Note
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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.
![velo arrow ellipse](../../_images/sphx_glr_velo_arrow_ellipse_001.png)
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",
uncertaintyfill="lightblue1",
line=True,
spec="e0.2/0.39/18",
frame=["WSne", "2g2f"],
projection="x0.8c",
vector="0.3c+p1p+e+gred",
)
fig.show()
Total running time of the script: ( 0 minutes 0.544 seconds)