import numpy as np
import matplotlib.pyplot as plt

# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
data1 = np.exp(t)
data2 = np.sin(2 * np.pi * t)

fig1, ax1 = plt.subplots(num='1')

color = 'tab:red'
ax1.set_xlabel('time (s)')
ax1.set_ylabel('exp', color=color)
ax1.set_xscale('log')  # set x axis to log scale
ax1.plot(t, data1, color=color)
ax1.tick_params(axis='y', labelcolor=color)

ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis

color = 'tab:blue'
ax2.set_ylabel('sin', color=color)  # we already handled the x-label with ax1
ax2.plot(t, data2, color=color)
ax2.tick_params(axis='y', labelcolor=color)

fig1.tight_layout()  # otherwise the right y-label is slightly clipped
plt.show()

fig2, ax3 = plt.subplots(num='2')

color = 'tab:red'
ax3.set_xlabel('time (s)')
ax3.set_ylabel('exp', color=color)
ax3.plot(t, data1, color=color)
ax3.tick_params(axis='y', labelcolor=color)

ax4 = ax3.twinx()  # instantiate a second axes that shares the same x-axis

# set log scale for both axis
for ax in [ax3, ax4]:
    ax.set_xscale('log')

color = 'tab:blue'
ax4.set_ylabel('sin', color=color)  # we already handled the x-label with ax3
ax4.plot(t, data2, color=color)
ax4.tick_params(axis='y', labelcolor=color)

fig2.tight_layout()  # otherwise the right y-label is slightly clipped
plt.show()