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import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid
import yt
fns = [
"Enzo_64/DD0005/data0005",
"Enzo_64/DD0015/data0015",
"Enzo_64/DD0025/data0025",
"Enzo_64/DD0035/data0035",
]
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 with a single
# shared narrow colorbar on the right hand side of the multipanel plot. Axes
# labels are drawn for all plots since we're slicing along different directions
# for each plot.
grid = AxesGrid(
fig,
(0.075, 0.075, 0.85, 0.85),
nrows_ncols=(2, 2),
axes_pad=0.05,
label_mode="L",
share_all=True,
cbar_location="right",
cbar_mode="single",
cbar_size="3%",
cbar_pad="0%",
)
for i, fn in enumerate(fns):
# Load the data and create a single plot
ds = yt.load(fn) # load data
p = yt.ProjectionPlot(ds, "z", ("gas", "density"), width=(55, "Mpccm"))
# Ensure the colorbar limits match for all plots
p.set_zlim(("gas", "density"), 1e-4, 1e-2)
# This forces the ProjectionPlot to redraw itself on the AxesGrid axes.
plot = p.plots[("gas", "density")]
plot.figure = fig
plot.axes = grid[i].axes
plot.cax = grid.cbar_axes[i]
# Finally, this actually redraws the plot.
p.render()
plt.savefig("multiplot_2x2_time_series.png")
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