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numpy数组子集错误

[英]numpy array subsetting error

I have a numpy sparse matrix A1 of type 我有一个类型的numpy稀疏矩阵A1

 scipy.sparse.dok.dok_matrix

with integer values. 与整数值。 I'm trying to use it to subset another integer matrix A2 of type 我正在尝试使用它来子集另一类型的整数矩阵A2

 numpy.matrixlib.defmatrix.matrix

by 通过

 A2[A1>0]

Both of them have shape (1,10000). 它们都具有形状(1,10000)。 Although it works well to use 虽然很好用

 A1[A1>0]

I get the following error: 我收到以下错误:

>> A2[A1>0]

Traceback (most recent call last):

File "<ipython-input-250-19959d659dc5>", line 1, in <module>
  edge_counts[nodes>0]

File "//anaconda/lib/python2.7/site-packages/numpy/matrixlib/defmatrix.py", line 284, in __getitem__
out = N.ndarray.__getitem__(self, index)

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

IndexError is telling that A1 > 0 is not an object compatible with indexing. IndexError告诉A1 > 0不是与索引兼容的对象。 You can investigate easily with: 您可以使用以下方法轻松进行调查:

In []: type(A1 > 0)
Out[]: scipy.sparse.csr.csr_matrix

And you can turn in to a bool array by converting A1 to an array first, using toarray() : 您可以通过使用toarray()首先将A1转换为数组来生成bool数组:

In []: type(A1.toarray() > 0)
Out[]: numpy.ndarray

Then A2[A1.toarray() > 0] should work just fine. 然后A2[A1.toarray() > 0]应该可以正常工作。

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