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yt-project
GitHub Repository: yt-project/yt
 Path: blob/main/doc/source/cookbook/multi_plot_slice_and_proj.py
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import numpy as np

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from matplotlib.colors import LogNorm

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import yt

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from yt.visualization.base_plot_types import get_multi_plot

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fn = "GasSloshing/sloshing_nomag2_hdf5_plt_cnt_0150"  # dataset to load

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orient = "horizontal"

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ds = yt.load(fn)  # load data

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# There's a lot in here:

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#   From this we get a containing figure, a list-of-lists of axes into which we

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#   can place plots, and some axes that we'll put colorbars.

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# We feed it:

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#   Number of plots on the x-axis, number of plots on the y-axis, and how we

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#   want our colorbars oriented.  (This governs where they will go, too.

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#   bw is the base-width in inches, but 4 is about right for most cases.

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fig, axes, colorbars = get_multi_plot(3, 2, colorbar=orient, bw=4)

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slc = yt.SlicePlot(

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    ds,

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    "z",

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    fields=[("gas", "density"), ("gas", "temperature"), ("gas", "velocity_magnitude")],

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)

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proj = yt.ProjectionPlot(ds, "z", ("gas", "density"), weight_field=("gas", "density"))

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slc_frb = slc.data_source.to_frb((1.0, "Mpc"), 512)

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proj_frb = proj.data_source.to_frb((1.0, "Mpc"), 512)

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dens_axes = [axes[0][0], axes[1][0]]

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temp_axes = [axes[0][1], axes[1][1]]

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vels_axes = [axes[0][2], axes[1][2]]

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for dax, tax, vax in zip(dens_axes, temp_axes, vels_axes):

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    dax.xaxis.set_visible(False)

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    dax.yaxis.set_visible(False)

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    tax.xaxis.set_visible(False)

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    tax.yaxis.set_visible(False)

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    vax.xaxis.set_visible(False)

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    vax.yaxis.set_visible(False)

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# Converting our Fixed Resolution Buffers to numpy arrays so that matplotlib

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# can render them

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slc_dens = np.array(slc_frb["gas", "density"])

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proj_dens = np.array(proj_frb["gas", "density"])

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slc_temp = np.array(slc_frb["gas", "temperature"])

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proj_temp = np.array(proj_frb["gas", "temperature"])

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slc_vel = np.array(slc_frb["gas", "velocity_magnitude"])

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proj_vel = np.array(proj_frb["gas", "velocity_magnitude"])

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plots = [

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    dens_axes[0].imshow(slc_dens, origin="lower", norm=LogNorm()),

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    dens_axes[1].imshow(proj_dens, origin="lower", norm=LogNorm()),

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    temp_axes[0].imshow(slc_temp, origin="lower"),

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    temp_axes[1].imshow(proj_temp, origin="lower"),

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    vels_axes[0].imshow(slc_vel, origin="lower", norm=LogNorm()),

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    vels_axes[1].imshow(proj_vel, origin="lower", norm=LogNorm()),

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]

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plots[0].set_clim((1.0e-27, 1.0e-25))

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plots[0].set_cmap("bds_highcontrast")

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plots[1].set_clim((1.0e-27, 1.0e-25))

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plots[1].set_cmap("bds_highcontrast")

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plots[2].set_clim((1.0e7, 1.0e8))

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plots[2].set_cmap("hot")

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plots[3].set_clim((1.0e7, 1.0e8))

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plots[3].set_cmap("hot")

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plots[4].set_clim((1e6, 1e8))

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plots[4].set_cmap("gist_rainbow")

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plots[5].set_clim((1e6, 1e8))

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plots[5].set_cmap("gist_rainbow")

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titles = [

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    r"$\mathrm{Density}\ (\mathrm{g\ cm^{-3}})$",

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    r"$\mathrm{Temperature}\ (\mathrm{K})$",

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    r"$\mathrm{Velocity Magnitude}\ (\mathrm{cm\ s^{-1}})$",

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]

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for p, cax, t in zip(plots[0:6:2], colorbars, titles):

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    cbar = fig.colorbar(p, cax=cax, orientation=orient)

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    cbar.set_label(t)

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# And now we're done!

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fig.savefig(f"{ds}_3x2")

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