我正在尝试解决以下方程组:
我使用scipy.sparse.diags
生成稀疏矩阵,然后我想解决一个方程组。目前,我正在使用scipy.sparse.linalg
(对于不可重现的示例道歉):
AMatrix = sparse.diags([xx,yy,zz,Param.Lambda[0], Param.Lambda[1]], [-1,0,1,+I, -I])
BMatrix = sparse.diags([BDiag], [0]) - AMatrix
VNew = slinalg.spsolve(BMatrix, bVector)
然而,有时我会
/usr/local/lib/python2.7/site-packages/scipy/sparse/compressed.py:690: SparseEfficiencyWarning: Changing the sparsity structure of a csc_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
我found out that一种方法是在创建时强制(失去性能)csr
矩阵。会有更高效的替代方案吗?