One parameter of my problem in Sobol sensitivity analysis has lognormal distribution as below: [![enter image description here][1]][1]

When I define it in "problem" as "lognorm" the generated samples look very different, for example the peak density happens around 1 instead of 0.7: [![enter image description here][2]][2]

 from SALib.sample import sobol
 from SALib.sample import sobol
 import matplotlib.pyplot as plt
 problem = {
    'num_vars': 2,
    'names': ['x', 'z'],
    'bounds': [[0.302, 0.529], [0, 1]],
    'dists': ['lognorm', 'unif']
 }

 param_values = sobol.sample(problem, 1024)`
 plt.hist(param_values[:, 0], bins=30, density=True, alpha=0.6, color='g')
 plt.xlabel('x')
 plt.ylabel('Density')
 plt.title('Histogram of generated Samples for x (Lognormal Distribution)')
 plt.grid(True)
 plt.show()

the definition of lognorm distribution in SALib seems different, it does not even use the "shape" parameter of the lognormal distribution. Here is the screenshot: [![enter image description here][3]][3]

My question is: HOW can I correctly define my lognoraml parameter in the code. I appreciate your inputs.
[1]: .png [2]: .png [3]: .png