def pi_grow(tree, max_depth):
"""
Grows a tree until a single branch reaches a specified depth. Does this
by only using recursive production choices until a single branch of the
tree has reached the specified maximum depth. After that any choices are
allowed.
:param tree: An instance of the representation.tree.Tree class.
:param max_depth: The maximum depth to which to derive a tree.
:return: The fully derived tree.
"""
# Initialise derivation queue.
queue = [[tree, ret_true(params['BNF_GRAMMAR'].non_terminals[
tree.root]['recursive'])]]
# Initialise empty genome. With PI operators we can't use a depth-first
# traversal of the tree to build the genome, we need to build it as we
# encounter each node.
genome = []
while queue:
# Loop until no items remain in the queue.
# Pick a random item from the queue.
chosen = randint(0, len(queue) - 1)
# Pop the next item from the queue.
all_node = queue.pop(chosen)
node, recursive = all_node[0], all_node[0]
# Get depth of current node.
if node.parent is not None:
node.depth = node.parent.depth + 1
# Get maximum depth of overall tree.
_, overall_depth = get_nodes_and_depth(tree)
# Find the productions possible from the current root.
productions = params['BNF_GRAMMAR'].rules[node.root]
# Set remaining depth.
remaining_depth = max_depth - node.depth
if (overall_depth < max_depth) or \
(recursive and (not any([item[1] for item in queue]))):
# We want to prevent the tree from creating terminals until a
# single branch has reached the full depth. Only select recursive
# choices.
# Find which productions can be used based on the derivation method.
available = legal_productions("full", remaining_depth, node.root,
productions['choices'])
else:
# Any production choices can be made.
# Find which productions can be used based on the derivation method.
available = legal_productions("random", remaining_depth, node.root,
productions['choices'])
# Randomly pick a production choice.
chosen_prod = choice(available)
# Find the index of the chosen production and set a matching codon
# based on that index.
prod_index = productions['choices'].index(chosen_prod)
codon = randrange(productions['no_choices'],
params['BNF_GRAMMAR'].codon_size,
productions['no_choices']) + prod_index
# Set the codon for the current node and append codon to the genome.
node.codon = codon
# Insert codon into the genome.
genome.append(codon)
# Initialise empty list of children for current node.
node.children = []
for i, symbol in enumerate(chosen_prod['choice']):
# Iterate over all symbols in the chosen production.
# Create new child.
child = Tree(symbol["symbol"], node)
# Append new node to children.
node.children.append(child)
if symbol["type"] == "NT":
# The symbol is a non-terminal.
# Check whether child is recursive
recur_child = ret_true(params['BNF_GRAMMAR'].non_terminals
[child.root]['recursive'])
# Insert new child into the correct position in the queue.
queue.insert(chosen + i, [child, recur_child])
# genome, output, invalid, depth, and nodes can all be generated by
# recursing through the tree once.
_, output, invalid, depth, \
nodes = tree.get_tree_info(params['BNF_GRAMMAR'].non_terminals.keys(),
[], [])
return genome, output, nodes, depth
def pi_random_derivation(tree, max_depth):
"""
Randomly builds a tree from a given root node up to a maximum given
depth. Uses position independent methods to derive non-terminal nodes.
Final tree is not guaranteed to reach the specified max_depth limit.
:param tree: An instance of the representation.tree.Tree class.
:param max_depth: The maximum depth to which to derive a tree.
:return: The fully derived tree.
"""
# Initialise derivation queue.
queue = [[
tree,
ret_true(params['BNF_GRAMMAR'].non_terminals[tree.root]['recursive'])
]]
# Initialise empty genome. With PI operators we can't use a depth-first
# traversal of the tree to build the genome, we need to build it as we
# encounter each node.
genome = []
while queue:
# Loop until no items remain in the queue.
# Pick a random item from the queue.
chosen = randint(0, len(queue) - 1)
# Pop the next item from the queue.
all_node = queue.pop(chosen)
node = all_node[0]
# Get depth current node.
if node.parent is not None:
node.depth = node.parent.depth + 1
# Find the productions possible from the current root.
productions = params['BNF_GRAMMAR'].rules[node.root]
# Set remaining depth.
remaining_depth = max_depth - node.depth
# Find which productions can be used based on the derivation method.
available = legal_productions("random", remaining_depth, node.root,
productions['choices'])
# Randomly pick a production choice.
chosen_prod = choice(available)
# Find the index of the chosen production and set a matching codon
# based on that index.
prod_index = productions['choices'].index(chosen_prod)
codon = randrange(productions['no_choices'],
params['BNF_GRAMMAR'].codon_size,
productions['no_choices']) + prod_index
# Set the codon for the current node and append codon to the genome.
node.codon = codon
# Insert codon into the genome.
genome.append(codon)
# Initialise empty list of children for current node.
node.children = []
for i, symbol in enumerate(chosen_prod['choice']):
# Iterate over all symbols in the chosen production.
# Create new child.
child = Tree(symbol["symbol"], node)
# Append new node to children.
node.children.append(child)
if symbol["type"] == "NT":
# The symbol is a non-terminal.
# Check whether child is recursive
recur_child = ret_true(params['BNF_GRAMMAR'].non_terminals[
child.root]['recursive'])
# Insert new child into the correct position in the queue.
queue.insert(chosen + i, [child, recur_child])
# genome, output, invalid, depth, and nodes can all be Generated by
# recursing through the tree once.
_, output, invalid, depth, \
nodes = tree.get_tree_info(params['BNF_GRAMMAR'].non_terminals.keys(),
[], [])
return genome, output, nodes, depth