def matches(self):
session = Session()
q = session.query(Matches)
qf = q.filter(Matches.source == self.source['node_id'],
Matches.destination == self.destination['node_id'])
odf = pd.read_sql(qf.statement, q.session.bind).set_index('id')
df = pd.DataFrame(odf.values, index=odf.index.values, columns=odf.columns.values)
df.index.name = 'id'
# Explicit close to get the session cleaned up
session.close()
return DbDataFrame(df,
parent=self,
name='matches')
def masks(self):
res = Session().query(Edges.masks).\
filter(Edges.source == self.source['node_id']).\
filter(Edges.destination == self.destination['node_id']).\
first()
if res:
df = pd.DataFrame.from_records(res[0])
df.index = df.index.map(int)
else:
ids = list(map(int, self.matches.index.values))
df = pd.DataFrame(index=ids)
df.index.name = 'match_id'
return DbDataFrame(df, parent=self, name='masks')
def costs(self):
# these are np.float coming out, sqlalchemy needs ints
ids = list(map(int, self.matches.index.values))
res = Session().query(Costs).filter(Costs.match_id.in_(ids)).all()
#qf = q.filter(Costs.match_id.in_(ids))
if res:
# Parse the JSON dicts in the cost field into a full dimension dataframe
costs = {r.match_id:r._cost for r in res}
df = pd.DataFrame.from_records(costs).T # From records is important because from_dict drops rows with empty dicts
else:
df = pd.DataFrame(index=ids)
df.index.name = 'match_id'
return DbDataFrame(df, parent=self, name='costs')