Returns the name of the node

Initialize a node with a name, attribute mapping, and a hybrid flag.

Retrieve the attribute mapping.

Set a node's attributes to a mapping of key labels to attribute values.

Get the speciation time for this node. Closer to 0 implies a time closer to the origin (the root). A larger time implies a time closer to the present (leaves).

Set the speciation time for this node. The arg 't' must be a non-negative number.

Create a string representation of a node.

Equality comparison for Node objects. Two nodes are equal if they have the same name (identity). Note: This is based on node identity, not biological distance.

Hash function for Node objects. Uses the node name for hashing to maintain consistency with equality.

Create a description of a node and summarize its attributes.

Sets the name of the node to new_name.

Sets whether a node is a reticulation Node (or not).

Retrieves whether a node is a reticulation Node (or not)

Put a key and value pair into the node attribute dictionary. If the key is already present, it will overwrite the old value.

If key is a key in the attributes mapping, then its value will be returned. Otherwise, returns None.

Associate a data sequence with this node, if this node is a leaf in a network.

Gets the data sequence associated with this node.

Duplicate this node by copying all data into a separate Node object. Useful for crafting copies of networks without having to deep copy.

Initialize an empty set of network nodes

Check if a node is in the network node set.

Add a list of nodes to the network node set.

Check if an edge is allowed to be added to the network (both nodes must be in the node set before an edge can be added). A undirected edge is not allowed to be inserted into a directed network, and a directed edge is not allowed to be inserted into an undirected graph. False will be returned in such instances.

Gets the in degree of a node in this set. Returns 0 if the node has no in edges, or if the node is not in the node set. It is up to the user to make sure the parameter node is in the node set.

Gets the out degree of a node in this set. Returns 0 if the node has no out edges, or if the node is not in the node set. It is up to the user to make sure the parameter node is in the node set.

Gets the in edges of a node in this set. Returns an empty set if the node has no in edges, or if the node is not in the node set. It is up to the user to make sure the parameter node is in the node set. Note: Returns a reference to the internal set. Copy before iterating if you plan to modify the graph during iteration.

Gets the out edges of a node in this set. Returns an empty set if the node has no out edges, or if the node is not in the node set. It is up to the user to make sure the parameter node is in the node set. Note: Returns a reference to the internal set. Copy before iterating if you plan to modify the graph during iteration.

Keep track of network data (in/out degrees, in/out edge maps) upon the addition or removal of an edge for a network.

Grab the set of nodes.

Remove a node from V, and update necessary mappings.

Protected method that processes updates to node labels within the NodeSet. You may not set a Node's name to None.

Get a node by name.

Gets the "first" node in this edge. (No ordering, but for efficient retrieval, we designate one as the first).

Gets the "second" node in this edge. (No ordering, but for efficient retrieval, we designate one as the second).

Initialize an undirected Edge.

Check if a node is a member of this edge.

Gets the branch length of this edge. If it is not equivalent to the current times of the source and destination nodes, then a warning is raised that the branch lengths are not equivalent, and that either the times are outdated or the branch length field is outdated.

Sets the branch length of this edge.

Duplicate this edge by copying all data into a separate UEdge object.

Convert this edge to a directed edge.

Gets the weight of this edge.

Sets the weight of this edge.

Get the names of the nodes in this edge.

Get the source node of this edge.

Get the destination node of this edge.

An edge has a source (parent) and a destination (child). Edges in a phylogenetic context are *generally* directed. source -----> destination

Set the name/identifiability tag of this edge.

Get the name/identifiability tag for this edge.

Set the inheritance probability of this edge. Only applicable to hybrid edges, but no warning will be raised if you attempt to set the probability of a non-hybrid edge.

Gets the inheritance probability for this edge.

Craft an identical edge to this edge object, just in a new object. Useful in building subnetworks of a network that is in hand.

Set the branch length of this edge. If enforce_times is True, then the branch length must be equivalent to the difference in times of the source and destination nodes. If warn_times is True, then a warning will be raised if the branch length is not equivalent to the difference in times of the source and destination nodes.

Get the branch length of this edge.

Set the weight of this edge.

Get the weight of this edge.

Get the names of the nodes in this edge.

Get the length of this edge.

Convert this edge to a Branch object for use in phylogenetic computations.

Initialize the set of edges, E, for a network.

An undirected edge (Edge) is in the EdgeSet if there is an equivalent edge object OR if there is anUEdgeobject with equivalent node members. A directed edge (DiEdge) is in the EdgeSet only if the EdgeSet has a reference to @e.

Add any number of edges to E.

Remove an edge from E.

Given the nodes that make up the edge and an inheritance probability, get the edge in E that matches the data. Inheritance probability is only required for when a directed network has two edges with the same source and destination nodes, and it is known that a bubble edge is being looked up. Inheritance probabilities are insufficient for identifiability of directed bubble edges should gamma be .5, in which case please tag your edges with some sort of key. If a bubble edge is being looked up and there is no gamma and/or tag provided, then one of the two bubble edges will be returned at random. There are no identifiability problems with undirected graphs, since duplicate edges are not a thing, and there exists only one edge with a given pair of member nodes.

Get the set, E, for a network.

Initialize a Network object. You may initialize with any combination of edges/nodes, or provide none at all.

Allows a simple pythonic "n in graph" or "e in graph" check.

Add any amount of nodes to this graph (or Network).

Ensure a node has a unique name that hasn't been used before/is not currently in use for this graph. May be used with a node that is or is not yet an element of V. The node will be added to V as a result of this function.

Removes any amount of nodes from the list of nodes. Also prunes all edges from the graph that are connected to the removed node(s). Has no effect if a node is not in this network.

Removes an edge from the EdgeSet. Does not delete nodes with no edges Has no effect if 'edge' is not in the graph.

Gets the edge in the graph with the given members.

Get all nodes in V.

Get the set E (in list form).

Access the blob storage with a key. CONSIDER REMOVAL OF THIS FUNCTION...

Add an item to the blob storage.

Rename a node and update the bookkeeping.

Check whether the graph has a node with a certain name. Strings must be exactly equal (same white space, capitalization, etc.)

Get the in-degree of a node.

Get the out-degree(number of edges where the given node is a parent) of a node in the graph.

Get the in-edges of a node in V. The in-edges are the edges in E, where the given node is the child.

Get the out-edges of a node in V. The out-edges are the edges in E, where the given node is the parent.

Initialize a Network object. You may initialize with any combination of edges/nodes, or provide none at all. If you provide an EdgeSet and no nodes, each node present in the EdgeSet *WILL* be added to the network.

Construct a Network object by passing in a newick string and parsing out the topology from there.

If edges is a list of Edges, then add each Edge to the list of edges. If edges is a singleton Edge then just add to the edge array. Note: Each edge that you attempt to add must be between two nodes that exist in the network. Otherwise, an error will be thrown.

Removes node from the list of nodes. Also prunes all edges from the graph that are connected to the node. Has no effect if node is not in this network.

Removes edge from the list of edges. Does not delete nodes with no edges Has no effect if 'edge' is not in the graph.

Note, that in the event of bubbles, 2 edges will exist with the same source and destination. If this is possible, please supply the inheritance probability of the correct branch. If both edges are known to be identical (gamma = 0.5), then one will be chosen at random.

Return the root of the Network. Phylogenetic networks only have one root, but for generality and practical use, multiple roots have been allowed. To get all roots, should multiple exist, call the function "roots". This function only returns 1 root.

Return all root(s) of the Network. Phylogenetic networks typically have one root, but for generality and practical use, multiple roots have been allowed. Use ``root()`` to retrieve a single root.

Returns the set X (a subset of V), the set of all leaves (nodes with out-degree 0). Only returns the leaves that are connected/reachable from the root.

Returns a list of the parents of a node. There is no hard cap on the length of this array.

Returns a list of the children of a node. There is no hard cap on the length of this array.

Returns a dictionary of branches connected to the node.

All the various ways that the graph can be cleaned up and streamlined while not altering topology or results of algorithms. Algorithm Indeces: 0) Remove nodes that have in/out degree of 0 (floater nodes) 1) Remove a spurious root/root edge (root node with only one out edge) 2) Consolidate all chains of nodes with in/out degree of 1 into 1 edge. Default behavior is to run all three. To not run a certain routine, set the options list at the indeces listed above to False. Ie. To run the first and third algo, use [True, False, True].

Computes the Least Common Ancestor of a set of graph nodes.

Compute the set of all leaf nodes that are descendants of the parameter node. Uses DFS to find paths to leaves.

Returns 2 random edges such that there does not exist a directed path from one edge source node to the other edge source node.

Given a node in this graph, return the subgenome count.

Returns the set (as a list) of edges that are in the subgraph of a node.

Returns the set (as a list) of edges that are in all paths from the root to this node. Useful in avoiding the creation of cycles when adding edges.

Maps edges to their subgenome counts.

Maps edges to their subgenome counts.

Map each node in the graph to its set of leaf descendants

Generate the newick string of the network.

Checks if each of this graph's connected components is acyclic

General bfs-dfs routine, with the added utility of checking whether or not this graph is made up of multiple connected components.

Make a copy of a subnetwork of this DAG, rooted at 'retic_node', with unique node names.

Copy this network into a new network object, also with new node and edge objects.

Convert this network to a NetworkX graph object.

Compares the topology of this network compared to another network. The following are options for the distance measure: [tree|tri|cluster|luay|rnbs|apd|normapd|wapd|normwapd] If [tree | tri | cluster] is used, the return value will be the average of the false positive and false negative rates. If [luay] is used, the return value will be the distance between the two networks. If [rnbs | apd | normapd | wapd | normwapd] is used, the return value is the dissimilarity between the two networks.

Check if this network is topologically isomorphic to another network. Two networks are isomorphic if they have the same topology, regardless of node labels or branch lengths. This method calls the GraphUtils.is_isomorphic function.

Computes the rooted triplet distance (Nakhleh distance) between two networks. This distance measure compares the topological relationships between all triplets of leaves in both networks.

Collect all nodes in the subtree rooted at the given node.

Get the distance from the root to the given node, measured in edge count (hop count) via BFS.

Compute a topological order of nodes in an acyclic network.

Compute distance from root to a given node.

Set time attributes for all nodes based on their distance from root. Uses cumulative branch lengths from root. Useful for enabling biologically meaningful node comparisons. The root node is assigned time 0.0 and each descendant's time is the sum of branch lengths along the BFS path from the root.

Set time attributes for all nodes based on their edge count from root. This provides biologically meaningful comparison when actual times are not available. Edge counts are converted to time values for comparison purposes. The root node is assigned time 0.0 and each descendant's time equals the number of edges on the BFS path from the root.

Initializes a MUL object.

Recursively expand reticulations, handling nested reticulations correctly. Each reticulation node with multiple parents is expanded by duplicating the downstream subnetwork for each additional parent, processing the deepest reticulations first.

Creates a (MU)lti-(L)abeled Species Tree from a network