import matplotlib.pyplot as plt#这里是对绘制是图形属性的一些定义，可以不用管，主要是后面的算法
decisionNode = dict(boxstyle="sawtooth", fc="0.8")
leafNode = dict(boxstyle="round4", fc="0.8")
arrow_args = dict(arrowstyle="<-")#这是递归计算树的叶子节点个数，比较简单
def getNumLeafs(myTree):numLeafs = 0firstStr = myTree.keys()[0]secondDict = myTree[firstStr]for key in secondDict.keys():if type(secondDict[key]).__name__=='dict':#test to see if the nodes are dictonaires, if not they are leaf nodesnumLeafs += getNumLeafs(secondDict[key])else:   numLeafs +=1return numLeafs
#这是递归计算树的深度，比较简单
def getTreeDepth(myTree):maxDepth = 0firstStr = myTree.keys()[0]secondDict = myTree[firstStr]for key in secondDict.keys():if type(secondDict[key]).__name__=='dict':#test to see if the nodes are dictonaires, if not they are leaf nodesthisDepth = 1 + getTreeDepth(secondDict[key])else:   thisDepth = 1if thisDepth > maxDepth: maxDepth = thisDepthreturn maxDepth
#这个是用来一注释形式绘制节点和箭头线，可以不用管
def plotNode(nodeTxt, centerPt, parentPt, nodeType):createPlot.ax1.annotate(nodeTxt, xy=parentPt,  xycoords='axes fraction',xytext=centerPt, textcoords='axes fraction',va="center", ha="center", bbox=nodeType, arrowprops=arrow_args )
#这个是用来绘制线上的标注，简单
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)
#重点，递归，决定整个树图的绘制，难（自己认为）
def plotTree(myTree, parentPt, nodeTxt):#if the first key tells you what feat was split onnumLeafs = getNumLeafs(myTree)  #this determines the x width of this treedepth = getTreeDepth(myTree)firstStr = myTree.keys()[0]     #the text label for this node should be thiscntrPt = (plotTree.xOff + (1.0 + float(numLeafs))/2.0/plotTree.totalW, plotTree.yOff)plotMidText(cntrPt, parentPt, nodeTxt)plotNode(firstStr, cntrPt, parentPt, decisionNode)secondDict = myTree[firstStr]plotTree.yOff = plotTree.yOff - 1.0/plotTree.totalDfor key in secondDict.keys():if type(secondDict[key]).__name__=='dict':#test to see if the nodes are dictonaires, if not they are leaf nodes   plotTree(secondDict[key],cntrPt,str(key))        #recursionelse:   #it's a leaf node print the leaf nodeplotTree.xOff = plotTree.xOff + 1.0/plotTree.totalWplotNode(secondDict[key], (plotTree.xOff, plotTree.yOff), cntrPt, leafNode)plotMidText((plotTree.xOff, plotTree.yOff), cntrPt, str(key))plotTree.yOff = plotTree.yOff + 1.0/plotTree.totalD
#if you do get a dictonary you know it's a tree, and the first element will be another dict#这个是真正的绘制，上边是逻辑的绘制
def createPlot(inTree):fig = plt.figure(1, facecolor='white')fig.clf()axprops = dict(xticks=[], yticks=[])createPlot.ax1 = plt.subplot(111, frameon=False)    #no ticksplotTree.totalW = float(getNumLeafs(inTree))plotTree.totalD = float(getTreeDepth(inTree))plotTree.xOff = -0.5/plotTree.totalW; plotTree.yOff = 1.0;plotTree(inTree, (0.5,1.0), '')plt.show()#这个是用来创建数据集即决策树
def retrieveTree(i):listOfTrees =[{'no surfacing': {0:{'flippers': {0: 'no', 1: 'yes'}}, 1: {'flippers': {0: 'no', 1: 'yes'}}, 2:{'flippers': {0: 'no', 1: 'yes'}}}},{'no surfacing': {0: 'no', 1: {'flippers': {0: {'head': {0: 'no', 1: 'yes'}}, 1: 'no'}}}}]return listOfTrees[i]createPlot(retrieveTree(0))

def plotTree(myTree, parentPt, nodeTxt):#if the first key tells you what feat was split onnumLeafs = getNumLeafs(myTree)  #this determines the x width of this treedepth = getTreeDepth(myTree)firstStr = myTree.keys()[0]     #the text label for this node should be thiscntrPt = (plotTree.xOff + (1.0 + float(numLeafs))/2.0/plotTree.totalW, plotTree.yOff)plotMidText(cntrPt, parentPt, nodeTxt)plotNode(firstStr, cntrPt, parentPt, decisionNode)secondDict = myTree[firstStr]plotTree.yOff = plotTree.yOff - 1.0/plotTree.totalDfor key in secondDict.keys():if type(secondDict[key]).__name__=='dict':#test to see if the nodes are dictonaires, if not they are leaf nodes   plotTree(secondDict[key],cntrPt,str(key))        #recursionelse:   #it's a leaf node print the leaf nodeplotTree.xOff = plotTree.xOff + 1.0/plotTree.totalWplotNode(secondDict[key], (plotTree.xOff, plotTree.yOff), cntrPt, leafNode)plotMidText((plotTree.xOff, plotTree.yOff), cntrPt, str(key))plotTree.yOff = plotTree.yOff + 1.0/plotTree.totalD
#if you do get a dictonary you know it's a tree, and the first element will be another dictdef createPlot(inTree):fig = plt.figure(1, facecolor='white')fig.clf()axprops = dict(xticks=[], yticks=[])createPlot.ax1 = plt.subplot(111, frameon=False)    #no ticksplotTree.totalW = float(getNumLeafs(inTree))plotTree.totalD = float(getTreeDepth(inTree))plotTree.xOff = -0.5/plotTree.totalW; plotTree.yOff = 1.0;#totalW为整树的叶子节点树，totalD为深度plotTree(inTree, (0.5,1.0), '')plt.show()

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