1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
|
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")
|
