TypeError：稀疏矩阵长度不明确;在scipy中调用lil_matrix.diagonal()时使用getnnz()或shape[0]

8hhllhi2 于 2022-11-10 发布在 Go

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我尝试使用以下代码来获取以lil_matrix存储的稀疏矩阵的对角线之和：

sm1 = np.sum(board.diagonal(k=i1-row1))
sm2 = np.sum(board.diagonal(k=i2-row2))

然而，这给了我一个

TypeError: sparse matrix length is ambiguous; use getnnz() or shape[0]

type(board)返回<class 'scipy.sparse._lil.lil_matrix'>
row1, row2, i1, i2都是整数。有趣的是，如果我调用print(np.sum(board.diagonal(k=i1-row1))，它会在抛出类型错误之前打印正确的结果。
我怀疑这个错误与向csr矩阵的转换有关，因为错误消息中提到了return self.tocsr().diagonal(k=k)，调用board.tocsr()也会抛出同样的错误。
提前感谢！
下面是完整的错误日志：

Traceback (most recent call last):
  File "/usr/lib/python3.8/code.py", line 90, in runcode
    exec(code, self.locals)
  File "<input>", line 1, in <module>
  File "/snap/pycharm-professional/285/plugins/python/helpers/pydev/_pydev_bundle/pydev_umd.py", line 198, in runfile
    pydev_imports.execfile(filename, global_vars, local_vars)  # execute the script
  File "/snap/pycharm-professional/285/plugins/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "/home/noah/PycharmProjects/nQueens/sa_sparse.py", line 94, in <module>
    y.run()
  File "/home/noah/PycharmProjects/nQueens/sa_sparse.py", line 63, in run
    self.swap(newSol)
  File "/home/noah/PycharmProjects/nQueens/sa_sparse.py", line 34, in swap
    newCost = self.calcFastCost(board.board, row1, row2)
  File "/home/noah/PycharmProjects/nQueens/sa_sparse.py", line 47, in calcFastCost
    sm1 = np.sum(board.diagonal(k=i1-row1))
  File "/home/noah/nQueens/lib/python3.8/site-packages/scipy/sparse/_base.py", line 1214, in diagonal
    return self.tocsr().diagonal(k=k)
  File "/home/noah/nQueens/lib/python3.8/site-packages/scipy/sparse/_lil.py", line 459, in tocsr
    _csparsetools.lil_get_lengths(self.rows, indptr[1:])
  File "_csparsetools.pyx", line 111, in scipy.sparse._csparsetools.lil_get_lengths
  File "_csparsetools.pyx", line 117, in scipy.sparse._csparsetools._lil_get_lengths_int32
  File "/home/noah/nQueens/lib/python3.8/site-packages/scipy/sparse/_base.py", line 345, in __len__
    raise TypeError("sparse matrix length is ambiguous; use getnnz()"
TypeError: sparse matrix length is ambiguous; use getnnz() or shape[0]

scipy

来源：https://stackoverflow.com/questions/72629046/typeerror-sparse-matrix-length-is-ambiguous-use-getnnz-or-shape0-when-call

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按热度按时间

sdnqo3pr1#

您的scipy版本是什么？在当前设置中，我可以创建一个lil并获得对角线：

In [16]: M = sparse.lil_matrix(np.eye(3))
In [17]: M
Out[17]: 
<3x3 sparse matrix of type '<class 'numpy.float64'>'
    with 3 stored elements in List of Lists format>    
In [18]: M.A
Out[18]: 
array([[1., 0., 0.],
       [0., 1., 0.],
       [0., 0., 1.]])

转换为csr没有问题，对角线也没有问题：

In [19]: M.tocsr()
Out[19]: 
<3x3 sparse matrix of type '<class 'numpy.float64'>'
    with 3 stored elements in Compressed Sparse Row format>    
In [20]: M.diagonal()
Out[20]: array([1., 1., 1.])

但是询问len时，会给予错误：

In [21]: len(M)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [21], in <cell line: 1>()
----> 1 len(M)

File ~\anaconda3\lib\site-packages\scipy\sparse\base.py:291, in spmatrix.__len__(self)
    290 def __len__(self):
--> 291     raise TypeError("sparse matrix length is ambiguous; use getnnz()"
    292                     " or shape[0]")

TypeError: sparse matrix length is ambiguous; use getnnz() or shape[0]

对于这个lil，其他的步骤就可以了：

In [22]: M.nnz         
Out[22]: 3    
In [23]: M.getnnz()
Out[23]: 3
In [24]: M.shape
Out[24]: (3, 3)

lil将值存储在两个对象dtype数组中：

In [26]: M.data
Out[26]: array([list([1.0]), list([1.0]), list([1.0])], dtype=object)
In [27]: M.rows
Out[27]: array([list([0]), list([1]), list([2])], dtype=object)

如果我通过删除一个rows元素来破坏矩阵，我会得到一个非常不同的错误。
看起来错误发生在tocsr中，在这个块中，它从rows元素的长度创建indptr：

M, N = self.shape
    if M*N <= np.iinfo(np.int32).max:
        # fast path: it is known that 64-bit indexing will not be needed.
        idx_dtype = np.int32
        indptr = np.empty(M + 1, dtype=idx_dtype)
        indptr[0] = 0
        _csparsetools.lil_get_lengths(self.rows, indptr[1:])
        np.cumsum(indptr, out=indptr)
        nnz = indptr[-1]

lil_get_lengths是经过编译的代码，它遍历rows的元素，并将它们的长度放入第二个参数中。

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TypeError：稀疏矩阵长度不明确;在scipy中调用lil_matrix.diagonal()时使用getnnz()或shape[0]

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