def collect_data(self):
# Initialize data
data = {}
# Iterate through all nodes
for nid, node in self.env.nodes.items():
# If no generators in this node, return
if not node.generators:
data[nid] = pd.DataFrame()
continue
# Get all the bundles sent
sent = concat_dfs(
{
gid: gen.list_bundles()
for gid, gen in node.generators.items()
}, 'generator_id')
# Store data
data[nid] = sent
# Create the total data frame
df = concat_dfs(data, 'node')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df
def collect_data(self):
# Get the bundles stored in all the node's radios
df = concat_dfs({nid: concat_dfs({rid: r.stored for rid, r in node.radios.items()}, 'radio')
for nid, node in self.env.nodes.items()}, 'node')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df
def collect_data(self):
# Get the bundles stored in all the node's neighbor queues
df = concat_dfs({nid: concat_dfs({(n, b, t): d.stored for n, v in node.ducts.items()
for b, vv in v.items() for t, d in vv.items()},
('neighbor', 'band', 'duct_type', 'idx'))
for nid, node in self.env.nodes.items()}, 'node')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df
def collect_data(self):
# Initialize variables
res = {}
# Iterate over nodes
for nid, node in self.env.nodes.items():
q = node.limbo_queue
# No items in this queue
if not any(q.items):
continue
# The first element of the item is the bundle in the limbo queue
d = {i: d[0].to_dict() for i, d in enumerate(q.items)}
# Save data
res[nid] = pd.DataFrame.from_dict(d, orient='index')
# Get the bundles stored in all the node's radios
df = concat_dfs(res, 'node')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df
def collect_data(self):
# Get the bundles stored in all the node's neighbor queues
df = concat_dfs(
{
nid: concat_dfs(
{
neighbor: node.queues[neighbor].stored
for neighbor in node.neighbors
}, 'neighbor')
for nid, node in self.env.nodes.items()
}, 'node')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df
def collect_data(self):
# Get all the bundles that arrived in this node
df = concat_dfs(
{
nid: pd.DataFrame(bundle.to_dict() for bundle in node.dropped)
for nid, node in self.env.nodes.items()
}, 'node')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df
def collect_data(self):
# Get the bundles lost in a connection
df = concat_dfs(
{
cid: conn.list_sent()
for cid, conn in self.env.connections.items()
}, 'connection')
# Transform to string to save space. You can use a converter when loading
if 'visited' in df: df.visited = df.visited.apply(lambda v: str(v))
return df