问Matplotlib :如何在x logscale轴上显示和增加次要刻度和主要刻度的大小

EN

[1e-8, 1e-6, 1e-4, 1e-2, 1]

  # Important otherwise missing ticks
  plt.xticks([1e-8, 1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1])

# Modules import
import sys
import numpy as np
import scipy.integrate as pyint
import os
from os import path
import glob
import scipy
import re
import shutil
import matplotlib.pyplot as plt 
from matplotlib import ticker

# Initialize figure
fig = plt.figure(num=None, figsize=(12, 12), facecolor='w', edgecolor='k')
fig.patch.set_facecolor('white')
fig.patch.set_alpha(1)

# Control on graphic
ax = plt.gca()

# Increase space between x-axis and x-label
ax.tick_params(axis = 'x', which = 'major', pad = 15)

# Lebels on axis
plt.xlabel('Step $\Omega_{m}$', fontsize = 20)
plt.ylabel('$C_{\ell}^{\'}$($\Omega_{m}$) relative', fontsize = 20)
plt.xticks(fontsize = 20)
plt.yticks(fontsize = 20)
plt.xscale('log')
plt.grid()

# Important otherwise missing ticks
plt.xticks([1e-8, 1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1])

# Title : different multipoles
string_intel = '(CAMB-0.1.7) - '+type_GG_LL_GL+' - $C_{\ell}^{\'}$ relative of '+paramLatexArray[idParam]+'('+str(der)+' pts) at $z$ = '+str(zrange[idRedshift])+' - '+str(numel)+' pts'
plt.title(string_intel, fontsize = 20, pad = 25)

colorSimplePlot = ['b', 'r', 'g', 'k', 'y', 'm', 'c']

# Plot command 
for idMultipole in range(len(multipole)):
  plt.plot(stepNewArray[:], eval('matrixCl_der_'+str(der)+'[:, idMultipole, idParam, lx, ly]'), colorSimplePlot[idMultipole])

# Chose if negative or positive derivatives
# Plot with symlog or log along y-axis
# 1) For example : GG at z = 2.038 and l = 366
#    needs symlog with lintreshy = 1e-9
# 2) For example : LL at z = 2.038 and l = 366
#    needs nothing (even no log)
if (type_GG_LL_GL == 'GG'):
  plt.yscale('symlog', linthreshy = 1e-9)
elif (type_GG_LL_GL == 'LL'):
  plt.yscale('linear')

# Legend
plt.legend(['$l = 366.42$', '$l = 1079.28$', '$l = 1792.14$', '$l = 2505$',\
        '$l = 3217.85$', '$l = 3930.71$', '$l = 4643.57$'], fontsize=15, loc='best')

# Save plot
plt.savefig('Cl_derivative_Omega_m.pdf')

from matplotlib import ticker
from matplotlib.ticker import LogLocator

ax.tick_params(axis = 'x', which = 'major', pad = 15)
ax.xaxis.set_major_locator(LogLocator(base=10))
ax.xaxis.set_major_locator(LogLocator(base=10, subs=[1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0]))

  minors = (0.1**np.arange(9)[:,None] * np.arange(0.1,1,0.1)).ravel()
  plt.yticks(fontsize = 20)
  plt.xscale('log')
  # Important otherwise missing ticks
  plt.xticks([1e-8, 1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1], fontsize = 40)
  plt.xticks(minors, fontsize = 20)
  plt.grid()