我有以下使用Numpy的Python代码:
p = np.diag(1.0 / np.array(x))
我如何将其转换为稀疏矩阵p2
,使其与p
具有相同的值,而不必先创建p
?
我有以下使用Numpy的Python代码:
p = np.diag(1.0 / np.array(x))
我如何将其转换为稀疏矩阵p2
,使其与p
具有相同的值,而不必先创建p
?
scipy.sparse.spdiags
(起初可能会感到很困惑)scipy.sparse.dia_matrix
和/或 scipy.sparse.lil_diags
来构建稀疏矩阵(取决于所需的矩阵格式...)spdiags
:import numpy as np
import scipy as sp
import scipy.sparse
x = np.arange(10)
# "0" here indicates the main diagonal...
# "y" will be a dia_matrix type of sparse array, by default
y = sp.sparse.spdiags(x, 0, x.size, x.size)
p = sparse.dia_matrix(1.0 / np.array(x), shape=(len(x), len(x)));