def get_edge_dataframe(infr, edges=None, all=False):
import pandas as pd
if edges is None:
edges = infr.edges()
edge_datas = {e: infr.get_nonvisual_edge_data(e) for e in edges}
edge_datas = {
e: {k: None for k in infr.feedback_data_keys} if d is None else d
for e, d in edge_datas.items()
}
edge_df = pd.DataFrame.from_dict(edge_datas, orient='index')
part = ['evidence_decision', 'meta_decision', 'tags', 'user_id']
neworder = ut.partial_order(edge_df.columns, part)
edge_df = edge_df.reindex(neworder, axis=1)
if not all:
edge_df = edge_df.drop(
[
'review_id',
'timestamp',
'timestamp_s1',
'timestamp_c2',
'timestamp_c1',
],
axis=1,
)
# pd.DataFrame.from_dict(edge_datas, orient='list')
return edge_df
def get_aug_df(edges):
df = infr.get_edge_dataframe(edges)
if len(df):
df.index.names = ('aid1', 'aid2')
nids = np.array(
[infr.pos_graph.node_labels(u, v) for u, v in list(df.index)]
)
df = df.assign(nid1=nids.T[0], nid2=nids.T[1])
part = ['nid1', 'nid2', 'evidence_decision', 'tags', 'user_id']
neworder = ut.partial_order(df.columns, part)
df = df.reindex(neworder, axis=1)
df = df.drop(['review_id', 'timestamp'], axis=1)
return df
def pandas_reorder(df, part):
import utool as ut
df = df.reindex_axis(ut.partial_order(df.columns, part), axis=1)