bwanalyzer recursive calculation object to graph.

recursive_df_obj_to_graph.py

import bw2data as bd
import bw2analyzer as bwa
import networkx as nx

# Make sure to set the right project.
A_PROJECT = "STeamPunk"
bd.projects.set_current(A_PROJECT)
# Where does the LCA fu come from?
FG_DB = "vent_eco"
a = bd.Database(FG_DB).random()
m_key = ('EF v3.1', 'climate change', 'global warming potential (GWP100)')

df = bwa.utils.recursive_calculation_to_object(a, m_key, as_dataframe=True)

def ca_graph(df, graph=None):
    data_keys = ["score", "fraction", "amount", "name", "key"]
    if graph is None:
        graph = nx.DiGraph()
    for _, row in df.iterrows():
        node_data = {k:row[k] for k in data_keys}
        graph.add_node(row['label'], **node_data)
        if not pd.isna(row['parent']):
            graph.add_edge(row['parent'], row['label'])

    return graph