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import numpy as np
from matplotlib.colors import LogNorm
import yt
from yt.visualization.base_plot_types import get_multi_plot
fn = "GasSloshing/sloshing_nomag2_hdf5_plt_cnt_0150" # dataset to load
orient = "horizontal"
ds = yt.load(fn) # load data
# There's a lot in here:
# From this we get a containing figure, a list-of-lists of axes into which we
# can place plots, and some axes that we'll put colorbars.
# We feed it:
# Number of plots on the x-axis, number of plots on the y-axis, and how we
# want our colorbars oriented. (This governs where they will go, too.
# bw is the base-width in inches, but 4 is about right for most cases.
fig, axes, colorbars = get_multi_plot(3, 2, colorbar=orient, bw=4)
slc = yt.SlicePlot(
ds,
"z",
fields=[("gas", "density"), ("gas", "temperature"), ("gas", "velocity_magnitude")],
)
proj = yt.ProjectionPlot(ds, "z", ("gas", "density"), weight_field=("gas", "density"))
slc_frb = slc.data_source.to_frb((1.0, "Mpc"), 512)
proj_frb = proj.data_source.to_frb((1.0, "Mpc"), 512)
dens_axes = [axes[0][0], axes[1][0]]
temp_axes = [axes[0][1], axes[1][1]]
vels_axes = [axes[0][2], axes[1][2]]
for dax, tax, vax in zip(dens_axes, temp_axes, vels_axes):
dax.xaxis.set_visible(False)
dax.yaxis.set_visible(False)
tax.xaxis.set_visible(False)
tax.yaxis.set_visible(False)
vax.xaxis.set_visible(False)
vax.yaxis.set_visible(False)
# Converting our Fixed Resolution Buffers to numpy arrays so that matplotlib
# can render them
slc_dens = np.array(slc_frb["gas", "density"])
proj_dens = np.array(proj_frb["gas", "density"])
slc_temp = np.array(slc_frb["gas", "temperature"])
proj_temp = np.array(proj_frb["gas", "temperature"])
slc_vel = np.array(slc_frb["gas", "velocity_magnitude"])
proj_vel = np.array(proj_frb["gas", "velocity_magnitude"])
plots = [
dens_axes[0].imshow(slc_dens, origin="lower", norm=LogNorm()),
dens_axes[1].imshow(proj_dens, origin="lower", norm=LogNorm()),
temp_axes[0].imshow(slc_temp, origin="lower"),
temp_axes[1].imshow(proj_temp, origin="lower"),
vels_axes[0].imshow(slc_vel, origin="lower", norm=LogNorm()),
vels_axes[1].imshow(proj_vel, origin="lower", norm=LogNorm()),
]
plots[0].set_clim((1.0e-27, 1.0e-25))
plots[0].set_cmap("bds_highcontrast")
plots[1].set_clim((1.0e-27, 1.0e-25))
plots[1].set_cmap("bds_highcontrast")
plots[2].set_clim((1.0e7, 1.0e8))
plots[2].set_cmap("hot")
plots[3].set_clim((1.0e7, 1.0e8))
plots[3].set_cmap("hot")
plots[4].set_clim((1e6, 1e8))
plots[4].set_cmap("gist_rainbow")
plots[5].set_clim((1e6, 1e8))
plots[5].set_cmap("gist_rainbow")
titles = [
r"$\mathrm{Density}\ (\mathrm{g\ cm^{-3}})$",
r"$\mathrm{Temperature}\ (\mathrm{K})$",
r"$\mathrm{Velocity Magnitude}\ (\mathrm{cm\ s^{-1}})$",
]
for p, cax, t in zip(plots[0:6:2], colorbars, titles):
cbar = fig.colorbar(p, cax=cax, orientation=orient)
cbar.set_label(t)
# And now we're done!
fig.savefig(f"{ds}_3x2")
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