How to create a pore distribution manually

[livashu]

I would like to create a pore distribution manually from experimental data without using Weibull distribution.
Is there a good way to do this?
Is there any way to read a graph created in Excel, for example?

[jgostick]

So you're saying that you have some like a histogram, and you want to add pores in proportion to height of each bar in your histogram. We do not have a function for this explicitly, but it should be do-able:

import numpy as np
import matplotlib.pyplot as plt
N = 1000  # N is the total number of pores diameter you want to generate
bin_centers = [0.5, 2.1, 3.3, 4.0, 5.0]  # In what ever units you like
bin_height = [0.05, 0.2, 0.4, 0.3, 0.15]  # Normalized to sum to 1.0
r = np.zeros(N)  
i = 0
while i < N:
    bin = np.random.randint(len(bin_centers))
    if np.random.rand() < bin_height[bin]:
        r[i] = bin_centers[bin]
        i += 1
plt.hist(r)

[livashu]

I managed to succeed. Thank you!

[mourendong]

I also wanted to create a pore distribution from experimental data.
As the way mentioned above, I just created the histogram, how to apply it to the size distribution of the pore network?
Can you tell me more detail about it?

[jgostick]

Once you get the values in r, you assign them to your geometry object, like geo['pore.diameter'] = r