"""Plots a HZ completeness comparison between an AYO and EXOSIMS run."""
import matplotlib.pyplot as plt
from matplotlib.cm import ScalarMappable
from matplotlib.colors import Normalize
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
[docs]
def plot_hz_completeness(
exosims_dir, ayo_dir, ax_kwargs=None, hline_kwargs=None, use_cyberpunk=False
):
"""Generate a scatter plot of the habitable zone completeness.
Args:
exosims_dir (EXOSIMSDirectory):
EXOSIMSDirectory to plot.
ayo_dir (AYODirectory):
AYODirectory to plot.
ax_kwargs (dict, optional):
Keyword arguments to pass to ax.set().
hline_kwargs (dict, optional):
Keyword arguments to pass to ax.axhline().
use_cyberpunk (bool, optional):
Whether to use the mplcyberpunk style. Default is False.
Returns:
matplotlib.figure.Figure, matplotlib.axes.Axes:
Figure and axes objects for the plot.
"""
if hline_kwargs is None:
hline_kwargs = {}
if ax_kwargs is None:
ax_kwargs = {}
if use_cyberpunk:
import mplcyberpunk # noqa: F401
plt.style.use("cyberpunk")
# Generate the figure and axes and set super x and y labels.
fig, axes = plt.subplots(1, 2, sharey=True)
fig.supxlabel("d (pc)")
fig.supylabel("Luminosity (L$_\odot$)")
ayo_ax, exo_ax = axes
ayo_ax.set(**ax_kwargs)
exo_ax.set(**ax_kwargs)
# Create the inset colorbar axes object.
cax = inset_axes(
exo_ax,
width="80%", # width: 50% of parent_bbox width
height="3%", # height: 5%
loc="upper center",
)
# Get the AYO colors.
colors = ayo_dir.get("star_comp_det")
# Get the colors and sizes for the scatter points.
plot_kwargs = {
"c": colors,
"alpha": [c + 0.1 if c == 0 else 1 for c in colors],
"s": [15 if c == 0 else 40 for c in colors],
}
# Plot the AYO data.
ayo_ax.ypl_scatter(
ayo_dir, x="star_dist", y="star_L", autolabel=False, **plot_kwargs
)
# Plot the horizontal lines differentiating the spectral types.
ayo_ax.axhline(y=5.5, **hline_kwargs)
ayo_ax.axhline(y=2, **hline_kwargs)
ayo_ax.axhline(y=0.65, **hline_kwargs)
ayo_ax.axhline(y=0.085, **hline_kwargs)
# Generate and format the colorbar.
cmappable = ScalarMappable(Normalize(0, 1))
cbar = fig.colorbar(cmappable, cax=cax, orientation="horizontal")
cbar.set_label("HZ Completeness", loc="center", fontsize=11)
cbar.ax.xaxis.set_label_position("bottom")
cbar.ax.xaxis.set_ticks_position("bottom")
cbar.ax.tick_params(labelsize=8, width=1.5)
# Get the EXOSIMS colors.
exosims_colors = exosims_dir.get("star_comp_det")
# Get the colors and sizes for the scatter points.
plot_kwargs = {
"c": exosims_colors,
"alpha": [c + 0.1 if c == 0 else 1 for c in exosims_colors],
"s": [15 if c == 0 else 40 for c in exosims_colors],
}
# Plot the EXOSIMS data.
exo_ax.ypl_scatter(
exosims_dir, x="star_dist", y="star_L", autolabel=False, **plot_kwargs
)
# Plot the horizontal lines differentiating the spectral types
exo_ax.axhline(y=5.5, **hline_kwargs)
exo_ax.axhline(y=2, **hline_kwargs)
exo_ax.axhline(y=0.65, **hline_kwargs)
exo_ax.axhline(y=0.085, **hline_kwargs)
# Add the spectral type labels.
ayo_ax.text(
0.07,
0.77,
"A",
transform=ayo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
)
ayo_ax.text(
0.07,
0.65,
"F",
transform=ayo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
)
ayo_ax.text(
0.07,
0.53,
"G",
transform=ayo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
)
ayo_ax.text(
0.07,
0.32,
"K",
transform=ayo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
)
ayo_ax.text(
0.07,
0.05,
"M",
transform=ayo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
)
# Add AYO and EXOSIMS labels.
props = dict(boxstyle="round", facecolor="white", alpha=0.5)
ayo_ax.text(
0.9,
0.08,
"AYO",
transform=ayo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
bbox=props,
)
exo_ax.text(
0.9,
0.08,
"EXOSIMS",
transform=exo_ax.transAxes,
fontsize=12,
verticalalignment="bottom",
horizontalalignment="right",
bbox=props,
)
# Remove the white space between the two subplots.
fig.subplots_adjust(wspace=0)
exo_ax.tick_params(right=True, which="both")
return fig, axes
