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DOC: Update the gallery example for pygmt.grdlandmask #4434

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Merged
seisman merged 2 commits into from
Mar 1, 2026
Merged

DOC: Update the gallery example for pygmt.grdlandmask #4434

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DOC: Update the gallery example for pygmt.grdlandmask
seisman Feb 28, 2026
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Merge branch 'main' into doc/grdlandmask
seisman Mar 1, 2026
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22 changes: 10 additions & 12 deletions examples/gallery/images/grdlandmask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,8 @@
Create 'wet-dry' mask grid
==========================

The :func:`pygmt.grdlandmask` function allows setting all nodes on land
or water to a specified value using the ``mask_values`` parameter.
The :func:`pygmt.grdlandmask` function allows setting all nodes on land or water to a
specified value using the ``mask_values`` parameter.
"""

# %%
Expand All @@ -15,22 +15,20 @@
# Define region of interest
region = [-65, -40, -40, -20]

# Assign a value of 0 for all water masses and a value of 1 for all land
# masses.
# Use shoreline data with (l)ow resolution and set the grid spacing to
# 5 arc-minutes in x- and y-directions.
# Assign a value of 0 for all water masses and a value of 1 for all land masses. Use
# shoreline data with low resolution and set the grid spacing to 5 arc-minutes in x-
# and y-directions.
grid = pygmt.grdlandmask(
region=region, spacing="5m", mask_values=[0, 1], resolution="l"
region=region, spacing="5m", mask_values=[0, 1], resolution="low"
)

# Plot clipped grid
fig.basemap(region=region, projection="M12c", frame=True)

# Define a colormap to be used for two categories, define the range of the
# new discrete CPT using series=(lowest_value, highest_value, interval),
# use color_model="+cwater,land" to write the discrete color palette
# "batlow" in categorical format and add water/land as annotations for the
# colorbar.
# Define a colormap to be used for two categories, define the range of the new discrete
# CPT using series=(low, high, interval), use color_model="+cwater,land" to write the
# discrete color palette "SCM/batlow" in categorical format and add water/land as
# annotations for the colorbar.
pygmt.makecpt(cmap="SCM/batlow", series=(0, 1, 1), color_model="+cwater,land")

fig.grdimage(grid=grid, cmap=True)
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