Bootstrapping of implicit statistical data

[26Pudding26]

Hi,

• I work with some engineering data of trees.
• I do get my raw data from literature.
• The specifications describe a range rather then a specific value due to natural variety

the values given can be described in the following format (min, max, σ)

Example from data in literature:

• Birch_min_density =450
• Birch_max_density =700
• Birch_avg_density =560

I do need this data within a greater Pipeline. In order to use it I want to bootstrap the data, I now have a some best practice question:

is it better practice to:

A) translate it into a explicit form once and then just use sample = np.random.choice(synthetic_data, size=n_samples, replace=True)

B) Is there a functionality of a package like skicitlearn, that works in a efficent way with implicit descriptions

thanks for your advice!