Creating high-quality spatial colormaps for research can be challenging, especially when existing tools don’t quite meet the demands for customization and visual quality. While MATLAB is a powerful tool, it often falls short in producing publication-ready spatial maps. Alternatives like R and Python offer libraries with varying degrees of customization, but they each have their limitations.
During my PhD, I explored several options:
- MATLAB: Provided basic functionality but lacked in visual appeal and flexibility.
- NCL (NCAR Command Language): Offers high-quality visuals but has a steep learning curve and lacks support for Windows, making it difficult to use.
- Python Libraries (GeoPandas, Cartopy): These are easier to learn and integrate well within the Python ecosystem, but sometimes fall short in the quality of their graphical output.
After considerable exploration, I settled on PyGMT, a Python interface for the Generic Mapping Tools (GMT). PyGMT strikes an excellent balance by offering ease of use, excellent customization, and high-quality graphical output.
The best way to install PYGMT is through Anaconda. Let’s see how to install the package step by step.
Making Spatial map with Pygmt
Making Spatial maps are extremely important in making good quality publications. The following code helps in creating good quality spatial map.
Your data structure?
It’s important to note that the for spatial plotting your dataset should something look like this:
- 1st column should be Longitude
- 2nd Column should be latitude
- 3rd column should be the data value that you want to show as a colored spatial map.
Loading the Dataset
Since you are now familiar with how the dataset should looklike let’s load some dataset using “pandas”.
Note that Pandas is a great platform when deal with dataframes or working with csv files.
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