Axes.axes.secondary_xaxis does not produce good ticks with some transformations

Bug report

Bug summary

If I supply a nonlinear transformation to secondary_xaxis, it produces overlapping tick positions, at least when I do not use a logarithmic scale, see images below.

Code for reproduction

import matplotlib.pyplot as plt
import numpy as np

c = 299792458.0

fig, ax1 = plt.subplots()
ax1.plot((1e16, 1e19), (0, 1))
ax1.set_xlim(1e16, 1e19)
ax1.set_xlabel(r'$\omega/\mathrm{s^{-1}}$')
ax2 = ax1.secondary_xaxis(-0.15, functions=(
    lambda omega: 2 * np.pi * c / omega,
    lambda lambda_: 2 * np.pi * c / lambda_)
)
ax2.set_xlabel(r'$\lambda/\mathrm{m}$')
plt.tight_layout()
plt.savefig('issue1.png')

ax1.set_xscale('log')
plt.savefig('issue2.png')

Actual outcome
Linear:

Logarithmic:

Expected outcome

Nice tick placement in both variants.

Matplotlib version

• Operating system: Arch Linux
• Matplotlib version (import matplotlib; print(matplotlib.__version__)): 3.4.1
• Matplotlib backend (print(matplotlib.get_backend())): Qt5Agg
• Python version: 3.9

Comece executando a reprodução fornecida com secondary_xaxis, primeiro no caso linear e depois com a escala logarítmica, para observar as posições sobrepostas dos ticks. Rastreie como secondary_xaxis gera e transforma os ticks; considera-se concluído quando ambas as variantes produzem um posicionamento de ticks legível e sem sobreposição.