multiplot_2x2_coordaxes_slice.py

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid

import yt

fn = "IsolatedGalaxy/galaxy0030/galaxy0030"
ds = yt.load(fn)  # load data

fig = plt.figure()

# See http://matplotlib.org/mpl_toolkits/axes_grid/api/axes_grid_api.html
# These choices of keyword arguments produce two colorbars, both drawn on the
# right hand side.  This means there are only two colorbar axes, one for Density
# and another for temperature.  In addition, axes labels will be drawn for all
# plots.
grid = AxesGrid(
    fig,
    (0.075, 0.075, 0.85, 0.85),
    nrows_ncols=(2, 2),
    axes_pad=1.0,
    label_mode="all",
    share_all=True,
    cbar_location="right",
    cbar_mode="edge",
    cbar_size="5%",
    cbar_pad="0%",
)

cuts = ["x", "y", "z", "z"]
fields = [
    ("gas", "density"),
    ("gas", "density"),
    ("gas", "density"),
    ("gas", "temperature"),
]

for i, (direction, field) in enumerate(zip(cuts, fields)):
    # Load the data and create a single plot
    p = yt.SlicePlot(ds, direction, field)
    p.zoom(40)

    # This forces the ProjectionPlot to redraw itself on the AxesGrid axes.
    plot = p.plots[field]
    plot.figure = fig
    plot.axes = grid[i].axes

    # Since there are only two colorbar axes, we need to make sure we don't try
    # to set the temperature colorbar to cbar_axes[4], which would if we used i
    # to index cbar_axes, yielding a plot without a temperature colorbar.
    # This unnecessarily redraws the Density colorbar three times, but that has
    # no effect on the final plot.
    if field == ("gas", "density"):
        plot.cax = grid.cbar_axes[0]
    elif field == ("gas", "temperature"):
        plot.cax = grid.cbar_axes[1]

    # Finally, redraw the plot.
    p.render()

plt.savefig("multiplot_2x2_coordaxes_slice.png")