Use this graph operation to transform, inspect, classify, or aggregate a graph whose directedness, edge semantics, weights, node identifiers, and duplicate-edge policy are defined.

Candidates

Required object input.

Return parameter p

Required number input.

In-out parameter q

Required number input.

Calculate second-order node2vec transition probabilities from return, neighborhood, and outward candidates. The tool evaluates the supplied inputs together and returns the named outputs below; it does not infer omitted operating conditions or change the units shown.^[1]

Transition probabilities

The resulting transition probabilities returned as an object.

• Graph results depend on representation and conventions for self-loops, parallel edges, direction, isolated nodes, weights, normalization, and traversal order. Learned embeddings additionally depend on sampling and training parameters.
• Use finite inputs in the displayed units and preserve more precision than the final presentation requires. Independently verify safety-critical, financial, compliance, or production decisions.

Validate node and edge counts before and after transformation, test small known graphs, and preserve an explicit graph schema with algorithm parameters.

• Node2Vec++ Transition Demonstrator

  Demonstrate weighted node2vec-style transitions with a threshold for strong previous-node connections.

• Graph Adjacency List to Matrix Converter

  Convert an adjacency map into a square 0/1 matrix with sorted node order.

• Graph Breadth-First Traversal

  Visit every node reachable from a start node in breadth-first order over directed edges, visiting neighbors in ascending order and reporting each node's depth.