The OPTGRAPH Procedure
- Overview
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Getting Started
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SyntaxFunctional SummaryPROC OPTGRAPH StatementBICONCOMP StatementCENTRALITY StatementCLIQUE StatementCOMMUNITY StatementCONCOMP StatementCORE StatementCYCLE StatementDATA_LINKS_VAR StatementDATA_MATRIX_VAR StatementDATA_NODES_VAR StatementEIGENVECTOR StatementLINEAR_ASSIGNMENT StatementMINCOSTFLOW StatementMINCUT StatementMINSPANTREE StatementPERFORMANCE StatementREACH StatementSHORTPATH StatementSUMMARY StatementTRANSITIVE_CLOSURE StatementTSP Statement
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DetailsGraph Input DataMatrix Input DataData Input OrderParallel ProcessingNumeric LimitationsSize LimitationsCommon Notation and AssumptionsBiconnected Components and Articulation PointsCentralityCliqueCommunityConnected ComponentsCore DecompositionCycleEigenvector ProblemLinear Assignment (Matching)Minimum-Cost Network FlowMinimum CutMinimum Spanning TreeReach (Ego) NetworkShortest PathSummaryTransitive ClosureTraveling Salesman ProblemMacro VariablesODS Table Names
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ExamplesArticulation Points in a Terrorist NetworkInfluence Centrality for Project Groups in a Research DepartmentBetweenness and Closeness Centrality for Computer Network TopologyBetweenness and Closeness Centrality for Project Groups in a Research DepartmentEigenvector Centrality for Word Sense DisambiguationCentrality Metrics for Project Groups in a Research DepartmentCommunity Detection on Zachary’s Karate Club DataRecursive Community Detection on Zachary’s Karate Club DataCycle Detection for Kidney Donor ExchangeLinear Assignment Problem for Minimizing Swim TimesLinear Assignment Problem, Sparse Format versus Dense FormatMinimum Spanning Tree for Computer Network TopologyTransitive Closure for Identification of Circular Dependencies in a Bug Tracking SystemReach Networks for Computation of Market Coverage of a Terrorist NetworkTraveling Salesman Tour through US Capital Cities
- References
Data Input Order
Numerous algorithms are sensitive to the order in which PROC OPTGRAPH reads the data. If the order of the nodes or links is changed, either by you or by some parameter setting, the final result might change. In some cases, this difference is simply a permutation of identifiers (for example, connected components). In other cases, when using local optimization (for example, community detection) or discrete branching decisions (for example, traveling salesman problem), the final result might be a local (or alternative) solution. Two parameters that could have such an effect are STANDARDIZED_LABELS and NTHREADS=. Both of these options can change the internal order of the nodes and links.