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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 a four panel plot that includes
# four narrow colorbars, one for each plot. Axes labels are only drawn on the
# bottom left hand plot to avoid repeating information and make the plot less
# cluttered.
grid = AxesGrid(
fig,
(0.075, 0.075, 0.85, 0.85),
nrows_ncols=(2, 2),
axes_pad=1.0,
label_mode="1",
share_all=True,
cbar_location="right",
cbar_mode="each",
cbar_size="3%",
cbar_pad="0%",
)
fields = [
("gas", "density"),
("gas", "velocity_x"),
("gas", "velocity_y"),
("gas", "velocity_magnitude"),
]
# Create the plot. Since SlicePlot accepts a list of fields, we need only
# do this once.
p = yt.SlicePlot(ds, "z", fields)
# Velocity is going to be both positive and negative, so let's make these
# slices use a linear colorbar scale
p.set_log(("gas", "velocity_x"), False)
p.set_log(("gas", "velocity_y"), False)
p.zoom(2)
# For each plotted field, force the SlicePlot to redraw itself onto the AxesGrid
# axes.
for i, field in enumerate(fields):
plot = p.plots[field]
plot.figure = fig
plot.axes = grid[i].axes
plot.cax = grid.cbar_axes[i]
# Finally, redraw the plot on the AxesGrid axes.
p.render()
plt.savefig("multiplot_2x2.png")
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