mplhep styles with contourf log scale causes hang about mplhep HOT 8 CLOSED

import matplotlib.colors as colors
import mplhep
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import rc_context
from matplotlib.ticker import LogFormatterSciNotation
from numpy import random
from numpy.random import PCG64, SeedSequence
from scipy.interpolate import LinearNDInterpolator

# generate observed values (x, y)
x_step = 250
x_range = np.arange(750, 3000 + x_step, step=x_step)
y_step = 150
y_range = np.arange(700, 2000 + y_step, step=y_step)

bit_generator = PCG64(SeedSequence(0))
rng = random.default_rng(bit_generator)

x = []
y = []
for step in x_range:
    choose_n = rng.integers(low=0, high=y_range.size - 2)
    for value in y_range[: choose_n + 2]:
        x.append(step)
        y.append(value)

x = np.asarray(x)
y = np.asarray(y)

# Generate uniform data on the interval [1e-3, 100.]
# Uniform [a,b) = (b - a) * random_sample() + a
uniform_range = [1e-3, 100.0]
z = (uniform_range[1] - uniform_range[0]) * rng.random(x.size) + uniform_range[0]

# Generate a 2D grid
x_coords = np.linspace(min(x), max(x), 100)
y_coords = np.linspace(min(y), max(y), 100)
x_grid, y_grid = np.meshgrid(x_coords, y_coords)  # 2D grid for interpolation

# Interpolate with function of choice across the grid
# between the known values
interp_func = LinearNDInterpolator(list(zip(x, y)), z)
interp_Z = interp_func(x_grid, y_grid)

plt.style.use(mplhep.style.ATLAS)

# c.f. https://github.com/scikit-hep/mplhep/issues/362
rc_options = {"ytick.minor.visible": False}  # yticks
with rc_context(rc_options):
    fig, ax = plt.subplots()

    # plot interpolated values
    real_valued_Z = interp_Z[~np.isnan(interp_Z)]
    step_exp = 0.25
    levels_exp = np.arange(
        np.floor(np.log10(real_valued_Z.min()) - 1),
        np.ceil(np.log10(real_valued_Z.max()) + 1) + step_exp,
        step=step_exp,
    )
    levels = np.power(10, levels_exp)

    cs = ax.contourf(
        x_grid,
        y_grid,
        interp_Z,
        cmap="PuBu_r",
        levels=levels,
        norm=colors.LogNorm(vmin=levels.min(), vmax=levels.max()),
    )
    formatter = LogFormatterSciNotation(10, labelOnlyBase=False)
    cbar = fig.colorbar(cs, format=formatter)

    # plot observed values
    scatter_size = 15.0
    ax.scatter(x, y, s=scatter_size, color="white", edgecolors="black")

    ax.set_xlabel(r"$x$")
    ax.set_ylabel(r"$y$")
    cbar.set_label(r"$z(x, y)$")

    file_types = ["png", "pdf"]
    for extension in file_types:
        fig.savefig(f"example.{extension}")