networkx_function#

generate_and_connect_segment_from_linestring_list(linestring_list: list[LineString]) → list[LineString][source]#

Generate unitary segments from a list of LineString objects and ensure every segment is connected in a NetworkX graph sense:

  1. Break down the LineString objects: Divide each LineString into its individual segments, each defined by two consecutive points (start and end).

  2. Build a graph: Create a NetworkX graph where each segment is an edge, and the endpoints of the segments serve as nodes.

  3. Define every connected subgraph.

  4. Connect every subgraph finding the smallest segments needed.

Parameters:

linestring_list (list[LineString]) – The list of LineString objects.

Returns:

The list of connected LineString segments.

Return type:

list[LineString]

generate_bfs_tree_with_edge_data(graph: Graph, source)[source]#

Create a BFS tree from a graph while retaining edge data.

Parameters:

  • graph (nx.Graph) – The input graph.

  • source (node) – The starting node for BFS.

Returns:

A directed BFS tree with edge data preserved.

Return type:

nx.DiGraph

generate_nx_edge(data: Expr, nx_graph: Graph) → Expr[source]#

Generate edges in a NetworkX graph from a Polars expression.

Parameters:

  • data (pl.Expr) – The Polars expression containing edge data.

  • nx_graph (nx.Graph) – The NetworkX graph.

Returns:

The Polars expression with edges added to the graph.

Return type:

pl.Expr

generate_shortest_path_length_matrix(nx_grid: Graph, weight_name: str | None = None, forced_weight: int | float | None = None)[source]#

Generate a matrix of shortest path lengths between all pairs of nodes in a graph.

Parameters:

  • nx_graph (nx.Graph) – The graph to process.

  • weight (str, optional) – The edge attribute to use as weight. Default is ‘weight’.

  • forced_weight (Optional[Union[int, float]], optional) – The weight to use for all edges. Default is None.

Returns:

A GraphBlas matrix where the rows and columns represent the nodes (from and to), and the values represent the shortest path lengths.

Return type:

gb.Matrix

generate_tree_graph_from_edge_data(edge_data: DataFrame, slack_node_id: str | int | float, data_name: list[str] | None = None) → DiGraph[source]#

Generate a tree graph from edge data and a specified slack node.

Parameters:

  • edge_data (pl.DataFrame) – The Polars DataFrame containing edge data.

  • slack_node_id (Union[str, int, float]) – The ID of the slack node.

  • data_name (Optional[list[str]], optional) – The list of edge data names to include. Defaults to None.

Returns:

The generated tree graph with edge data preserved.

Return type:

nx.DiGraph

Raises:

ValueError – If the edge data names are invalid or if the grid is not a connected tree.

Example: >>> import polars as pl >>> import networkx as nx >>> edge_data = pl.DataFrame({ … “u_of_edge”: [“A”, “C”, “C”], … “v_of_edge”: [“B”, “B”, “D”], … “weight”: [1, 2, 3] … }) >>> slack_node_id = “A” >>> tree_graph = generate_tree_graph_from_edge_data(edge_data, slack_node_id) >>> print(tree_graph.edges(data=True)) [(“A”, “B”, {“weight”: 1}), (“B”, “C”, {“weight”: 2}), (“C”, “D”, {“weight”: 3})]

get_all_edge_data(nx_graph: Graph) → DataFrame[source]#

Get every edge data from a NetworkX graph.

Parameters:

nx_graph (nx.Graph) – The NetworkX graph.

Returns:

Polar DataFrame containing every edge data.

Return type:

pl.DataFrame

get_connected_edges_data(nx_graph: Graph) → DataFrame[source]#

Group all edges that are connected together in a NetworkX graph and return the result as a Polars DataFrame.

Parameters:

nx_graph (nx.Graph) – The NetworkX graph.

Returns:

A Polars DataFrame containing the connected edges with columns graph_id , u_of_edge, v_of_edge, and every edge attribute.

Return type:

pl.DataFrame

get_edge_data_from_node_list(node_list: list, nx_graph: Graph) → list[dict][source]#

Get edge data for a list of nodes from a NetworkX graph.

Parameters:

  • node_list (list) – The list of node IDs.

  • nx_graph (nx.Graph) – The NetworkX graph.

Returns:

The list of dictionaries containing every edge data.

Return type:

list[dict]

get_edge_data_list(nx_graph: Graph, data_name: str) → list[source]#

Get a list of edge data from a NetworkX graph.

Parameters:

  • nx_graph (nx.Graph) – The NetworkX graph.

  • data_name (str) – The name of the edge data to retrieve.

Returns:

The list of edge data.

Return type:

list

get_edge_param_from_node_list(node_list: list, nx_graph: Graph, data_name: str) → list[dict][source]#

Get edge parameter from a list of nodes from a NetworkX graph.

Parameters:

  • node_list (list) – The list of node IDs.

  • nx_graph (nx.Graph) – The NetworkX graph.

  • data_name (str) – The name of the edge parameter to retrieve.

Returns:

The list of dictionaries containing every edge data.

Return type:

list[dict]

get_node_neighbor_edge_data(nx_graph: Graph, node)[source]#

Get the edge data for all neighbors of a specified node in a graph.

Parameters:

  • nx_graph (nx.Graph) – The graph to search.

  • node (node) – The node whose neighbors’ edge data is to be retrieved.

Returns:

A list of all neighbors edge data of the specified node.

Return type:

list

get_shortest_path_dijkstra_col_from_multisource(target: Expr, nx_graph: Graph, source: list, weight='weight') → Expr[source]#

Get the shortest path between source and target nodes using Dijkstra’s algorithm. Targets are stored in a polars columns and return it as a column.

Parameters:

  • nx_graph (nx.Graph) – The graph to search.

  • source (list) – Starting node for the path.

  • target (pl.Expr) – Ending node for the path.

  • weight (str, optional) – The edge attribute to use as weight. Default is ‘weight’.

Returns:

The Polars expression containing lists of shortest path nodes.

Return type:

pl.Expr

get_shortest_path_dijkstra_from_multisource(nx_graph: Graph, source: list, target, weight: str = 'weight')[source]#

Get the shortest path between source and target nodes using Dijkstra’s algorithm.

Parameters:

  • nx_graph (nx.Graph) – The graph to search.

  • source (list) – Starting node for the path.

  • target – Ending node for the path.

  • weight (str, optional) – The edge attribute to use as weight. Default is ‘weight’.

Returns: list: A list of nodes in the shortest path.

get_shortest_path_edge_data(nx_graph: Graph, source, target, data_name: str, weight: str = 'weight')[source]#

Get the edge data along the shortest path between source and target nodes in a graph.

Parameters:

  • nx_graph (nx.Graph) – The graph to search.

  • source (node) – Starting node for the path.

  • target (node) – Ending node for the path.

  • data_name (str) – The name of the edge attribute to retrieve.

  • weight (str, optional) – The edge attribute to use as weight. Default is ‘weight’.

Returns:

A list of edge data along the shortest path.

Return type:

list