Question

我有一个矩阵，前10行是质心，最后10行是点。我想计算成对欧几里德距离。

mat = matrix(c(25,125, 44,105, 29,97,  35,63,  55,63, 
           42,57,  23,40,  64,37,  33,22,  55,20,
           28,145, 65,140, 50,130, 38,115, 55,118,
           50,90,  43,83,  63,88,  50,60, 50,30), 
           ncol=2, byrow=T)

centroids = mat[1:10,]
points = mat[11:20,]

eudis = function(x, y) { sqrt( sum( (x-y)^2 ) ) } # define Euclidean distance

我尝试使用如下的外部产品。

outer(centroids, points, FUN = eudis)

但它不会奏效。我认为我在处理类似情况的外部产品方面取得了成功。有人能让它发挥作用吗？提前谢谢！

Answer 1

我想你想要一个显示每个质心和每个点之间距离的矩阵。要使用outer执行此操作，您可以迭代索引：

outer(1:10, 1:10, FUN=Vectorize(function(x, y) eudis(centroids[x,], points[y,])))
           [,1]      [,2]      [,3]     [,4]     [,5]     [,6]     [,7]     [,8]      [,9]    [,10]
 [1,]  20.22375  42.72002  25.49510 16.40122 30.80584 43.01163 45.69464 53.03772 69.641941 98.23441
 [2,]  43.08132  40.81666  25.70992 11.66190 17.02939 16.15549 22.02272 25.49510 45.398238 75.23962
 [3,]  48.01042  56.08030  39.11521 20.12461 33.42155 22.13594 19.79899 35.17101 42.544095 70.21396
 [4,]  82.29824  82.63776  68.65858 52.08647 58.52350 30.88689 21.54066 37.53665 15.297059 36.24914
 [5,]  86.33076  77.64664  67.18631 54.70832 55.00000 27.45906 23.32381 26.24881  5.830952 33.37664
 [6,]  89.10668  86.12781  73.43705 58.13777 62.36986 33.95585 26.01922 37.44329  8.544004 28.16026
 [7,] 105.11898 108.46197  93.96276 76.48529 84.30896 56.82429 47.42362 62.48200 33.600595 28.79236
 [8,] 113.84200 103.00485  94.04786 82.21922 81.49847 54.81788 50.56679 51.00980 26.925824 15.65248
 [9,] 123.10158 122.26201 109.32978 93.13431 98.48858 70.09280 61.81424 72.49828 41.629317 18.78829
[10,] 127.88276 120.41595 110.11358 96.50907 98.00000 70.17834 64.13267 68.46897 40.311289 11.18034

实际上，您需要对eudis函数进行矢量化以使其起作用，因为向量通过outer传递给函数，但不是eudis期望的方式。

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