def balance_correlation_and_plot(graph: nx.MultiDiGraph) -> tuple:
"""
Calculate the coefficient of determination (r^2) b/w the number of transactions to/from
an account and it's ether balance, and the root mean squared value
of the linear model that gives this r^2 value.
Scatter Plot the number of transactions to/from an account and it's ether balance
Return results in tuple of the form (r^2, rmse)
"""
# Choose a random seed (stays the same each time for reproducible results)
np.random.seed(1212)
# Dictionary accumulator that maps the balance of a UNIQUE account
# to its degree (the sum of all transactions that it has both sent
# and received).
account_data = {}
for node in graph.nodes():
if graph.nodes[node] != {}:
balance = graph.nodes[node]['balance']
# This gets marked as error, but it is correct according to nx docs.
degree = graph.degree(node)
# Add pairing as an entry to the dictionary.
account_data[balance] = degree
# Convert the predictor data (balance) and response data (number of
# transactions) into numpy arrays.
balance_x = np.array(list(account_data)).reshape((-1, 1))
transactions_y = np.array(list(account_data.values())).reshape(-1, 1)
# Create a dataframe with the two variables as columns.
ether_df = pd.DataFrame(list(account_data.items()),
columns=['balance', 'degree'])
# Create the model.
lin_reg = linear_model.LinearRegression()
# Perform a train/test split on the data.
balance_train, balance_test, transaction_train, transaction_test \
= train_test_split(balance_x, transactions_y, test_size=0.2)
# Train the model
reg_model = lin_reg.fit(balance_train, transaction_train)
# Compute Coefficient of determination
r2 = reg_model.score(balance_test, transaction_test)
# Compute RMSE
predictions = reg_model.predict(transaction_test)
rmse = metrics.mean_squared_error(y_true=balance_test,
y_pred=predictions,
squared=False)
# plot
fig = px.scatter(ether_df,
x='balance',
y='degree',
title="Degree vs. Balance Scatter Plot",
labels={"Balance", "Degree"})
fig.show()
return (abs(r2), rmse)
class NxGraph(BaseGraph):
"""
NxGraph is a wrapper that provides methods to interact with a networkx.MultiDiGraph.
NxGraph extends kgx.graph.base_graph.BaseGraph and implements all the methods from BaseGraph.
"""
def __init__(self):
super().__init__()
self.graph = MultiDiGraph()
self.name = None
def add_node(self, node: str, **kwargs: Any) -> None:
"""
Add a node to the graph.
Parameters
----------
node: str
Node identifier
**kwargs: Any
Any additional node properties
"""
if "data" in kwargs:
data = kwargs["data"]
else:
data = kwargs
self.graph.add_node(node, **data)
def add_edge(self,
subject_node: str,
object_node: str,
edge_key: str = None,
**kwargs: Any) -> None:
"""
Add an edge to the graph.
Parameters
----------
subject_node: str
The subject (source) node
object_node: str
The object (target) node
edge_key: Optional[str]
The edge key
kwargs: Any
Any additional edge properties
"""
if "data" in kwargs:
data = kwargs["data"]
else:
data = kwargs
return self.graph.add_edge(subject_node,
object_node,
key=edge_key,
**data)
def add_node_attribute(self, node: str, attr_key: str,
attr_value: Any) -> None:
"""
Add an attribute to a given node.
Parameters
----------
node: str
The node identifier
attr_key: str
The key for an attribute
attr_value: Any
The value corresponding to the key
"""
self.graph.add_node(node, **{attr_key: attr_value})
def add_edge_attribute(
self,
subject_node: str,
object_node: str,
edge_key: Optional[str],
attr_key: str,
attr_value: Any,
) -> None:
"""
Add an attribute to a given edge.
Parameters
----------
subject_node: str
The subject (source) node
object_node: str
The object (target) node
edge_key: Optional[str]
The edge key
attr_key: str
The attribute key
attr_value: Any
The attribute value
"""
self.graph.add_edge(subject_node,
object_node,
key=edge_key,
**{attr_key: attr_value})
def update_node_attribute(self,
node: str,
attr_key: str,
attr_value: Any,
preserve: bool = False) -> Dict:
"""
Update an attribute of a given node.
Parameters
----------
node: str
The node identifier
attr_key: str
The key for an attribute
attr_value: Any
The value corresponding to the key
preserve: bool
Whether or not to preserve existing values for the given attr_key
Returns
-------
Dict
A dictionary corresponding to the updated node properties
"""
node_data = self.graph.nodes[node]
updated = prepare_data_dict(node_data, {attr_key: attr_value},
preserve=preserve)
self.graph.add_node(node, **updated)
return updated
def update_edge_attribute(
self,
subject_node: str,
object_node: str,
edge_key: Optional[str],
attr_key: str,
attr_value: Any,
preserve: bool = False,
) -> Dict:
"""
Update an attribute of a given edge.
Parameters
----------
subject_node: str
The subject (source) node
object_node: str
The object (target) node
edge_key: Optional[str]
The edge key
attr_key: str
The attribute key
attr_value: Any
The attribute value
preserve: bool
Whether or not to preserve existing values for the given attr_key
Returns
-------
Dict
A dictionary corresponding to the updated edge properties
"""
e = self.graph.edges((subject_node, object_node, edge_key),
keys=True,
data=True)
edge_data = list(e)[0][3]
updated = prepare_data_dict(edge_data, {attr_key: attr_value},
preserve)
self.graph.add_edge(subject_node, object_node, key=edge_key, **updated)
return updated
def get_node(self, node: str) -> Dict:
"""
Get a node and its properties.
Parameters
----------
node: str
The node identifier
Returns
-------
Dict
The node dictionary
"""
n = {}
if self.graph.has_node(node):
n = self.graph.nodes[node]
return n
def get_edge(self,
subject_node: str,
object_node: str,
edge_key: Optional[str] = None) -> Dict:
"""
Get an edge and its properties.
Parameters
----------
subject_node: str
The subject (source) node
object_node: str
The object (target) node
edge_key: Optional[str]
The edge key
Returns
-------
Dict
The edge dictionary
"""
e = {}
if self.graph.has_edge(subject_node, object_node, edge_key):
e = self.graph.get_edge_data(subject_node, object_node, edge_key)
return e
def nodes(self, data: bool = True) -> Dict:
"""
Get all nodes in a graph.
Parameters
----------
data: bool
Whether or not to fetch node properties
Returns
-------
Dict
A dictionary of nodes
"""
return self.graph.nodes(data)
def edges(self, keys: bool = False, data: bool = True) -> Dict:
"""
Get all edges in a graph.
Parameters
----------
keys: bool
Whether or not to include edge keys
data: bool
Whether or not to fetch node properties
Returns
-------
Dict
A dictionary of edges
"""
return self.graph.edges(keys=keys, data=data)
def in_edges(self,
node: str,
keys: bool = False,
data: bool = False) -> List:
"""
Get all incoming edges for a given node.
Parameters
----------
node: str
The node identifier
keys: bool
Whether or not to include edge keys
data: bool
Whether or not to fetch node properties
Returns
-------
List
A list of edges
"""
return self.graph.in_edges(node, keys=keys, data=data)
def out_edges(self,
node: str,
keys: bool = False,
data: bool = False) -> List:
"""
Get all outgoing edges for a given node.
Parameters
----------
node: str
The node identifier
keys: bool
Whether or not to include edge keys
data: bool
Whether or not to fetch node properties
Returns
-------
List
A list of edges
"""
return self.graph.out_edges(node, keys=keys, data=data)
def nodes_iter(self) -> Generator:
"""
Get an iterable to traverse through all the nodes in a graph.
Returns
-------
Generator
A generator for nodes where each element is a Tuple that
contains (node_id, node_data)
"""
for n in self.graph.nodes(data=True):
yield n
def edges_iter(self) -> Generator:
"""
Get an iterable to traverse through all the edges in a graph.
Returns
-------
Generator
A generator for edges where each element is a 4-tuple that
contains (subject, object, edge_key, edge_data)
"""
for u, v, k, data in self.graph.edges(keys=True, data=True):
yield u, v, k, data
def remove_node(self, node: str) -> None:
"""
Remove a given node from the graph.
Parameters
----------
node: str
The node identifier
"""
self.graph.remove_node(node)
def remove_edge(self,
subject_node: str,
object_node: str,
edge_key: Optional[str] = None) -> None:
"""
Remove a given edge from the graph.
Parameters
----------
subject_node: str
The subject (source) node
object_node: str
The object (target) node
edge_key: Optional[str]
The edge key
"""
self.graph.remove_edge(subject_node, object_node, edge_key)
def has_node(self, node: str) -> bool:
"""
Check whether a given node exists in the graph.
Parameters
----------
node: str
The node identifier
Returns
-------
bool
Whether or not the given node exists
"""
return self.graph.has_node(node)
def has_edge(self,
subject_node: str,
object_node: str,
edge_key: Optional[str] = None) -> bool:
"""
Check whether a given edge exists in the graph.
Parameters
----------
subject_node: str
The subject (source) node
object_node: str
The object (target) node
edge_key: Optional[str]
The edge key
Returns
-------
bool
Whether or not the given edge exists
"""
return self.graph.has_edge(subject_node, object_node, key=edge_key)
def number_of_nodes(self) -> int:
"""
Returns the number of nodes in a graph.
Returns
-------
int
"""
return self.graph.number_of_nodes()
def number_of_edges(self) -> int:
"""
Returns the number of edges in a graph.
Returns
-------
int
"""
return self.graph.number_of_edges()
def degree(self):
"""
Get the degree of all the nodes in a graph.
"""
return self.graph.degree()
def clear(self) -> None:
"""
Remove all the nodes and edges in the graph.
"""
self.graph.clear()
@staticmethod
def set_node_attributes(graph: BaseGraph, attributes: Dict) -> None:
"""
Set nodes attributes from a dictionary of key-values.
Parameters
----------
graph: kgx.graph.base_graph.BaseGraph
The graph to modify
attributes: Dict
A dictionary of node identifier to key-value pairs
"""
return set_node_attributes(graph.graph, attributes)
@staticmethod
def set_edge_attributes(graph: BaseGraph, attributes: Dict) -> None:
"""
Set nodes attributes from a dictionary of key-values.
Parameters
----------
graph: kgx.graph.base_graph.BaseGraph
The graph to modify
attributes: Dict
A dictionary of node identifier to key-value pairs
Returns
-------
Any
"""
return set_edge_attributes(graph.graph, attributes)
@staticmethod
def get_node_attributes(graph: BaseGraph, attr_key: str) -> Dict:
"""
Get all nodes that have a value for the given attribute ``attr_key``.
Parameters
----------
graph: kgx.graph.base_graph.BaseGraph
The graph to modify
attr_key: str
The attribute key
Returns
-------
Dict
A dictionary where nodes are the keys and the values
are the attribute values for ``key``
"""
return get_node_attributes(graph.graph, attr_key)
@staticmethod
def get_edge_attributes(graph: BaseGraph, attr_key: str) -> Dict:
"""
Get all edges that have a value for the given attribute ``attr_key``.
Parameters
----------
graph: kgx.graph.base_graph.BaseGraph
The graph to modify
attr_key: str
The attribute key
Returns
-------
Dict
A dictionary where edges are the keys and the values
are the attribute values for ``attr_key``
"""
return get_edge_attributes(graph.graph, attr_key)
@staticmethod
def relabel_nodes(graph: BaseGraph, mapping: Dict) -> None:
"""
Relabel identifiers for a series of nodes based on mappings.
Parameters
----------
graph: kgx.graph.base_graph.BaseGraph
The graph to modify
mapping: Dict
A dictionary of mapping where the key is the old identifier
and the value is the new identifier.
"""
relabel_nodes(graph.graph, mapping, copy=False)
