[英]Plotting a decision tree with pydot
我已经训练了一个tree
(Python 字典),如下所示。 现在我正在尝试使用pydot绘制它。 在定义树的每个节点(pydot 图)时,我为它指定了一个唯一(并且详细)的名称和一个简短的标签。
我的问题是,在我通过写入 .png 得到的结果图中,我看到了详细的node names
而不是node labels
。
我在这里遵循了@Martijn Pieters 的回答。 我不知道我错过了什么,有什么想法吗?
import pydot
tree= {'salary': {'41k-45k': 'junior', '46k-50k': {'department': {'marketing': 'senior', 'sales': 'senior', 'systems': 'junior'}}, '36k-40k': 'senior', '26k-30k': 'junior', '31k-35k': 'junior', '66k-70k': 'senior'}}
def walk_dictionaryv2(graph, dictionary, parent_node=None):
'''
Recursive plotting function for the decision tree stored as a dictionary
'''
for k in dictionary.keys():
if parent_node is not None:
from_name = parent_node.get_name().replace("\"", "") + '_' + str(k)
from_label = str(k)
node_from = pydot.Node(from_name, label=from_label)
graph.add_edge( pydot.Edge(parent_node, node_from) )
if isinstance(dictionary[k], dict): # if interim node
walk_dictionaryv2(graph, dictionary[k], node_from)
else: # if leaf node
to_name = str(k) + '_' + str(dictionary[k]) # unique name
to_label = str(dictionary[k])
node_to = pydot.Node(to_name, label=to_label, shape='box')
graph.add_edge(pydot.Edge(node_from, node_to))
#node_from.set_name(to_name)
else:
from_name = str(k)
from_label = str(k)
node_from = pydot.Node(from_name, label=from_label)
walk_dictionaryv2(graph, dictionary[k], node_from)
def plot_tree(tree, name):
# first you create a new graph, you do that with pydot.Dot()
graph = pydot.Dot(graph_type='graph')
walk_dictionaryv2(graph, tree)
graph.write_png(name+'.png')
plot_tree(tree,'name')
这是我用上面的代码得到的(不需要的)输出:
您需要将您创建的节点显式添加到图中:
node_from = pydot.Node(from_name, label=from_label)
graph.add_node(node_from)
和
node_to = pydot.Node(to_name, label=to_label, shape='box')
graph.add_node(node_to)
否则渲染器将看不到名称。 graph.add_node()
在生成的.dot
文件中包含节点元数据。
添加那些graph.add_node()
行后,结果是:
如果有人想要使用边缘标签的版本(显示决策树的传统方式)
import pydot
import uuid
def generate_unique_node():
""" Generate a unique node label."""
return str(uuid.uuid1())
def create_node(graph, label, shape='oval'):
node = pydot.Node(generate_unique_node(), label=label, shape=shape)
graph.add_node(node)
return node
def create_edge(graph, node_parent, node_child, label):
link = pydot.Edge(node_parent, node_child, label=label)
graph.add_edge(link)
return link
def walk_tree(graph, dictionary, prev_node=None):
""" Recursive construction of a decision tree stored as a dictionary """
for parent, child in dictionary.items():
# root
if not prev_node:
root = create_node(graph, parent)
walk_tree(graph, child, root)
continue
# node
if isinstance(child, dict):
for p, c in child.items():
n = create_node(graph, p)
create_edge(graph, prev_node, n, str(parent))
walk_tree(graph, c, n)
# leaf
else:
leaf = create_node(graph, str(child), shape='box')
create_edge(graph, prev_node, leaf, str(parent))
def plot_tree(dictionary, filename="DecisionTree.png"):
graph = pydot.Dot(graph_type='graph')
walk_tree(graph, tree)
graph.write_png(filename)
tree = {'salary': {'41k-45k': 'junior', '46k-50k': {'department': {'marketing': 'senior', 'sales': 'senior', 'systems': 'junior'}}, '36k-40k': 'senior', '26k-30k': 'junior', '31k-35k': 'junior', '66k-70k': 'senior'}}
plot_tree(tree)
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