Read BN Structure from a File, Learn Distribution Parameters

Used imports:

from bamt.preprocessors import Preprocessor
import pandas as pd
from sklearn import preprocessing as pp
from bamt.networks.hybrid_bn import HybridBN
import json

There are two options for loading a BN structure. The first is to read it directly from a JSON file:

bn = HybridBN(use_mixture=True, has_logit=True)

bn2.load("structure.json")

The second one is to set it manually using list of edges, but first nodes should be added:

encoder = preprocessing.LabelEncoder()
discretizer = preprocessing.KBinsDiscretizer(n_bins=5, encode='ordinal', strategy='quantile')

p = pp.Preprocessor([('encoder', encoder), ('discretizer', discretizer)])
discretized_data, est = p.apply(data)

info = p.info

bn.add_nodes(info)

structure = [("Tectonic regime", "Structural setting"),
            ("Gross", "Netpay"),
            ("Lithology", "Permeability")]

bn.set_structure(edges=structure)

The next step is to learn parameters from data, to do this we need to read the data and perform parameters learning:

# reading data
data = pd.read_csv("data.csv")

# parameters learning
bn.fit_parameters(data)