Note

Go to the end to download the full example code.

# Cartesian logarithmic

**X***width*[**l**][/*height*[**l**]] or
**x***x-scale*[**l**][/*y-scale*[**l**]]

Give the *width* of the figure and the optional *height*.
The lower-case version **x** is similar to **X** but expects
an *x-scale* and an optional *y-scale*.
Each axis with a logarithmic transformation requires **l** after
its size argument.

```
import numpy as np
import pygmt
# Create a list of x-values 0-100
xline = np.arange(0, 101)
# Create a list of y-values that are the square root of the x-values
yline = xline**0.5
# Create a list of x-values for every 10 in 0-100
xpoints = np.arange(0, 101, 10)
# Create a list of y-values that are the square root of the x-values
ypoints = xpoints**0.5
fig = pygmt.Figure()
fig.plot(
region=[1, 100, 0, 10],
# Set a logarithmic transformation on the x-axis
projection="X15cl/10c",
# Set the figures frame and color as well as
# annotations, ticks, and gridlines
frame=["WSne+gbisque", "xa2g3", "ya2f1g2"],
x=xline,
y=yline,
# Set the line thickness to "1p", the color to "blue",
# and the style to "-", i.e. "dashed"
pen="1p,blue,-",
)
# Plot square root values as points on the line
# Style of points is 0.3 cm squares, color fill is "red" with a "black" outline
# Points are not clipped if they go off the figure
fig.plot(x=xpoints, y=ypoints, style="s0.3c", fill="red", no_clip=True, pen="black")
fig.show()
```

**Total running time of the script:** (0 minutes 0.154 seconds)