令我惊讶的是，以下操作失败：
In [1]: import numpy as np
In [2]: from scipy import sparse
In [3]: A = sparse.rand(10, 4, format='csc')
In [4]: b = np.zeros(10)
In [5]: b += A[:, 0]
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-7-8704096141d1> in <module>
----> 1 b += A[:, 0]
~/anaconda3/lib/python3.6/site-packages/scipy/sparse/base.py in __radd__(self, other)
420
421 def __radd__(self,other): # other + self
--> 422 return self.__add__(other)
423
424 def __sub__(self, other): # self - other
~/anaconda3/lib/python3.6/site-packages/scipy/sparse/base.py in __add__(self, other)
414 return self._add_sparse(other)
415 elif isdense(other):
--> 416 other = broadcast_to(other, self.shape)
417 return self._add_dense(other)
418 else:
~/anaconda3/lib/python3.6/site-packages/numpy/lib/stride_tricks.py in broadcast_to(array, shape, subok)
171 [1, 2, 3]])
172 """
--> 173 return _broadcast_to(array, shape, subok=subok, readonly=True)
174
175
~/anaconda3/lib/python3.6/site-packages/numpy/lib/stride_tricks.py in _broadcast_to(array, shape, subok, readonly)
126 broadcast = np.nditer(
127 (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
--> 128 op_flags=[op_flag], itershape=shape, order='C').itviews[0]
129 result = _maybe_view_as_subclass(array, broadcast)
130 if needs_writeable and not result.flags.writeable:
ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (10,) and requested shape (10,1)
一个明显但昂贵的解决方案是在将
.toarray()添加到b之前调用A[:, 0]。内置的scipy / numpy函数可以有效地避免这种情况吗？ 最佳答案
您可以直接使用csc格式：
if not A.has_canonical_format: # make sure indices are unique
A.sum_duplicates()
l, r = A.indptr[idx:idx+2] # find the relevant column
b[A.indices[l:r]] += A.data[l:r] # add nonzero values at their offsets
关于python - 高效地将稀疏(CSC)矩阵列添加到形状正确的密集numpy数组中，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/53538945/