Colorbar

The pygmt.Figure.colorbar method creates a color scalebar. We must specify the colormap via the cmap parameter, and optionally set the placement via the position parameter. The full list of color palette tables can be found at https://docs.generic-mapping-tools.org/latest/cookbook/cpts.html. You can set the position of the colorbar using the following options:

• j/J: placed inside/outside the plot bounding box using any 2-character combination of vertical (Top, Middle, Bottom) and horizontal (Left, Center, Right) alignment codes, e.g. position="jTR" for Top Right.

• g: using map coordinates, e.g. position="g170/-45" for longitude 170E, latitude 45S.

• x: using paper coordinates, e.g. position="x5c/7c" for 5 cm, 7 cm from anchor point.

• n: using normalized (0-1) coordinates, e.g. position="n0.4/0.8".

Note that the anchor point defaults to the bottom left (BL). Append +h to position to get a horizontal colorbar instead of a vertical one.

import pygmt

fig = pygmt.Figure()
fig.basemap(region=[0, 3, 6, 9], projection="x3c", frame=["af", "WSne+tColorbars"])

# ============
# Create a colorbar designed for seismic tomography - roma
# Colorbar is placed at bottom center (BC) by default if no position is given
fig.colorbar(cmap="roma", frame=["x+lVelocity", "y+lm/s"])

# ============
# Create a colorbar showing the scientific rainbow - batlow
fig.colorbar(
    cmap="batlow",
    # Colorbar positioned at map coordinates (g) longitude/latitude 0.3/8.7,
    # with a length/width (+w) of 4 cm by 0.5 cm, and plotted horizontally (+h)
    position="g0.3/8.7+w4c/0.5c+h",
    box=True,
    frame=["x+lTemperature", "y+l°C"],
    scale=100,
)

# ============
# Create a colorbar suitable for surface topography - oleron
fig.colorbar(
    cmap="oleron",
    # Colorbar placed outside the plot bounding box (J) at Middle Right (MR),
    # offset (+o) by 1 cm horizontally and 0 cm vertically from anchor point,
    # with a length/width (+w) of 7 cm by 0.5 cm and a box for NaN values (+n)
    position="JMR+o1c/0c+w7c/0.5c+n+mc",
    # Note that the label 'Elevation' is moved to the opposite side and plotted
    # vertically as a column of text using '+mc' in the position parameter
    # above
    frame=["x+lElevation", "y+lm"],
    scale=10,
)

# ============
# Create a colorbar suitable for categorical data - hawaii
# Set up the colormap
pygmt.makecpt(
    cmap="hawaii",
    series=[0, 3, 1],
    # Comma-separated string for the annotations of the colorbar
    color_model="+cA,B,C,D",
)
# Plot the colorbar
fig.colorbar(
    cmap=True,  # Use colormap set up above
    # Colorbar placed inside the plot bounding box (j) at Bottom Left (BL),
    # offset (+o) by 0.5 cm horizontally and 0.8 cm vertically from anchor
    # point, and plotted horizontally (+h)
    position="jBL+o0.5c/0.8c+h",
    box=True,
    # Divide colorbar into equal-sized rectangles
    equalsize=0.5,
)

fig.show()