python基础:
中间可能会遇到的一些问题:主要是Python2.x与3.x的差别导致的:
#Clearly you’re passing in d.keys() to your shuffle function.
# Probably this was written with python2.x (when d.keys() returned a list). With python3.x, d.keys() returns a dict_keys object which behaves a lot more like a set than a list.
# As such, it can’t be indexed.
#The solution is to pass list(d.keys()) (or simply list(d)) to shuffle.
或者中文可以参照这位csdn的:firstStr = myTree.keys()[0]
下面是绘制树形图的代码:
import matplotlib.pyplot as plt decisionNode = dict(boxstyle="sawtooth",fc="0.8") leafNode = dict(boxstyle="round4",fc="0.8") arrow_args = dict(arrowstyle="<-") 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) def createPlot(): fig = plt.figure(1, facecolor='white') fig.clf() createPlot.ax1 = plt.subplot(111, frameon=False) plotNode(U'decision node', (0.5, 0.1), (0.1, 0.5), decisionNode) plotNode(U'leaf node', (0.8, 0.1), (0.3, 0.8), leafNode) plt.show() def getNumLeafs(myTree): numLeafs = 0 firstStr = list(myTree.keys())#Clearly you're passing in d.keys() to your shuffle function. # Probably this was written with python2.x (when d.keys() returned a list). With python3.x, d.keys() returns a dict_keys object which behaves a lot more like a set than a list. # As such, it can't be indexed. #The solution is to pass list(d.keys()) (or simply list(d)) to shuffle. firstStr=firstStr[0] secondDict = myTree[firstStr] for key in secondDict.keys(): if type(secondDict[key]).__name__=='dict': numLeafs = 1+getNumLeafs(secondDict[key]) else: numLeafs+=1 return numLeafs def getTreeDepth(myTree): maxDepth = 0 firstStr = list(myTree.keys()) firstStr=firstStr[0] 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 def retrieveTree(i): listOfTrees =[{'no surfacing': {0: 'no', 1: {'flippers': {0: 'no', 1: 'yes'}}}}, {'no surfacing': {0: 'no', 1: {'flippers': {0: {'head': {0: 'no', 1: 'yes'}}, 1: 'no'}}}} ] return listOfTrees[i] 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) def plotTree(myTree, parentPt, nodeTxt): # if the first key tells you what feat was split on numLeafs = getNumLeafs(myTree) # this determines the x width of this tree depth = getTreeDepth(myTree) firstStr = list(myTree.keys()) firstStr=firstStr[0]# the text label for this node should be this cntrPt = (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.totalD for 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)) # recursion else: # it's a leaf node print the leaf node plotTree.xOff = plotTree.xOff + 1.0 / plotTree.totalW plotNode(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 def createPlot(inTree): fig = plt.figure(1, facecolor='white') fig.clf() axprops = dict(xticks=[], yticks=[]) createPlot.ax1 = plt.subplot(111, frameon=False, **axprops) #no ticks #createPlot.ax1 = plt.subplot(111, frameon=False) #ticks for demo puropses plotTree.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()
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