### Navigation

- index
- modules |
- modules |
- previous |
- FNSS 0.6.0 documentation »
- API Reference »

# Classes

## Topology

class `Topology`(data=None, name='', **kwargs)

  Base class for undirected topology

  Methods

  `add_cycle`(nodes, **attr) | Add a cycle.
  `add_edge`(u, v[, attr_dict]) | Add an edge between u and v.
  `add_edges_from`(ebunch[, attr_dict]) | Add all the edges in ebunch.
  `add_node`(n[, attr_dict]) | Add a single node n and update node attributes.
  `add_nodes_from`(nodes, **attr) | Add multiple nodes.
  `add_path`(nodes, **attr) | Add a path.
  `add_star`(nodes, **attr) | Add a star.
  `add_weighted_edges_from`(ebunch[, weight]) | Add all the edges in ebunch as weighted edges with specified weights.
  `adjacency_iter`() | Return an iterator of (node, adjacency dict) tuples for all nodes.
  `adjacency_list`() | Return an adjacency list representation of the graph.
  `applications`() | Return a dictionary of all applications deployed, keyed by node
  `buffers`() | Return a dictionary of all buffer sizes, keyed by interface
  `capacities`() | Return a dictionary of all link capacities, keyed by link
  `clear`() | Remove all nodes and edges from the graph.
  `copy`() | Return a copy of the topology.
  `degree`([nbunch, weight]) | Return the degree of a node or nodes.
  `degree_iter`([nbunch, weight]) | Return an iterator for (node, degree).
  `delays`() | Return a dictionary of all link delays, keyed by link
  `edges`([nbunch, data]) | Return a list of edges.
  `edges_iter`([nbunch, data]) | Return an iterator over the edges.
  `get_edge_data`(u, v[, default]) | Return the attribute dictionary associated with edge (u,v).
  `has_edge`(u, v) | Return True if the edge (u,v) is in the graph.
  `has_node`(n) | Return True if the graph contains the node n.
  `is_directed`() | Return True if graph is directed, False otherwise.
  `is_multigraph`() | Return True if graph is a multigraph, False otherwise.
  `nbunch_iter`([nbunch]) | Return an iterator of nodes contained in nbunch that are also in the graph.
  `neighbors`(n) | Return a list of the nodes connected to the node n.
  `neighbors_iter`(n) | Return an iterator over all neighbors of node n.
  `nodes`([data]) | Return a list of the nodes in the graph.
  `nodes_iter`([data]) | Return an iterator over the nodes.
  `nodes_with_selfloops`() | Return a list of nodes with self loops.
  `number_of_edges`([u, v]) | Return the number of edges between two nodes.
  `number_of_nodes`() | Return the number of nodes in the graph.
  `number_of_selfloops`() | Return the number of selfloop edges.
  `order`() | Return the number of nodes in the graph.
  `remove_edge`(u, v) | Remove the edge between u and v.
  `remove_edges_from`(ebunch) | Remove all edges specified in ebunch.
  `remove_node`(n) | Remove node n.
  `remove_nodes_from`(nodes) | Remove multiple nodes.
  `selfloop_edges`([data]) | Return a list of selfloop edges.
  `size`([weight]) | Return the number of edges.
  `stacks`() | Return a dictionary of all node stacks, keyed by node
  `subgraph`(nbunch) | Return the subgraph induced on nodes in nbunch.
  `to_directed`() | Return a directed representation of the topology.
  `to_undirected`() | Return an undirected copy of the topology.
  `weights`() | Return a dictionary of all link weights, keyed by link

## DirectedTopology

class `DirectedTopology`(data=None, name='', **kwargs)

  Base class for directed topology

  Methods

  `add_cycle`(nodes, **attr) | Add a cycle.
  `add_edge`(u, v[, attr_dict]) | Add an edge between u and v.
  `add_edges_from`(ebunch[, attr_dict]) | Add all the edges in ebunch.
  `add_node`(n[, attr_dict]) | Add a single node n and update node attributes.
  `add_nodes_from`(nodes, **attr) | Add multiple nodes.
  `add_path`(nodes, **attr) | Add a path.
  `add_star`(nodes, **attr) | Add a star.
  `add_weighted_edges_from`(ebunch[, weight]) | Add all the edges in ebunch as weighted edges with specified weights.
  `adjacency_iter`() | Return an iterator of (node, adjacency dict) tuples for all nodes.
  `adjacency_list`() | Return an adjacency list representation of the graph.
  `applications`() | Return a dictionary of all applications deployed, keyed by node
  `buffers`() | Return a dictionary of all buffer sizes, keyed by interface
  `capacities`() | Return a dictionary of all link capacities, keyed by link
  `clear`() | Remove all nodes and edges from the graph.
  `copy`() | Return a copy of the topology.
  `degree`([nbunch, weight]) | Return the degree of a node or nodes.
  `degree_iter`([nbunch, weight]) | Return an iterator for (node, degree).
  `delays`() | Return a dictionary of all link delays, keyed by link
  `edges`([nbunch, data]) | Return a list of edges.
  `edges_iter`([nbunch, data]) | Return an iterator over the edges.
  `get_edge_data`(u, v[, default]) | Return the attribute dictionary associated with edge (u,v).
  `has_edge`(u, v) | Return True if the edge (u,v) is in the graph.
  `has_node`(n) | Return True if the graph contains the node n.
  `has_predecessor`(u, v) | Return True if node u has predecessor v.
  `has_successor`(u, v) | Return True if node u has successor v.
  `in_degree`([nbunch, weight]) | Return the in-degree of a node or nodes.
  `in_degree_iter`([nbunch, weight]) | Return an iterator for (node, in-degree).
  `in_edges`([nbunch, data]) | Return a list of the incoming edges.
  `in_edges_iter`([nbunch, data]) | Return an iterator over the incoming edges.
  `is_directed`() | Return True if graph is directed, False otherwise.
  `is_multigraph`() | Return True if graph is a multigraph, False otherwise.
  `nbunch_iter`([nbunch]) | Return an iterator of nodes contained in nbunch that are also in the graph.
  `neighbors`(n) | Return a list of successor nodes of n.
  `neighbors_iter`(n) | Return an iterator over successor nodes of n.
  `nodes`([data]) | Return a list of the nodes in the graph.
  `nodes_iter`([data]) | Return an iterator over the nodes.
  `nodes_with_selfloops`() | Return a list of nodes with self loops.
  `number_of_edges`([u, v]) | Return the number of edges between two nodes.
  `number_of_nodes`() | Return the number of nodes in the graph.
  `number_of_selfloops`() | Return the number of selfloop edges.
  `order`() | Return the number of nodes in the graph.
  `out_degree`([nbunch, weight]) | Return the out-degree of a node or nodes.
  `out_degree_iter`([nbunch, weight]) | Return an iterator for (node, out-degree).
  `out_edges`([nbunch, data]) | Return a list of edges.
  `out_edges_iter`([nbunch, data]) | Return an iterator over the edges.
  `predecessors`(n) | Return a list of predecessor nodes of n.
  `predecessors_iter`(n) | Return an iterator over predecessor nodes of n.
  `remove_edge`(u, v) | Remove the edge between u and v.
  `remove_edges_from`(ebunch) | Remove all edges specified in ebunch.
  `remove_node`(n) | Remove node n.
  `remove_nodes_from`(nbunch) | Remove multiple nodes.
  `reverse`([copy]) | Return the reverse of the graph.
  `selfloop_edges`([data]) | Return a list of selfloop edges.
  `size`([weight]) | Return the number of edges.
  `stacks`() | Return a dictionary of all node stacks, keyed by node
  `subgraph`(nbunch) | Return the subgraph induced on nodes in nbunch.
  `successors`(n) | Return a list of successor nodes of n.
  `successors_iter`(n) | Return an iterator over successor nodes of n.
  `to_directed`() | Return a directed representation of the topology.
  `to_undirected`() | Return an undirected copy of the topology.
  `weights`() | Return a dictionary of all link weights, keyed by link

## DatacenterTopology

class `DatacenterTopology`(data=None, name='', **kwargs)

  Represent a datacenter topology

  Methods

  `add_cycle`(nodes, **attr) | Add a cycle.
  `add_edge`(u, v[, attr_dict]) | Add an edge between u and v.
  `add_edges_from`(ebunch[, attr_dict]) | Add all the edges in ebunch.
  `add_node`(n[, attr_dict]) | Add a single node n and update node attributes.
  `add_nodes_from`(nodes, **attr) | Add multiple nodes.
  `add_path`(nodes, **attr) | Add a path.
  `add_star`(nodes, **attr) | Add a star.
  `add_weighted_edges_from`(ebunch[, weight]) | Add all the edges in ebunch as weighted edges with specified weights.
  `adjacency_iter`() | Return an iterator of (node, adjacency dict) tuples for all nodes.
  `adjacency_list`() | Return an adjacency list representation of the graph.
  `applications`() | Return a dictionary of all applications deployed, keyed by node
  `buffers`() | Return a dictionary of all buffer sizes, keyed by interface
  `capacities`() | Return a dictionary of all link capacities, keyed by link
  `clear`() | Remove all nodes and edges from the graph.
  `copy`() | Return a copy of the topology.
  `degree`([nbunch, weight]) | Return the degree of a node or nodes.
  `degree_iter`([nbunch, weight]) | Return an iterator for (node, degree).
  `delays`() | Return a dictionary of all link delays, keyed by link
  `edges`([nbunch, data]) | Return a list of edges.
  `edges_iter`([nbunch, data]) | Return an iterator over the edges.
  `get_edge_data`(u, v[, default]) | Return the attribute dictionary associated with edge (u,v).
  `has_edge`(u, v) | Return True if the edge (u,v) is in the graph.
  `has_node`(n) | Return True if the graph contains the node n.
  `hosts`() | Return the list of host nodes in the topology
  `is_directed`() | Return True if graph is directed, False otherwise.
  `is_multigraph`() | Return True if graph is a multigraph, False otherwise.
  `nbunch_iter`([nbunch]) | Return an iterator of nodes contained in nbunch that are also in the graph.
  `neighbors`(n) | Return a list of the nodes connected to the node n.
  `neighbors_iter`(n) | Return an iterator over all neighbors of node n.
  `nodes`([data]) | Return a list of the nodes in the graph.
  `nodes_iter`([data]) | Return an iterator over the nodes.
  `nodes_with_selfloops`() | Return a list of nodes with self loops.
  `number_of_edges`([u, v]) | Return the number of edges between two nodes.
  `number_of_hosts`() | Return the number of hosts in the topology
  `number_of_nodes`() | Return the number of nodes in the graph.
  `number_of_selfloops`() | Return the number of selfloop edges.
  `number_of_switches`() | Return the number of switches in the topology
  `order`() | Return the number of nodes in the graph.
  `remove_edge`(u, v) | Remove the edge between u and v.
  `remove_edges_from`(ebunch) | Remove all edges specified in ebunch.
  `remove_node`(n) | Remove node n.
  `remove_nodes_from`(nodes) | Remove multiple nodes.
  `selfloop_edges`([data]) | Return a list of selfloop edges.
  `size`([weight]) | Return the number of edges.
  `stacks`() | Return a dictionary of all node stacks, keyed by node
  `subgraph`(nbunch) | Return the subgraph induced on nodes in nbunch.
  `switches`() | Return the list of switch nodes in the topology
  `to_directed`() | Return a directed representation of the topology.
  `to_undirected`() | Return an undirected copy of the topology.
  `weights`() | Return a dictionary of all link weights, keyed by link

## TrafficMatrix

class `TrafficMatrix`(volume_unit='Mbps', flows=None)

  Class representing a single traffic matrix.

  It simply contains a set of traffic volumes being exchanged between origin-destination pairs

  Parameters: | volume_unit : str The unit in which traffic volumes are expressed flows : dict, optional The traffic volumes or the matrix, keyed by origin-destination pair. The origin-destination pair is a tuple whose two elements are respectively the identifier of the origin and destination nodes and volumes are all expressed in the same unit

  Methods

  `add_flow`(origin, destination, volume) | Add a flow to the traffic matrix
  `flows`() | Return the flows of the traffic matrix
  `od_pairs`() | Return all OD pairs of the traffic matrix
  `pop_flow`(origin, destination) | Pop a flow from the traffic matrix and return the volume of the flow removed.

## TrafficMatrixSequence

class `TrafficMatrixSequence`(interval=None, t_unit='min')

  Class representing a sequence of traffic matrices.

  Parameters: | interval : float or int, optional The time interval elapsed between subsequent traffic matrices of the sequence t_unit : str, optional The unit of the interval value (e.g. ‘sec’ or ‘min’)

  Methods

  `append`(tm) | Append a traffic matrix at the end of the sequence
  `get`(i) | Return a specific traffic matrix in a specific position of the sequence
  `insert`(i, tm) | Insert a traffic matrix in the sequence at a specified position
  `pop`(i) | Removes the traffic matrix in a specific position of the sequence

## EventSchedule

class `EventSchedule`(t_start=0, t_unit='ms')

  Class representing an event schedule. This class is simply a wrapper for a list of events.

  Methods

  `add`(time, event[, absolute_time]) | Adds an event to the schedule.
  `add_schedule`(event_schedule) | Merge with another event schedule.
  `events_between`(t_start, t_end) | Return an event schedule comprising all events scheduled between a start time (included) and an end time (excluded).
  `number_of_events`() | Return the number of events in the schedule
  `pop`(i) | Remove from the schedule the event in a specific position

### Navigation

- index
- modules |
- modules |
- previous |
- FNSS 0.6.0 documentation »
- API Reference »