treeplotter.py

import matplotlib.pyplot as plt
import trees

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.axl.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.axl = plt.subplot(111,frameon = False)
    plotNode('a decision node',(0.5,0.1),(0.1,0.5),decisionNode)
    plotNode('a leaf node',(0.8,0.1),(0.3,0.8),leafNode)
    plt.show()

def getNumLeafs(myTree):
    numleafs = 0
    firstStr = 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 = myTree.keys()[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):
    listOfTree = [{'no surfacing':{0:'no',1:{
        'flippers':{0:'no',1:'yes'}},3:'maybe'}},
        {'no surfacing':{0:'no',1:{'flippers':
            {0:{'head':{0:'no',1:'yes'}},1:'no'}}}}
            ]
    return listOfTree[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.axl.text(xMid,yMid,txtString,va = "center")

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 = myTree.keys()[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

def createPlot(inTree):
    fig = plt.figure(1,facecolor = 'white')
    fig.clf()
    axprops = dict(xticks = [],yticks = [])
    createPlot.axl = plt.subplot(111,frameon = False,**axprops)
    plotTree.totalW = float(getNumLeafs(inTree))
    plotTree.totalW = float(getTreeDepth(inTree))
    plotTree.xOff = -0.5/plotTree.totalW
    plotTree.yOff = 1.0
    plotTree(inTree,(0.5,1.0),'')
    plt.show()