def optimize(
yml_file,
draw,
show_balances,
basic,
):
if not yml_file:
yml_file = stdin
ledger = yaml.load(yml_file)
optimized_graph, optimized_ledger = optimize_debts_from_ledger(ledger, basic=basic)
yaml.dump(optimized_ledger, stdout, default_flow_style=False)
if draw:
import matplotlib.pyplot as plt
pos = nx.spring_layout(optimized_graph)
nx.draw(
optimized_graph,
pos=pos,
node_color='white',
node_size=3000,
with_labels=True
)
edge_labels = {
(u, v): format_amount(data['amount'])
for u, v, data in optimized_graph.edges_iter(data=True)
}
nx.draw_networkx_edge_labels(
optimized_graph,
pos=pos,
edge_labels=edge_labels
)
if show_balances:
node_labels = {
node: format_amount(data['orig_balance'])
for node, data in optimized_graph.nodes_iter(data=True)
}
elevated_pos = {
key: (x, y + 5 / 100)
for key, (x, y) in pos.items()
}
nx.draw_networkx_labels(
optimized_graph,
pos=elevated_pos,
labels=node_labels,
font_weight='bold'
)
plt.show()
def build_transactions_from_ledger(ledger: dict):
transactions = []
for debtor, debts in ledger.items():
for creditor, amount in debts.items():
tx = dict(
debtor=debtor,
creditor=creditor,
amount=format_amount(amount)
)
transactions.append(tx)
return transactions
def optimize(
yml_file,
draw,
show_balances,
basic,
):
if not yml_file:
yml_file = stdin
ledger = yaml.load(yml_file)
optimized_graph, optimized_ledger = optimize_debts_from_ledger(ledger,
basic=basic)
yaml.dump(optimized_ledger, stdout, default_flow_style=False)
if draw:
import matplotlib.pyplot as plt
pos = nx.spring_layout(optimized_graph)
nx.draw(optimized_graph,
pos=pos,
node_color='white',
node_size=3000,
with_labels=True)
edge_labels = {(u, v): format_amount(data['amount'])
for u, v, data in optimized_graph.edges_iter(data=True)}
nx.draw_networkx_edge_labels(optimized_graph,
pos=pos,
edge_labels=edge_labels)
if show_balances:
node_labels = {
node: format_amount(data['orig_balance'])
for node, data in optimized_graph.nodes_iter(data=True)
}
elevated_pos = {
key: (x, y + 5 / 100)
for key, (x, y) in pos.items()
}
nx.draw_networkx_labels(optimized_graph,
pos=elevated_pos,
labels=node_labels,
font_weight='bold')
plt.show()