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GeoDataPython example of OMTI and RISR data

Primary Author:John Swoboda
Co-Authors:Anna Stuhlmacher, Michael Hirsch


This is the repository for the Python version of GeoData to plot and analyze data from geophysics sources such as radar and optical systems.


git clone
cd GeoDataPython
pip install -e .

To install Mayavi, suggest "menpo" conda channel as well as creating a separate Conda Environment:

conda create -n geodata python=3.5 pyqt=4
source activate geodata

conda install -c menpo mayavi

Software Structure

The code is broken up into these files:

File Description
File Functionality code related to the GeoData class such as the class def file and any other functions that directly use or impact the class. code that will be used to read in data from new data types. functions to plot data. code for different coordinate transforms.

Style Guide:

This style guide will cover conventions and elements specific to this codebase. For more general tips on proper Python style guidelines see PEP 8 the de-facto Python style guide.

Code that impacts the class will be placed in the class def file. For example if it is desired to interpolate the data to a different set of coordinates this should be implemented as a method in the class. The code for doing this can be written outside of the class def file if needed but this should only be done to keep the code neat.

The read functions will be placed in file. The names of the functions will start with read_ and then followed by a descriptive name.

The properties names will be all lower case. While all function names will be lower case with _ to separate words. The classes will have capitalized words with no spaces. Directories will be capitalized with _ to separate words.

If the user would like to create test code please do this in the Test folder. Also this code is not be uploaded to the main code base on GitHub.

Class Structure

The GeoData software is built around a class where each instance is a data set from a sensor. The user will simply have to make a function to read the data into the class and which at that point will give them access to other tools such as interpolations and plotting methods that can be used to augment or display the data.

The class will be made up of the following variables

Primary Class Variables
variable description
data This will hold the data for the data set. In python this will be a dictionary where the keys are the names of the data and the values will be numpy arrays that hold the data. In MATLAB the field names will be the data names and the arrays will be the values. Each data set will be held in a flattened array structure or can be an NxT array where N is the number of locations of measurements and T will be the number of times.
coordnames This string will hold the types of coordinates for the data. There will be a set number of coordinate types seen in the table below. More can be added as needed,
dataloc This will be a NxP array of locations in the coordinate system of choice. P is the number of elements
sensorloc This will be an array that holds the location of the sensor in wgs84. If there are multiple sensors such as a set of satellite measurements the array will be filled with nans.
times A Tx2 array of times in posix format showing the ending and beginning of a measurement.

For the coordnames variable, here are the possible names

Possible Coordinate Names
String Name Definition
wgs84 Latitude Longitude Altitude (deg,deg,m)
Spherical Range azimuth and elevation (km, deg, deg) elevation angle is referenced to z=0 plane
Spherical2 Range azimuth and elevation (km, deg, deg) elevation angle is referenced to x=y=0 line
ENU East north up (m,m,m). sensorloc holds the origin
ECEF Earth centered earth fixed (m,m,m)
Cartesian Local Cartesian grid (km,km,km). Pretty much the same as ENU but in km


The GeoData take advantage of a standardized structure of data to give the user access to the avalible tools. It's built off of container class where each instances is a specfic data set. In all cases the user needs to put their data in this structure. This first task will require a line of code similar to the following to start the process:

Geo = GeoData(readfunction,input1,input2 ...)

The readfunction is a function that can read the data from its previous format to the one specified by GeoData. The terms input1, input2 are what ever inputs are required by the read function to work.

Once the data set is now in the proper format the user can go about augmenting it in a number of ways. The user can augment the values and labeling of the data sets by using the changedata method built into the class. Interpolation methods are avalible in the class to change the coordinate system or simply regrid it in the current system. The size of the data set can be reduced by applying methods to filter out specfic time and data points. A time registration method is also avalible where it will take as input a second instance of the class and determine what measurements overlap in time with the original instance.

At this point the user can plot their results. Each of the plotting tools are set up in different functions in the Plotting folder. These plotting tools will output handles to figures that we plotted along with handles to colorbars if included.


run all these from the GeoDataPython/Test/ directory

Example Programs
Test Description overlays Ne data in transparent and contour forms in two panels quad plot of radar beams, and three cool image/radar overlays of the radar only  

Error diagnosis

Most issues revolve around Mayavi 3-D plotting.


Fast 3-D plotting typically involves OpenGL these days. Mayavi/VTK use OpenGL to make highly dense 3-D plots beautiful. If you get an OpenGL error like this try:

sudo apt install mayavi2


If you get QT/PyQT errors, be sure you have QT and PyQT version 4.x not 5.x with Mayavi 4.5. Hopefully future versions of Mayavi will be QT 5.x compatible -- Mayavi 4.5.0 requires QT 4.x.


This holds the GeoData implementation in Python







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