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 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()
Total running time of the script: (0 minutes 0.210 seconds)