Velocity arrows and confidence ellipses

The pygmt.Figure.velo method can be used to plot mean velocity arrows and confidence ellipses. The example below plots red velocity arrows with lightblue confidence ellipses outlined in red with the east_velocity x north_velocity used for the station names. Note that the velocity arrows are scaled by 0.2 and the 39% confidence limit will give an ellipse which fits inside a rectangle of dimension east_sigma by north_sigma.

import pandas as pd
import pygmt

fig = pygmt.Figure()
df = pd.DataFrame(
    data={
        "x": [0, -8, 0, -5, 5, 0],
        "y": [-8, 5, 0, -5, 0, -5],
        "east_velocity": [0, 3, 4, 6, -6, 6],
        "north_velocity": [0, 3, 6, 4, 4, -4],
        "east_sigma": [4, 0, 4, 6, 6, 6],
        "north_sigma": [6, 0, 6, 4, 4, 4],
        "correlation_EN": [0.5, 0.5, 0.5, 0.5, -0.5, -0.5],
        "SITE": ["0x0", "3x3", "4x6", "6x4", "-6x4", "6x-4"],
    }
)
fig.velo(
    data=df,
    region=[-10, 8, -10, 6],
    projection="x0.8c",
    frame=["WSne", "2g2f"],
    spec="e0.2/0.39+f18",
    uncertaintyfill="lightblue1",
    pen="0.6p,red",
    line=True,
    vector="0.3c+p1p+e+gred",
)

fig.show()