" ValueError:包含多个元素的数组的真值是不明确的"

I am trying to execute the following code :( this is a simple code for Kmeans algorithm which has been written in Python.The two-step procedure continues until the assignments of clusters and centroids no longer change. The convergence is guaranteed but the solution might be a local minimum. In practice, the algorithm is run multiple times and averaged.

我正在尝试执行以下代码:(这是用Python编写的Kmeans算法的简单代码。两步过程继续，直到集群和质心的分配不再改变。收敛是有保证的，但解决方案可能是局部最小值。在实践中，该算法运行多次，平均。

import numpy as np
import random
from numpy import *

points = [[1,1],[1.5,2],[3,4],[5,7],[3.5,5],[4.5,5], [3.5,4]]


def cluster(points,center):
  clusters = {}

  for x in points:

    z= min([(i[0], np.linalg.norm(x-center[i[0]]))  for i in enumerate(center)], key=lambda t:t[1])

    try:
      clusters[z].append(x)
    except KeyError:
      clusters[z]=[x]

  return clusters

def update(oldcenter,clusters):

 d=[]
 r=[]
 newcenter=[]

 for k in clusters:
  if k[0]==0: 
   d.append(clusters[(k[0],k[1])])

  else:
   r.append(clusters[(k[0],k[1])])

 c=np.mean(d, axis=0)
 u=np.mean(r,axis=0)
 newcenter.append(c)
 newcenter.append(u)

 return newcenter

def shouldStop(oldcenter,center, iterations):
    MAX_ITERATIONS=4
    if iterations > MAX_ITERATIONS: return True
    return (oldcenter == center)

def kmeans():   
  points = np.array([[1,1],[1.5,2],[3,4],[5,7],[3.5,5],[4.5,5], [3.5,4]])
  clusters={}
  iterations = 0
  oldcenter=([[],[]])   
  center= ([[1,1],[5,7]])                        

  while not shouldStop(oldcenter, center, iterations):
        # Save old centroids for convergence test. Book keeping.
        oldcenter=center
        iterations += 1
        clusters=cluster(points,center)  
        center=update(oldcenter,clusters)

  return (center,clusters)

kmeans()

but now i stuck. Can anybody help me with this, please?

但是现在我卡住了。有人能帮我一下吗?

Traceback (most recent call last):
  File "has_converged.py", line 64, in <module>
    (center,clusters)=kmeans()
  File "has_converged.py", line 55, in kmeans
    while not shouldStop(oldcenter, center, iterations):
  File "has_converged.py", line 46, in shouldStop
    return (oldcenter == center)
ValueError: The truth value of an array with more than one element is ambiguous.
 Use a.any() or a.all()

1 个解决方案

#1

As the error indicates, you cannot compare two arrays with == in NumPy:

如错误所示，不能将两个数组与NumPy中的== =进行比较:

>>> a = np.random.randn(5)
>>> b = np.random.randn(5)
>>> a
array([-0.28636246,  0.75874234,  1.29656196,  1.19471939,  1.25924266])
>>> b
array([-0.13541816,  1.31538069,  1.29514837, -1.2661043 ,  0.07174764])
>>> a == b
array([False, False, False, False, False], dtype=bool)

The result of == is an element-wise boolean array. You can tell whether this array is all true with the all method:

==是一个元素的布尔数组。您可以通过所有方法判断该数组是否为真:

>>> (a == b).all()
False

That said, checking whether the centroids changed in this way is unreliable because of rounding. You might want to use np.allclose instead.

也就是说，检查质心是否因为四舍五入而以这种方式改变是不可靠的。你可能想用np。allclose代替。

#1