Symbol Graph Algorithm
The Symbol Graph Algorithm is a powerful data structure used for solving problems that involve processing large datasets of interconnected items, such as social networks or biological pathways. It works by representing the relationships between various entities (symbols) in a graph, which is a mathematical structure composed of nodes (vertices) and edges (connections). In the context of the Symbol Graph Algorithm, nodes represent the unique symbols or entities, while edges denote the relationships between these symbols. This algorithm enables efficient querying and analysis of complex relationships, supporting various graph traversal and search techniques, which can uncover hidden patterns and connections in the data.
One of the main advantages of the Symbol Graph Algorithm is its ability to handle and analyze sparse data, where the number of connections between entities is relatively low compared to the total number of entities. This is particularly useful when working with large-scale datasets, such as social networks or gene interaction networks, where it can be computationally expensive to analyze relationships using other data structures, like adjacency matrices. By leveraging the inherent graph structure and efficient algorithms for graph traversal, the Symbol Graph Algorithm can quickly identify specific connections, find shortest paths between entities, or discover communities within the dataset. This makes it a valuable tool for a wide range of applications, from social network analysis and recommendation systems to computational biology and natural language processing.
package org.gs.graph
import scala.collection.immutable.TreeMap
/** Graph where vertex names are strings
*
* @constructor creates a new SymbolGraph with a symbol table, keys and a graph
* @tparam A generic graph type, must extend BaseGraph
* @param st ordered key value map
* @param keys from st without nulls
* @param g graph constructed from st
* @see [[https://algs4.cs.princeton.edu/41undirected/SymbolGraph.java.html]]
* @author Scala translation by Gary Struthers from Java by Robert Sedgewick and Kevin Wayne.
*/
class SymbolGraph[A <: BaseGraph](st: TreeMap[String, Int], val keys: Array[String], val g: A) {
/** Does graph contain s */
def contains(s: String): Boolean = st.contains(s)
/**
* @param s vertex name
* @return associated index of vertex
*/
def index(s: String): Option[Int] = st.get(s)
/**
* @param v associated index of vertex
* @return associated name of vertex
*/
def name(v: Int): String = keys(v)
}
