DisjointCommunityDetection class. More...
Public Member Functions | |
| def | run (self) |
| Runs the algorithm in order to find the communities. More... | |
| def | exclude_nodes (self, nodes) |
| Set which nodes can't be used. More... | |
| def | add_all_edge_types (self) |
| Allows connectivity through all edge types of the graph. More... | |
| def | get_communities (self) |
| Returns the results generated by the execution of the algorithm. More... | |
| def | add_edge_type (self, type) |
| Allows connectivity through edges of the given type. More... | |
| def | add_node_type (self, type) |
| Allows connectivity through nodes of the given type. More... | |
| def | exclude_edges (self, edges) |
| Set which edges can't be used. More... | |
| def | set_materialized_attribute (self, attribute_name) |
| Creates a new common attribute type for all node types in the graph in order to store, persistently, the results related to the disjoint communities found while executing this algorithm. More... | |
| def | include_nodes (self, nodes) |
| Set additional nodes that can be used. More... | |
| def | add_all_node_types (self) |
| Allows connectivity through all node types of the graph. | |
| def | include_edges (self, edges) |
| Set additional edges that can be used. More... | |
| def | close (self) |
| Closes the CommunityDetection instance. More... | |
| def | is_closed (self) |
| Gets if CommunityDetection has been closed or not. More... | |
Detailed Description
DisjointCommunityDetection class.
Any class implementing this abstract class can be used to solve a problem related to graph connectivity as finding the strongly connected components, finding the weakly connected components.
Check out the 'Algorithms' section in the SPARKSEE User Manual for more details on this.
Member Function Documentation
| def sparksee.DisjointCommunityDetection.add_all_edge_types | ( | self | ) |
Allows connectivity through all edge types of the graph.
The edges can be used in Any direction.
| def sparksee.DisjointCommunityDetection.add_edge_type | ( | self, | |
| type | |||
| ) |
Allows connectivity through edges of the given type.
The edges can be used in Any direction.
- Parameters
-
type [in] Edge type.
| def sparksee.DisjointCommunityDetection.add_node_type | ( | self, | |
| type | |||
| ) |
Allows connectivity through nodes of the given type.
- Parameters
-
type null
|
inherited |
Closes the CommunityDetection instance.
It must be called to ensure the integrity of all data.
| def sparksee.DisjointCommunityDetection.exclude_edges | ( | self, | |
| edges | |||
| ) |
Set which edges can't be used.
This will replace any previously specified set of excluded edges. Should only be used to exclude the usage of specific edges from allowed edge types because it's less efficient than not allowing an edge type.
- Parameters
-
edges [in] A set of edge identifiers that must be kept intact until the destruction of the class.
| def sparksee.DisjointCommunityDetection.exclude_nodes | ( | self, | |
| nodes | |||
| ) |
Set which nodes can't be used.
This will replace any previously specified set of excluded nodes. Should only be used to exclude the usage of specific nodes from allowed node types because it's less efficient than not allowing a node type.
- Parameters
-
nodes [in] A set of node identifiers that must be kept intact until the destruction of the class.
| def sparksee.DisjointCommunityDetection.get_communities | ( | self | ) |
Returns the results generated by the execution of the algorithm.
These results contain information related to the disjoint communities found as the number of different components, the set of nodes contained in each component or many other data.
- Returns
- Returns an instance of the class DisjointCommunities which contain information related to the disjoint communities found.
| def sparksee.DisjointCommunityDetection.include_edges | ( | self, | |
| edges | |||
| ) |
Set additional edges that can be used.
This will replace any previously specified set of include edges. Using this optional method adds valid edges to the edges of any edge type explicitly set as a valid type. Should only be used to include specific small sets of edges because it's less efficient than just using an edge type. For any edge to be used, both nodes must be also valid.
- Parameters
-
edges [in] A set of edge identifiers that must be kept intact until the destruction of the class.
| def sparksee.DisjointCommunityDetection.include_nodes | ( | self, | |
| nodes | |||
| ) |
Set additional nodes that can be used.
This will replace any previously specified set of include nodes. Using this optional method adds valid nodes to the nodes of any node type explicitly set as a valid type. Should only be used to include specific small sets of nodes because it's less efficient than just using a node type.
- Parameters
-
nodes [in] A set of node identifiers that must be kept intact until the destruction of the class.
|
inherited |
Gets if CommunityDetection has been closed or not.
- See also
- close()
- Returns
- TRUE if the CommunityDetection instance has been closed, FALSE otherwise.
| def sparksee.DisjointCommunityDetection.run | ( | self | ) |
Runs the algorithm in order to find the communities.
This method can be called only once.
| def sparksee.DisjointCommunityDetection.set_materialized_attribute | ( | self, | |
| attribute_name | |||
| ) |
Creates a new common attribute type for all node types in the graph in order to store, persistently, the results related to the disjoint communities found while executing this algorithm.
Whenever the user wants to retrieve the results, even when the graph has been closed and opened again, it is only necessary to create a new instance of the class DisjointCommunities indicating the graph and the name of the common attribute type which stores the results. This instance will have all the information related to the disjoint communities found in the moment of the execution of the algorithm that stored this data.
It is possible to run the algorithm without specifying this parameter in order to avoid materializing the results of the execution.
- Parameters
-
attribute_name [in] The name of the common attribute type for all node types in the graph which will store persistently the results generated by the execution of the algorithm.
