Colorbar

The pygmt.Figure.colorbar method creates a color scalebar. We must specify the colormap via the cmap argument, and optionally set the placement via the position argument. 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: justified inside/outside the map frame 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 5cm,7cm 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.

Out:

<IPython.core.display.Image object>

import pygmt

fig = pygmt.Figure()
fig.basemap(region=[0, 3, 6, 9], projection="x3c", frame=["af", 'WSne+t"Colorbars"'])

## 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 4cm by 0.5cm, and plotted horizontally (+h)
    position="g0.3/8.7+w4c/0.5c+h",
    box=True,
    frame=["x+lTemperature", r"y+l\260C"],
    scale=100,
)

## Create a colorbar suitable for surface topography - oleron
fig.colorbar(
    cmap="oleron",
    # Colorbar position justified outside map frame (J) at Middle Right (MR),
    # offset (+o) by 1cm horizontally and 0cm vertically from anchor point,
    # with a length/width (+w) of 7cm by 0.5cm 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 argument above
    frame=["x+lElevation", "y+lm"],
    scale=10,
)

fig.show()