block = np.random.rand(block_size, block_size) block = (block + block.T) / 2 B[i*block_size:(i+1)*block_size, i*block_size:(i+1)*block_size] = block return B n = 6 block_size = 2 B = generate_symmetric_block_diagonal_matrix(n, block_size) print("对称块对角矩阵B:") ...
Return a sparse matrix from diagonals. block_diag(mats[, format, dtype]) Build a block diagonal sparse matrix from provided matrices. tril(A[, k, format]) Return the lower triangular portion of a matrix in sparse format triu(A[, k, format]) Return the upper triangular portion of a matr...
A set of subroutines for detecting the block-tridiagonal structure of a Hamiltonian matrix and splitting it into series of diagonal and off-diagonal blocks is based on a new greedy algorithm with recursion. Additionally the developed software is equipped with a set of programs for computing complex...
Element j of this integer array gives the index of the element in thecolumns array that is first non-zero block in a rowj of the block matrix. pointerE Element j of this integer array gives the index of the element in thecolumns array that contains the last non-zero block in a rowj...
'asmatrix', 'asscalar', 'atleast_1d', 'atleast_2d', 'atleast_3d', 'average', 'bartlett', 'base_repr', 'bench', 'binary_repr', 'bincount', 'bitwise_and', 'bitwise_not', 'bitwise_or', 'bitwise_xor', 'blackman', 'block', 'bmat', 'bool', 'bool8', 'bool_', 'broadcast...
bsr_matrix: Block Sparse Row format lil_matrix: List of Lists format dok_matrix: Dictionary of Keys format coo_matrix: COOrdinate format (aka IJV, triplet format) dia_matrix: DIAgonal format 在用python进行科学运算时,常常需要把一个稀疏的np.array压缩,这时候就用到scipy库中的sparse.csr_matrix(cs...
bmat函数需要构建一个字符串或二维数组来描述块矩阵的结构,而block_diag函数则可以直接接受多个矩阵作为输入,并返回一个合并后的块对角矩阵。 输出结果矩阵: python print(combined_matrix) 完整的代码如下: python import numpy as np from scipy.linalg import block_diag def create_diag_matrix(): diagonal_...
DIA(Diagonal):对角格式,适合对角占优的矩阵。 BSR(Block Sparse Row):块行压缩格式,用于处理块稀疏矩阵。 创建稀疏矩阵 在SciPy中,可以使用scipy.sparse模块中的函数来创建稀疏矩阵。以下是一些示例: import numpy as np from scipy.sparse import csr_matrix, coo_matrix # 使用COO格式创建稀疏矩阵 row = np....
bsr_matrix bsr_matrix,全称Block Sparse Row matrix,这种压缩方式极其类似CSR格式,但使用分块的思想对稀疏矩阵进行按行压缩。所以,BSR适用于具有dense子矩阵的稀疏矩阵。该种矩阵有五种初始化方式,分别如下: bsr_matrix(D, [blocksize=(R,C)])
scipy.sparse的稀疏矩阵类型bsr_matrix：Block Sparse Row矩阵，通过arg1创建，支持指定形状、数据类型等。coo_matrix：Coordinate格式的稀疏矩阵，同样支持arg1的初始化，便于创建。csc_matrix：Compressed Sparse Column矩阵，可由bsr_matrix或coo_matrix创建，是常用类型之一。csr_matrix：Compressed Sparse Row...