map_plotter

The package abstracts away some complexity of using the Python packages cartopy/matplotlib for creating global heatmaps / intensity maps of a quantity.

Setup

Opinionated recommendation: avoid dependency hell and use conda to create a virtual environment and install cartopy (with precompiled binaries).

conda install cartopy

Installation

Install this package within the virtual environment:

pip install .

Usage

Import the module and call the plot function as shown below:

import map_plotter
map_plotter.plot(
    lons_g, lats_g, 
    variable, units="m/s", 
    variable_vector,
    img_name="image.png",
    save=True, plot=True, 
    title="something", zlims=[0,10])

Whereby:

• lons_g and lats_g represent 2D matrices / grids of longitudes and latitudes.
• variable is the matrix of scalar values to be plotted (same grid dimensions).
• variable_vector is the matrix of values of tuples (u,v) to be plotted (same grid dimensions). If both variable and variable_vector specified, quiver plot is overload onto intensity plot.
• units and img_name (self explanatory, units apply to scalar variable intensity plot).
• save & plot boolean flags to save the file and plot to screen, respectively.
• zlims define the color scale minimum and maximum.

Tests

Install testing dependencies:

pip install -r tests/requirements.txt

Run the test script to visualize ocean current data:

python tests/check_map.py

A map is displayed, and a PNG file is generated in the tests/ directory.

Example

Figure 1: Total electron content of the ionosphere for given date-time as nowcast by the NOAA WAM-IPE model

Sponsor

https://amentum.io