23_5.py

def genDistribution(xMean, xSD, yMean, ySD, n, namePrefix):
    samples = []
    for s in range(n):
        x = random.gauss(xMean, xSD)
        y = random.gauss(yMean, ySD)
        samples.append(Example(namePrefix+str(s), [x,y]))
    return samples

def plotSamples(samples, marker):
    xVals, yVals = [], []
    for s in samples:
        x = s.getFeatures()[0]
        y = s.getFeatures()[1]
        pylab.annotate(s.getName(), xy = (x,y), mytext=(x+0.13,y-0.07), fontsize='x-large')
        xVals.append(x)
        yVals.append(y)
    pylab.plot(xVals, yVals, marker)

def contrivedTest(numTrials, k, verbose = False):
    xMean = 3
    xSD = 1
    yMean = 5
    ySD = 1
    n = 10
    d1Samples = genDistribution(xMean, xSD, yMean, ySD, n, 'A')
    plotSamples(d1Samples, 'k^')
    d2Samples = genDistribution(xMean+3, xSD, yMean+1, ySD, n, 'B')
    plotSamples(d2Samples, 'ko')
    clusters = trymeans(d1Samples+d2Samples, k, numTrials, verbose)
    print('Final Result')
    for c in clusters:
        print(" ", c)