[Julia] 稀疏数组

生成稀疏数组

代码	解释
sparse(index, value)	用指标对应值的方式,其他元素为0
spzeros(dims)	生成相应维数的稀疏零数组
sprand(T, dims, p)	生成类型 T, 相应维数的[0,1]均匀随机数组, 稀疏概率为 1-p
sprandn(T, dims, p)	生成类型 T, 相应维数的标准正态随机数组, 稀疏概率为 1-p
spdiagm(vec)	生成以向量数组 vec 构成对角线的稀疏矩阵
blockdiag(mat1,mat2,…)	生成以 mat1, mat2 …构成的对角型分块稀疏矩阵

using SparseArrays
A = sparse([1, 1, 2, 3], [1, 3, 2, 3], [0, 1, 2, 0])

3×3 SparseMatrixCSC{Int64, Int64} with 4 stored entries:
0 ⋅ 1
⋅ 2 ⋅
⋅ ⋅ 0

nonzeros(A)

4-element Vector{Int64}:
0
2
1
0

A=sparse([0.0 0.0 1.0;
         0.0 2.0 0.0;
         0 0 0.0 ])
nonzeros(A)

2-element Vector{Float64}:
2.0
1.0

spzeros(2,3)

2×3 SparseMatrixCSC{Float64, Int64} with 0 stored entries:
⋅ ⋅ ⋅
⋅ ⋅ ⋅

 sprand(Bool, 2, 3, 0.5)

2×3 SparseMatrixCSC{Bool, Int64} with 3 stored entries:
1 ⋅ ⋅
1 ⋅ 1

sprand(Float64, 2,3, 0.25)

2×3 SparseMatrixCSC{Float64, Int64} with 2 stored entries:
⋅ 0.114653 ⋅
⋅ 0.584111 ⋅

sprandn(Float64, 2,3, 0.25)

2×3 SparseMatrixCSC{Float64, Int64} with 1 stored entry:
⋅ ⋅ ⋅
⋅ 1.58349 ⋅

spdiagm([1,2,3])

3×3 SparseMatrixCSC{Int64, Int64} with 3 stored entries:
1 ⋅ ⋅
⋅ 2 ⋅
⋅ ⋅ 3
blockdiag(sprand(3,3,0.25), sprand(2,2,0.75))