Multiple colormaps

This gallery example shows how to create multiple colormaps for different subplots. To better understand how GMT modern mode maintains several levels of colormaps, please refer to https://docs.generic-mapping-tools.org/latest/cookbook/features.html#gmt-modern-mode-hierarchical-levels for details.

Out:

grdcut [NOTICE]: Remote data courtesy of GMT data server https://oceania.generic-mapping-tools.org [https://oceania.generic-mapping-tools.org]
grdcut [NOTICE]: Earth Relief at 10x10 arc minutes from Gaussian Cartesian filtering (18 km fullwidth) of SRTM15+V2.1 [Tozer et al., 2019].
grdcut [NOTICE]:   -> Download grid file [3.0M]: earth_relief_10m_p.grd
grdimage [WARNING]: 2 annotations along the bottom border were skipped due to crowding.
grdimage [WARNING]: Crowding decisions is controlled by MAP_ANNOT_MIN_SPACING, currently set to 25.5563p.
grdimage [WARNING]: Decrease or increase MAP_ANNOT_MIN_SPACING to see more or fewer annotations, with 0 showing all annotations.
<IPython.core.display.Image object>

import pygmt

fig = pygmt.Figure()

# Load Earth relief data for the entire globe and a subset region
grid_globe = pygmt.datasets.load_earth_relief(resolution="01d")
subset_region = [-14, 30, 35, 60]
grid_subset = pygmt.datasets.load_earth_relief(resolution="10m", region=subset_region)

# Define a 1-row, 2-column subplot layout. The overall figure dimensions is set
# to be 15 cm wide and 8 cm high. Each subplot is automatically labelled.
# The space between the subplots is set to be 0.5 cm.
with fig.subplot(
    nrows=1, ncols=2, figsize=("15c", "8c"), autolabel=True, margins="0.5c"
):
    # Activate the first panel so that the colormap created by the makecpt
    # method is a panel-level CPT
    with fig.set_panel(panel=0):
        pygmt.makecpt(cmap="geo", series=[-8000, 8000])
        # "R?" means Winkel Tripel projection with map width automatically
        # determined from the subplot width.
        fig.grdimage(grid=grid_globe, projection="R?", region="g", frame=True)
        fig.colorbar(frame=["a4000f2000", "x+lElevation", "y+lm"])
    # Activate the second panel so that the colormap created by the makecpt
    # method is a panel-level CPT
    with fig.set_panel(panel=1):
        pygmt.makecpt(cmap="globe", series=[-6000, 3000])
        # "M?" means Mercator projection with map width also automatically
        # determined from the subplot width.
        fig.grdimage(
            grid=grid_subset, projection="M?", region=subset_region, frame=True
        )
        fig.colorbar(frame=["a2000f1000", "x+lElevation", "y+lm"])

fig.show()