网上的版本好像好久都没更新了treePlotter是没有人用了么。今天学习的时候发现有些地方已经改了，我改的是在python 3.6 上的运行版本，需要导入matplotlib.pyplot

import matplotlib.pyplot as plt

# 定义决策树决策结果属性

descisionNode = dict(boxstyle=‘sawtooth‘, fc=‘0.8‘)

leafNode = dict(boxstyle=‘round4‘, fc=‘0.8‘)

arrow_args = dict(arrowstyle=‘

# myTree = {‘no surfacing‘: {0: ‘no‘, 1: {‘flippers‘: {0: ‘no‘, 1: ‘yes‘}}}}

def plotNode(nodeTxt, centerPt, parentPt, nodeType):

# nodeTxt为要显示的文本，centerNode为文本中心点, nodeType为箭头所在的点， parentPt为指向文本的点

createPlot.ax1.annotate(nodeTxt, xy=parentPt, xycoords=‘axes fraction‘,

xytext=centerPt, textcoords=‘axes fraction‘,

va=‘center‘, ha=‘center‘, bbox=nodeType, arrowprops=arrow_args)

# def createPlot():

# fig = plt.figure(1, facecolor=‘white‘)

# fig.clf()

# # createPlot.ax1为全局变量,绘制图像句柄

# # frameon表示是否绘制坐标轴矩形

# createPlot.ax1 = plt.subplot(111, frameon=False)

# plotNode(‘a decision node‘, (0.5, 0.1), (0.1, 0.5), descisionNode)

# plotNode(‘a leaf node‘, (0.8, 0.1), (0.3, 0.8), leafNode)

# plt.show()

# 这个是用来测试的

# -----------分割线-------------

# 获取树的叶子数和树的深度

def getNumLeafs(myTree):

numLeafs = 0

firstStr = list(myTree.keys())[0]

secondDict = myTree[firstStr]

for key in secondDict.keys():

if type(secondDict[key]).__name__ == ‘dict‘:

numLeafs += getNumLeafs(secondDict[key])

else:

numLeafs += 1

return numLeafs

def getTreeDepth(myTree):

maxDepth = 0

firstStr = list(myTree.keys())[0] # 这个是改的地方，原来myTree.keys()返回的是dict_keys类，不是列表，运行会报错。有好几个地方这样

secondDict = myTree[firstStr]

for key in secondDict.keys():

if type(secondDict[key]).__name__ == ‘dict‘:

thisDepth = 1 + getTreeDepth(secondDict[key])

else:

thisDepth = 1

if thisDepth > maxDepth:

maxDepth = thisDepth

return maxDepth

# ---------分割线-------------

# 制图

def createPlot(inTree):

fig = plt.figure(1, facecolor=‘white‘)

fig.clf()

axprops = {‘xticks‘: None, ‘yticks‘: None}

createPlot.ax1 = plt.subplot(111, frameon=False)

plotTree.totalW = float(getNumLeafs(inTree)) # 全局变量宽度 = 叶子数目

plotTree.totalD = float(getTreeDepth(inTree)) # 全局变量高度 = 深度

plotTree.xOff = -0.5/plotTree.totalW

plotTree.yOff = 1.0

plotTree(inTree, (0.5, 1.0), ‘‘)

plt.show()

def plotTree(myTree, parentPt, nodeTxt):

numLeafs = getNumLeafs(myTree)

depth = getTreeDepth(myTree)

firstStr = list(myTree.keys())[0]

# cntrPt文本中心点， parentPt指向文本中心的点

cntrPt = (plotTree.xOff + (1.0 + float(numLeafs))/2.0/plotTree.totalW, plotTree.yOff)

plotMidText(cntrPt, parentPt, nodeTxt)

plotNode(firstStr, cntrPt, parentPt, descisionNode)

seconDict = myTree[firstStr]

plotTree.yOff = plotTree.yOff - 1.0/plotTree.totalD

for key in seconDict.keys():

if type(seconDict[key]).__name__ == ‘dict‘:

plotTree(seconDict[key], cntrPt, str(key))

else:

plotTree.xOff = plotTree.xOff + 1.0/plotTree.totalW

plotNode(seconDict[key], (plotTree.xOff, plotTree.yOff), cntrPt, leafNode)

plotMidText((plotTree.xOff, plotTree.yOff), cntrPt, str(key))

plotTree.yOff = plotTree.yOff + 1.0/plotTree.totalD

def plotMidText(cntrPt, parentPt, txtString):

xMid = (parentPt[0] - cntrPt[0])/2.0 + cntrPt[0]

yMid = (parentPt[1] - cntrPt[1])/2.0 + cntrPt[1]

createPlot.ax1.text(xMid, yMid, txtString, va=‘center‘, ha=‘center‘, rotation=30)

# createPlot(myTree)

这个treePlotter导入了就可以把原来得到的决策树模型导入啦，而且要注意是以字典形式导入，所以保存和导入文件的时候最好用json。

发布5分钟之后，突然发现已经有人改过了，那就只算是个学习笔记吧 -  -