please fix this so it will produce an output, when I run it nothing happens...

import pylab

def stdDev(X): mean = sum(X)/len(X) std = 0 for e in X: std += (e-mean)**2 return (std/len(X))**0.5

def minkowskiDist(v1, v2, p): dist = np.sum((np.abs(v1-v2))**p) ''' for i in range(len(v1)): dist += abs(v1[i]-v2[i])**p ''' return dist**(1/p)

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), xytext=(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 = tryKmeans(d1Samples+d2Samples, Example, k, numTrials, verbose) print("Final result:") for c in clusters: print(' ', c)

def contrivedTest2(numTrials, k, verbose = False): xMean = 3 xSD = 1 yMean = 5 ySD = 1 n = 8 d1Samples = genDistribution(xMean, xSD, yMean, ySD, n, 'A') plotSamples(d1Samples, 'k^') d2Samples = genDistribution(xMean + 3, xSD, yMean, ySD, n, 'B') plotSamples(d2Samples, 'ko') d3Samples = genDistribution(xMean, xSD, yMean+3, ySD, n, 'C') plotSamples(d3Samples, 'kx') clusters = tryKmeans(d1Samples + d2Samples + d3Samples, k, numTrials, verbose) pylab.ylim(0,11) print('Final result has dissimilarity', round(dissimilarity(clusters), 3)) for c in clusters: print('', c)