import numpy as np
import matplotlib.pyplot as plt
import corner
 
n_samples = 10000
n_parameters = 3
samples = np.random.randn(n_samples, n_parameters)
 
fig = corner.corner(samples,
                    show_titles=True,
                    labels=['X1', 'X2', 'X3'])
 
axes = np.array(fig.axes).reshape((n_parameters, n_parameters))
 
for i in range(n_parameters):
    for j in range(i + 1, n_parameters):
        if i == j:
            if i == 0 or i == 2:
                axes[i, j].set_xscale('log')
        if i > j:
            if j == 0 or j == 2:
                axes[i, j].set_xscale('linear')
            if i == 0 or i == 2:
                axes[i, j].set_yscale('log')
 
plt.show()

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