Plotting data points¶
GMT shines when it comes to plotting data on a map. We can use some sample data that is
packaged with GMT to try this out. PyGMT provides access to these datasets through the
pygmt.datasets package. If you don’t have the data files already, they are
automatically downloaded and saved to a cache directory the first time you use them
[131.29, 150.89, 34.02, 50.77] year month day latitude longitude depth_km magnitude 0 1987 1 4 49.77 149.29 489 4.1 1 1987 1 9 39.90 141.68 67 6.8 2 1987 1 9 39.82 141.64 84 4.0 3 1987 1 14 42.56 142.85 102 6.5 4 1987 1 16 42.79 145.10 54 5.1
pygmt.Figure.plot method to plot circles on the locations of the
hypocenters of the earthquakes.
We used the style
c0.3c which means “circles of 0.3 centimeter size”. The
attribute controls the outline of the symbols and the
color controls the fill.
We can map the size of the circles to the earthquake magnitude by passing an array to
sizes argument. Because the magnitude is on a logarithmic scale, it helps to
show the differences by scaling the values using a power law.
Notice that we didn’t include the size in the
style argument this time, just the
c (circles) and the unit
c (centimeter). So in this case, the sizes
will be interpreted as being in centimeters.
We can also map the colors of the markers to the depths by passing an array to the
color argument and providing a colormap name (
cmap). We can even use the new
matplotlib colormap “viridis”.
We normalize the data values given to
color because, by default,
plot can only interpret values between 0 and 1. To use the
actual data values, we would need to create a color palette table (CPT) which
isn’t implemented yet.
Total running time of the script: ( 0 minutes 3.724 seconds)