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 light-blue 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.

Out:

<IPython.core.display.Image object>

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],
    pen="0.6p,red",
    uncertaintycolor="lightblue1",
    line=True,
    spec="e0.2/0.39/18",
    frame=["WSne", "2g2f"],
    projection="x0.8c",
    vector="0.3c+p1p+e+gred",
)

fig.show()