SparkseePython  6.0.2
Public Member Functions | List of all members
sparksee.Connectivity Class Reference

Connectivity class. More...

Inheritance diagram for sparksee.Connectivity:
Inheritance graph

Public Member Functions

def run (self)
 Runs the algorithm in order to find the connected components. More...
 
def exclude_nodes (self, nodes)
 Set which nodes can't be used. More...
 
def get_connected_components (self)
 Returns the results generated by the execution of the algorithm. More...
 
def exclude_edges (self, edges)
 Set which edges can't be used. More...
 
def add_node_type (self, t)
 Allows connectivity through nodes of the given type. 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 connected components found while executing this algorithm. More...
 
def close (self)
 Closes the Connectivity instance. More...
 
def add_all_node_types (self)
 Allows connectivity through all node types of the graph.
 
def is_closed (self)
 Gets if Connectivity has been closed or not. More...
 

Detailed Description

Connectivity 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.

Author
Sparsity Technologies http://www.sparsity-technologies.com

Member Function Documentation

def sparksee.Connectivity.add_node_type (   self,
  t 
)

Allows connectivity through nodes of the given type.

Parameters
tnull
def sparksee.Connectivity.close (   self)

Closes the Connectivity instance.

It must be called to ensure the integrity of all data.

def sparksee.Connectivity.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.Connectivity.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.Connectivity.get_connected_components (   self)

Returns the results generated by the execution of the algorithm.

These results contain information related to the connected components 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 ConnectedComponents which contain information related to the connected components found.
def sparksee.Connectivity.is_closed (   self)

Gets if Connectivity has been closed or not.

See also
close()
Returns
TRUE if the Connectivity instance has been closed, FALSE otherwise.
def sparksee.Connectivity.run (   self)

Runs the algorithm in order to find the connected components.

This method can be called only once.

def sparksee.Connectivity.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 connected components 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 ConnectedComponents 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 connected components 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.