def to_tree_obj(self, spanning_tree, k, resp):
"""Computes a Tree object from the spanning tree. Categorical distributions are
computed from the samples and responsibilities
Parameters:
spanning_tree -- List of tuples (v_i, v_j weight)
k -- Index of tree we're updating
resp -- Responsibility matrix (num_samples, num_trees)
Returns:
Tree object with first vertex in the spanning tree as root and remaining nodes
organised as a Tree, each node with its MLE q distribution
"""
tree = Tree()
tree.root = Node(0, [])
tree.k = 2
visit_list = [tree.root]
remaining_nodes = spanning_tree
while len(visit_list) != 0:# and len(remaining_nodes):
tree.num_nodes += 1
tree.num_leaves += 1
cur_node = visit_list[0]
# We're going to separate the remaining nodes in those that are connected
# to the current and those that aren't
connected = [edge for edge in remaining_nodes
if edge[0] == int(cur_node.name) or edge[1] == int(cur_node.name)]
not_connected = [edge for edge in remaining_nodes
if edge[0] != int(cur_node.name) and edge[1] != int(cur_node.name)]
# We create a Node for the connected nodes and add them as children to current node
for edge in connected:
other = edge[0] if edge[0] != int(cur_node.name) else edge[1]
child = Node(other, [])
child.ancestor = cur_node
cur_node.descendants.append(child)
visit_list = visit_list[1:] + cur_node.descendants
remaining_nodes = not_connected # Keep only nodes that aren't connected yet
# Now we built a tree. We traverse it again to set the correct node names and
# categorical distributions
visit_list = [tree.root]
cont = 0
while len(visit_list) != 0:
cur_node = visit_list[0]
# TODO: Why does it work if I dont't rename the nodes?
#cur_node.name = cont
cat = []
if cur_node.ancestor == None:
cat = [self.q_marginal(k, cur_node.name, 0, resp),
self.q_marginal(k, cur_node.name, 1, resp)]
else:
parent_idx = int(cur_node.ancestor.name)
child_idx = int(cur_node.name)
for p in [0, 1]: # For possible values of parent
q_given_parent = [0, 0]
for c in [0, 1]: # For possible values of child
q_given_parent[c] = self.q(k, parent_idx, child_idx, p, c, resp)
q_given_parent /= self.q_marginal(k, parent_idx, p, resp)
cat.append(q_given_parent)
cont += 1
cur_node.cat = cat
visit_list = visit_list[1:] + cur_node.descendants
return tree
