2017), A powerful new tool for research, Eos, 98, Published on 17 July 2017.

IPython: Python at your fingertips


To install the IPython notebook, do the following:

sudo apt-get install distribute ipython python-zmq python-tornado ipython-notebook
pip install numpy matplotlib #if you want to use the numpy extension & matplotlib plotting library
ipython notebook # launch the notebook from a terminal (will open in browser!)