class GraphSim[TLabel] extends GraphMatcher[TLabel]
The GraphSim class provides a second implementation for Simple Graph
Simulation. It differ from GraphSim in the parent directory in the looping
order in the main for-loop and early termination when 'phi(u)' is empty.
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val
CHECK: Int
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val
LIMIT: Double
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SELF_LOOPS: Boolean
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def
bijections(): Set[Array[Int]]
Apply a graph pattern matching algorithm to find subgraphs of data graph 'g' that isomorphically match query graph 'q'.
Apply a graph pattern matching algorithm to find subgraphs of data graph 'g' that isomorphically match query graph 'q'. These are represented by a set of single-valued bijections {'psi'} where each 'psi' function maps each query graph vertex 'u' to a data graph vertices 'v'.
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def
countMappings(phi: Array[Set[Int]]): Pair
Count the number of mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}, giving the number of distinct vertices and edges.
Count the number of mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}, giving the number of distinct vertices and edges.
- phi
the set-valued mapping function
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- GraphMatcher
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final
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eq(arg0: AnyRef): Boolean
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equals(arg0: Any): Boolean
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def
feasibleMates(): Array[Set[Int]]
Create an initial array of feasible mappings 'phi' from each query vertex 'u' to the corresponding set of data graph vertices '{v}' whose label matches 'u's.
Create an initial array of feasible mappings 'phi' from each query vertex 'u' to the corresponding set of data graph vertices '{v}' whose label matches 'u's.
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- GraphMatcher
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def
feasibleMatesW(): Array[Set[Int]]
Create an initial array of feasible mappings 'phi' from each query vertex 'u' to the corresponding set of data graph vertices '{v}' whose label matches 'u's.
Create an initial array of feasible mappings 'phi' from each query vertex 'u' to the corresponding set of data graph vertices '{v}' whose label matches 'u's. This version handles query graph labels that have wildcards.
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finalize(): Unit
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val
gRange: Range
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hashCode(): Int
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isInstanceOf[T0]: Boolean
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def
mappings(): Array[Set[Int]]
Apply a graph pattern matching algorithm to find the mappings from the query graph 'q' to the data graph 'g'.
Apply a graph pattern matching algorithm to find the mappings from the query graph 'q' to the data graph 'g'. These are represented by a multi-valued function 'phi' that maps each query graph vertex 'u' to a set of data graph vertices '{v}'.
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ne(arg0: AnyRef): Boolean
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notify(): Unit
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final
def
notifyAll(): Unit
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def
overlaps(set1: Set[Int], set2: Set[Int]): Boolean
Determine whether two sets overlap, i.e., have a non-empty intersection.
Determine whether two sets overlap, i.e., have a non-empty intersection.
- set1
the first set
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the second set
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- GraphMatcher
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def
prune(phi: Array[Set[Int]]): Array[Set[Int]]
Given the mappings 'phi' produced by the 'feasibleMates' method, prune mappings 'u -> v' where v's children fail to match u's.
Given the mappings 'phi' produced by the 'feasibleMates' method, prune mappings 'u -> v' where v's children fail to match u's.
- phi
array of mappings from a query vertex u to { graph vertices v }
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val
qRange: Range
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def
showMappings(phi: Array[Set[Int]]): Unit
Show all mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}.
Show all mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}.
- phi
the set-valued mapping function
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- GraphMatcher
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
test(name: String, ans: Array[Set[Int]] = null): Unit
Test the Graph Pattern Matcher.
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def
toString(): String
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def
wait(): Unit
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def
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