假设我想从 scipy.sparse.csr_matrix
中删除对角线。有这样做的有效方法吗?我看到在 sparsetools
模块中有 C
函数来返回对角线。
基于其他 SO 答案 here和 here我目前的做法如下:
def csr_setdiag_val(csr, value=0):
"""Set all diagonal nonzero elements
(elements currently in the sparsity pattern)
to the given value. Useful to set to 0 mostly.
"""
if csr.format != "csr":
raise ValueError('Matrix given must be of CSR format.')
csr.sort_indices()
pointer = csr.indptr
indices = csr.indices
data = csr.data
for i in range(min(csr.shape)):
ind = indices[pointer[i]: pointer[i + 1]]
j = ind.searchsorted(i)
# matrix has only elements up until diagonal (in row i)
if j == len(ind):
continue
j += pointer[i]
# in case matrix has only elements after diagonal (in row i)
if indices[j] == i:
data[j] = value
然后我跟着
csr.eliminate_zeros()
如果不编写自己的 Cython
代码,这是我能做的最好的事情吗?
最佳答案
根据@hpaulj 的评论,我创建了一个 IPython Notebook can be seen on nbviewer .这表明在提到的所有方法中,以下是最快的(假设 mat
是一个稀疏 CSR 矩阵):
mat - scipy.sparse.dia_matrix((mat.diagonal()[scipy.newaxis, :], [0]), shape=(one_dim, one_dim))
关于python - 在 scipy 中删除/设置稀疏矩阵的非零对角线元素,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/22660374/