python

Convolutional Neural Network for Oil Spill detection in Synthetic Aperture Radar Satellite Images

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Anaconda Python needs cleaning every once in a while

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As a user of Anaconda python I have been receiving (Ubuntu) system warnings of low free space in my home directory. Investigating what was causing this I found out that Anaconda python had several versions of each package. The overall size of the pkgs directory was 14+ GB. After cleaning it is about 3GB.

The second largest directory was my mail in Thunderbird.

So it would be wise, especially if you are limited in disk space, to clean Anaconda. The commands I used are as follows:

 
conda clean --all
conda update conda
# just to make sure nothing is broken and
# your environment is updated
source activate <your-environment>
conda update --all
conda clean --all

Global SRTM Map

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global_srtm_bathymetry_map

The following is an 20x downsampled global Shuttle Radar Topography Mission (SRTM)  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.

368px-marianatrenchmap

Location of the Mariana trench. Wikimedia commons.

Credits: The SRTM dataset used was provided by IFREMER.

Python wrappers for the Generic Mapping Tools on the way

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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 gmt.show()
  • Pythonic aliases make the compact GMT flags

To contribute: github.com/GenericMappingTools

Reference

Cook, T. (2017), A powerful new tool for research, Eos, 98, https://doi.org/10.1029/2017EO077489. Published on 17 July 2017.

IPython: Python at your fingertips

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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!)