[Bug]: xlim not calculated correctly for inverted log plot #32336

# Demonstrates problem with xlim in recent (3.10.9) version
# of matplotlib. In 3.10.9, all of the data are pushed off 
# to one side of the figure. 

# In matplotlib 3.2.2, the data are appropriately distributed 
# across the plot.

import numpy as np
import matplotlib.pyplot as plt

# Some data to plot.
res = np.array([2.82481734, 2.60724989, 2.03974669, 1.4043936 ])
res_err = np.array([0.1, 0.1, 0.1 , 0.1])

ph = np.array([-3.09230529,  2.65380027,  1.50135906,  2.74889725])
ph_err = np.array([0.1, 0.1, 0.1 , 0.1])

freqs = np.array([ 687.5  ,  875.   , 1328.125, 6281.25 ])

# Figure setup.
gs_top = plt.GridSpec(3, 1, hspace=0)
gs_base = plt.GridSpec(3, 1)
fig = plt.figure()

ax_res = fig.add_subplot(gs_top[0, :])
ax_res.invert_xaxis()
ax_res.set_xscale('log')

ax_ph = fig.add_subplot(gs_top[1, :], sharex=ax_res)
ax_ph.set_xscale('log')

ax_pseudo = fig.add_subplot(gs_base[2, :])

# Shows the problem better with grids on.
ax_res.grid(axis='both', which='both')
ax_ph.grid(axis='both', which='both')
ax_pseudo.grid(axis='both', which='both')

# Plot the data.
ax_res.errorbar(freqs, res, yerr=res_err, fmt='o')

ax_ph.errorbar(freqs, ph*180/np.pi, yerr=ph_err*180/np.pi, fmt='o')

skins = np.array([100, 200, 400, 800])
ax_pseudo.plot(skins, res, 'o')

fig.show()