copulas.multivariate.tree module

Multivariate trees module.

class copulas.multivariate.tree.CenterTree(random_state=None)

Bases: Tree

Tree for a C-vine copula.

get_anchor()

Find anchor variable with highest sum of dependence with the rest.

Returns:

Anchor variable.

Return type:

int

tree_type = 0

class copulas.multivariate.tree.DirectTree(random_state=None)

Bases: Tree

DirectTree class.

tree_type = 1

class copulas.multivariate.tree.Edge(index, left, right, copula_name, copula_theta)

Bases: object

Represents an edge in the copula.

classmethod from_dict(edge_dict)

Create a new instance from a parameters dictionary.

Parameters:

params (dict) – Parameters of the Edge, in the same format as the one returned by the to_dict method.

Returns:

Instance of the edge defined on the parameters.

Return type:

Edge

classmethod get_child_edge(index, left_parent, right_parent)

Construct a child edge from two parent edges.

Parameters:

• index (int) – Index of the new Edge.

• left_parent (Edge) – Left parent

• right_parent (Edge) – Right parent

Returns:

The new child edge.

Return type:

Edge

classmethod get_conditional_uni(left_parent, right_parent)

Identify pair univariate value from parents.

Parameters:

• left_parent (Edge) – left parent

• right_parent (Edge) – right parent

Returns:

left and right parents univariate.

Return type:

tuple[np.ndarray, np.ndarray]

get_likelihood(uni_matrix)

Compute likelihood given a U matrix.

Parameters:

uni_matrix (numpy.array) – Matrix to compute the likelihood.

Returns:

likelihood and conditional values.

Return type:

tuple (np.ndarray, np.ndarray, np.array)

is_adjacent(another_edge)

Check if two edges are adjacent.

Parameters:

another_edge (Edge) – edge object of another edge

Returns:

True if the two edges are adjacent.

Return type:

bool

static sort_edge(edges)

Sort iterable of edges first by left node indices then right.

Parameters:

edges (list[Edge]) – List of edges to be sorted.

Returns:

Sorted list by left and right node indices.

Return type:

list[Edge]

to_dict()

Return a dict with the parameters to replicate this Edge.

Returns:

Parameters of this Edge.

Return type:

dict

class copulas.multivariate.tree.RegularTree(random_state=None)

Bases: Tree

RegularTree class.

tree_type = 2

class copulas.multivariate.tree.Tree(random_state=None)

Bases: Multivariate

Helper class to instantiate a single tree in the vine model.

fit(index, n_nodes, tau_matrix, previous_tree, edges=None)

Fit this tree object.

Parameters:

• index (int) – index of the tree.

• n_nodes (int) – number of nodes in the tree.

• tau_matrix (numpy.array) – kendall’s tau matrix of the data, shape (n_nodes, n_nodes).

• previous_tree (Tree) – tree object of previous level.

fitted = False

classmethod from_dict(tree_dict, previous=None)

Create a new instance from a parameters dictionary.

Parameters:

params (dict) – Parameters of the Tree, in the same format as the one returned by the to_dict method.

Returns:

Instance of the tree defined on the parameters.

Return type:

Tree

get_adjacent_matrix()

Get adjacency matrix.

Returns:

adjacency matrix

Return type:

numpy.ndarray

get_likelihood(uni_matrix)

Compute likelihood of the tree given an U matrix.

Parameters:

uni_matrix (numpy.array) – univariate matrix to evaluate likelihood on.

Returns:

likelihood of the current tree, next level conditional univariate matrix

Return type:

tuple[float, numpy.array]

get_tau_matrix()

Get tau matrix for adjacent pairs.

Returns:

tau matrix for the current tree

Return type:

tau (numpy.ndarray)

prepare_next_tree()

Prepare conditional U matrix for next tree.

to_dict()

Return a dict with the parameters to replicate this Tree.

Returns:

Parameters of this Tree.

Return type:

dict

tree_type = None

class copulas.multivariate.tree.TreeTypes(*values)

Bases: Enum

The available types of trees.

CENTER = 0

DIRECT = 1

REGULAR = 2

copulas.multivariate.tree.get_tree(tree_type)

Get a Tree instance of the specified type.

Parameters:

tree_type (str or TreeTypes) – Type of tree of which to get an instance.

Returns:

Instance of a Tree of the specified type.

Return type:

Tree