phylox.generators.trees.add_edges

Classes

AddEdgeMethod(value[, names, module, ...])

phylox.generators.trees.add_edges.random_vplu_move_at_bottom(network, seed=None)

Returns a VPLU move that adds an edge between the incoming edges of two leaves.

Parameters:

  • network – the network to add an edge to.

  • seed – the seed to use for the random number generator, may be an integer or a numpy.random.RandomState.

Returns:

a VPLU move that adds an edge between the incoming edges of two leaves.

Example:

>>> from phylox import DiNetwork
>>> from phylox.rearrangement.movetype import MoveType
>>> from phylox.generators.trees.well_known import generate_balanced_tree
>>> from phylox.generators.trees.add_edges import random_vplu_move_at_bottom
>>> tree = generate_balanced_tree(8)
>>> move = random_vplu_move_at_bottom(tree)
>>> move.is_type(MoveType.VPLU)
True
phylox.generators.trees.add_edges.random_vplu_move_uniform(network, seed=None)

Returns a VPLU move that adds an edge between two edges in the network. Two edges are chosen uniformly at random from the network.

Parameters:

  • network – the network to add an edge to.

  • seed – the seed to use for the random number generator, may be an integer or a numpy.random.RandomState.

Returns:

a VPLU move that adds an edge between two edges in the network.

Example:

>>> from phylox import DiNetwork
>>> from phylox.rearrangement.movetype import MoveType
>>> from phylox.generators.trees.well_known import generate_balanced_tree
>>> from phylox.generators.trees.add_edges import random_vplu_move_uniform
>>> tree = generate_balanced_tree(8)
>>> move = random_vplu_move_uniform(tree)
>>> move.is_type(MoveType.VPLU)
True
phylox.generators.trees.add_edges.random_vplu_move_local(network, stop_prob=0.2, max_steps=None, max_tries=None, seed=None)

Returns a VPLU move that adds an edge between two edges in the network. Pick one edge, move a random number of edges through the network to find a second edge.

Parameters:

  • network – the network to add an edge to.

  • stop_prob – the probability to stop the random walk.

  • max_steps – the maximum number of steps to take in the random walk.

  • max_tries – the maximum number of tries to find a second edge.

Returns:

a VPLU move that adds an edge between two edges in the network.

Example:

>>> from phylox import DiNetwork
>>> from phylox.rearrangement.movetype import MoveType
>>> from phylox.generators.trees.well_known import generate_balanced_tree
>>> from phylox.generators.trees.add_edges import random_vplu_move_local
>>> tree = generate_balanced_tree(8)
>>> move = random_vplu_move_local(tree)
>>> move.is_type(MoveType.VPLU)
True
class phylox.generators.trees.add_edges.AddEdgeMethod(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

phylox.generators.trees.add_edges.network_from_tree(tree, reticulations, method, seed=None)

Returns a network with the given number of reticulations added to the given tree.

Parameters:

  • tree – a phylogenetic network, i.e., a DAG with leaf labels stored as the node attribute LABEL_ATTR.

  • reticulations – the number of reticulations to add to the tree.

  • method – the method to use to add the reticulations.

Returns:

a network with the given number of reticulations added to the given tree.

Example:

>>> from phylox import DiNetwork
>>> from phylox.rearrangement.movetype import MoveType
>>> from phylox.generators.trees.well_known import generate_balanced_tree
>>> from phylox.generators.trees.add_edges import network_from_tree, AddEdgeMethod
>>> tree = generate_balanced_tree(8)
>>> network = network_from_tree(tree, 2, AddEdgeMethod.BOTTOM)
>>> len(network.leaves)
8
>>> network.reticulation_number
2