Python KMeans.calculate_distance示例

示例#1

文件： plotter.py 项目： marcelxyz/kmeans-pyspark

def generate_distribution_plot(clusters, output_path):
    pyplot.clf()

    for centroid, points in clusters.iteritems():
        distances = sorted(
            [KMeans.calculate_distance(centroid, p) for p in points])

        pdf = stats.norm.pdf(distances, np.mean(distances), np.std(distances))

        pl.plot(distances, pdf)

    pl.savefig(output_path + 'distribution.png')

示例#2

文件： clustering_test.py 项目： marcelxyz/kmeans-pyspark

 def test_calculate_distance(self):
     a = (3, 5, 8, 15)
     b = (2, 3, 4, 5)
     distance = KMeans.calculate_distance(a, b)
     self.assertEqual(distance, 11)