def generate_parses(causal_tree):
node_type = causal_tree["node_type"]
if "children" not in causal_tree:
return (causal_tree,)
partial_causal_parses = []
# make a copy of the current node, minus the children (so we're keeping symbol_type, symbol, energy, node_type, etc)
current_node = causal_tree.copy()
current_node.pop("children")
if node_type in ("or","root",):
for child_node in causal_tree["children"]:
for parse in generate_parses(child_node):
current_node["children"] = (parse,)
partial_causal_parses.append(current_node.copy())
elif node_type in ("and",):
# generate causal parses on each tree
# build all cartesian products of those causal parses;
# each cartesian product is a set of children for the and node, a separate partial parse graph to return
child_parses = []
for child_node in causal_tree["children"]:
child_parses.append(generate_parses(child_node),)
for product in itertools.product(*child_parses):
current_node["children"] = product
partial_causal_parses.append(current_node.copy())
else:
raise Exception("UNKNOWN NODE TYPE: {}".format(node_type))
return partial_causal_parses
评论列表
文章目录
